ACA*GIScience Austria-Central Asia Centre for GIScience
Graz University of Technology Institute of Geoinformation
Tajik Agrarian University named after Shirinsho Shotemur
Austrian Academy of Sciences Institute for GIScience
enerGIS’10 Staff Development Workshop Geographic Information Systems (GIS) for Energy Issues in Central Asia
WORKBOOK September 20th – 24th, 2010 Dushanbe, Tajikistan
Editors: Scientific Workshop Organization: Gilbert Ahamer, Rainer Prüller, Johannes Scholz, Clemens Strauß, Carolina Lehner Workshop Committee: Josef Strobl, Izzatullo Sattori, Brigitte Winklehner Tajik Workshop Partner: Zamira Qodirova Verlag der Technischen Universität Graz www.ub.tugraz.at/Verlag ISBN: 978-3-85125-124-1 Date of publication: 20.09.2010 Bibliografische Information der Deutschen Bibliothek: Die Deutsche Bibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über http://dnb.ddb.de abrufbar. Link of the entire enerGIS‘10 Seminar: http://energis.tugraz.at (contains also the link to this workbook) Direct link for this publication: http://energis.tugraz.at/download/energis_workbook.pdf
Contents
Announcement Folder
5
Participants
7
Lecturers and Organization Team
11
The Rationale of this Workshop
13
Workshop presentations (in alphabetical order) Ahamer, G.: Climate Change Requirements are “Energetic”
15
Ahamer, G.: Renewable Energy Strategies in Central Asia
27
Boltayev, T.: GIS Training at Tashkent Institute of Irrigation and Melioration
39
Boronbaev, E.: GIS Spatial Tools: Design and Maintenance Optimization for Energy Efficiency, Passive and Healthy Buildings and Settlements, Adjusted to Daily and Seasonal Effects of the Sun, Wind and Environment
47
Boronbaev, E., Nazarkulova, A. & Strobl J.: Geoinformatics: Managing Energy, Resources, Environment
55
Griesebner, G.: Practical Session GPS Task
63
Imomov, S.: Application of Alternative Energy Sources
69
Navruzov, S.: Methodological Approach to Application of GIS & DSS for the Management of Water Resources of the Transboundary Rivers
71
Nazarkulov, K.: Feature Manipulation Engine Introduction Course – What is FME?
87
Paulus, G.: Theory on GIS & GPS – Selected Aspects
101
Prüller, R. & Strauß, C.: Practical Session GIS Tasks
163
Smith, A.: Hydrological Run-off Modelling for Determination of Hydroelectric Potential in ArcGIS, SAGA and GRASS
173
Smith, A.: Hydrological Run-off Modelling for Determination for Hydroelectric Potential; Practical using ArcGIS Spatial Analyst and Model Builder
187
Weidmann, Y.: Preparing Small-Scale Hydropower Projects for Private Sector Participation
199
Weidmann, Y.: Flächendeckende GIS-gestützte Identifikation potentieller Standorte von Kleinkraftwerken (Comprehensive GIS-Supported Identification of Potential Locations for Small Hydropower Plants)
217
motivation
data acquisition
data organization
data analysis
data presentation
Workshop Schedule
Sept 24th 2010
Sept 23rd 2010
Friday
Thursday
Wednesday
Tuesday
Monday
Sept 22rd 2010
Sept 21st 2010
Sept 20th 2010
afternoon 2:00 pm – 5:00 pm
morning 9:00 am – 12:30 pm
lunch
afternoon 2:00 pm – 5:00 pm
morning 9:00 am – 12:30 pm
lunch
afternoon 2:00 pm – 5:00 pm
morning 9:00 am – 12:30 pm
lunch
afternoon 2:00 pm – 5:00 pm
lunch Welcome, opening ceremony, introduction of all participants, morning administrative work, keynote presentations 9:00 am – 12:30 pm
Lecture: Motivation: GIS, energy and climate
Practical session: Preparation of fieldwork
Practical session: GPS Measurement
Practical session: Organization of spatial data
Conference session: Local application studies; presentations and poster session
Practical session: Spatial data analysis
Lecture
morning 9:00 am – 12:30 pm
lunch
afternoon 2:00 pm – 5:00 pm
Practical session: Presentation of spatial data (map making)
Presentation of user-created Maps, closing ceremony, handover certificate of attendance, administrative work
Austrian Academy of Sciences Institute for GISciences
Staff Development Workshop
Tajik Agrarian University named after Shirinsho Shotemur
September 20th – September 24th 2010, Dushanbe, Tajikistan
Geographic Information Systems (GIS) for Energy Issues in Central Asia
ener GIS
Graz University of Technology Institute of Geoinformation
Austrian-Central Asia Centre for GIScience
ACA*GIScience
Workshop Announcement
Topics presented at the Workshop The aim of the Staff Development Workshop enerGIS is to provide participants with an introduction to Geographic Information Systems (GIS) based on energy issues relevant for Central Asia. GIS is able to support decision-making processes by assisting the management of renewable energy resources like biomass, hydro, solar or wind energy. Workshop language: English, no translation provided.
Workshop Targets • • •
Theoretical and practical introduction to GIS and GPS. Understand the motivation for renewable energy sources. Ability to evaluate concrete energy potentials using GIS (ESRI ArcGIS).
Workshop Committee Academician Prof. Dr. Josef Strobl, Director of ÖAW/GIScience, Austria.
Academician Prof. DVSc Izzatullo Sattori, Rector of Tajik Agrarian University named after Shirinsho Shotemur, Tajikistan.
Prof. Dr. Brigitte Winklehner, President of Eurasia-Pacific Uninet.
Workshop Lecturers (preliminary) Dr. Gilbert Ahamer, ÖAW, Uni Graz / Salzburg Global change, Climate change and energy strategies DI Mag. Rainer Prüller, TU Graz WebGIS, Geodatabases, Land use modelling DI Clemens Strauß, TU Graz GIS technologies, Location Based Services Mag. Gerald Griesebner, Uni Salzburg GPS and GIS lecturer Mag. Manfred Mittlböck, Uni Salzburg GIS modelling, GIS metadata Dr. Gernot Paulus, FH Kärnten Geoinformation, Spatial Decision Support Systems
Guidelines for Participation • • • •
Registration on http://www.energis.tugraz.at Sufficient knowledge of the English language Interest in basic training on GIS Completion of the mandatory ArcGIS tutorial on http://tinyurl.com/energis2010 and submitting of the received certificate.
End of registration period Notification of acceptance
Important Deadlines: Participants August 15th August 30th
Important Deadlines: Local application studies (15 min.) and lectures (45 min.) June 30th Deadline for extended abstracts (1000 words) July 17th Notification of acceptance and review of submitted extended abstract August 15th Deadline for final version of extended abstract (to be published on the website) August 30th Review of presentation slides / completed poster September 10th Handover of final version of presentation slides / poster
Website
http://energis.tugraz.at
Tajik Workshop Partner
Dr. Zamira Qodirova Tajik Agrarian University named after Shirinsho Shotemur email:
[email protected]
Austrian Workshop Organization Team
Dr. Gilbert Ahamer Austrian Academy of Sciences - GIScience email:
[email protected]
Participants
ABDULLOBEKOV Bekhzod Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur AKBAROV Odil Uzbekistan
[email protected] Tashkent Institute of Irrigation and Melioration AKHMEDOV Khamid Tajikistan
[email protected] AKRAMOV Abdugaffor Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur ALIEV Nozim Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur ALIMBEKOVA Nagima Kazakhstan
[email protected] Kyrgyz State University for Construction, Transportation and Architecture BAIBAGYSHOV Ermek Kyrgyzstan
[email protected] Naryn State University BOLTAYEV Tolmasbek Uzbekistan
[email protected] Tashkent Institute of Irrigation and Melioration BUTABEKOV Dilovar Tajikistan
[email protected] University of Central Asia DJURABOEV Djamshid Uzbekistan jamshi
[email protected] Tashkent Institute of Irrigation and Melioration
ERGESHOVA Gulshaan Kyrgyzstan
[email protected] Kyrgyz State University for Construction, Transportation and Architecture ERSHOVA Nataliya Kyrgyzstan
[email protected] Kyrgyz Russian Slavic University FROLOVA Galina Kyrgyzstan
[email protected] Kyrgyz Russian Slavic University HASANOV Anvar Tajikistan Tajik Agrarian University named after Shirinsho Shotemur IMOMOV Shavkat Uzbekistan
[email protected] Tashkent Institute of Irrigation and Melioration ISLOMOV Obid Tajikistan
[email protected] Tajik Ararian University named after Shirinsho Shotemur JANBOEV Ernist Kyrgyzstan
[email protected] Kyrgyz National Agrarian University JEENTAEV Erik Kyrgyzstan
[email protected] Kyrgyz State University for Construction, Transportation and Architecture KARIMOVA Gulmira Kyrgyzstan
[email protected] Kyrgyz National Agrarian University KEREMBAY Nurzhan Kazakhstan
[email protected] Al-Farabi Kazakh National University
KUKANOV Firdavs Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur MIRZOEV Mirasil Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur NASYROV Adylbek Kyrgyzstan
[email protected] Naryn State University named after S. Naamatov RAHMATILLOEV Foteh Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur SABOIEV Rizo
[email protected] University of Central Asia SAFAROV Hasan Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur UMIRBEKOV Atabek Uzbekistan
[email protected] Regional Environmental Center for Central Asia ZEVARSHOEV Askarsho Tajikistan Askarsho.Zeva
[email protected] Mountain Societies Development Support Programme
Lecturers and Organization Team
AHAMER Gilbert Austria
[email protected] Austrian Academy of Science / GIScience & University of Graz BORONBAEV Erkin Kyrgyzstan
[email protected] Kyrgyz State University for Construction, Transportation and Architecture GRIESEBNER Gerald Austria
[email protected] University of Salzburg KADIROVA Zamirakhon Tajikistan
[email protected] Tajik Agrarian University named after Shorinsho Shotemur LEHNER Carolina Austria
[email protected] Eurasia Pacific Uninet NAVRUZOV Sobir Tajikistan
[email protected] Technology University of Tajikistan NAZARKULOV Kydyr Kyrgyzstan
[email protected] Kyrgyz State University for Construction, Transportation and Architecture PAULUS Gernot Austria
[email protected] Carinthia University of Applied Sciences PRÜLLER Rainer Austria
[email protected] Graz University of Technology SATTORRI Izzatullo Tajikistan
[email protected] Tajik Agrarian University named after Shirinsho Shotemur
SMITH Andrew New Zealand / Kyrgyzstan
[email protected] Kyrgyz State University for Construction, Transportation and Agriculture STRAUSS Clemens Austria
[email protected] Graz University of Technology WEIDMANN Yvo Switzerland
[email protected] Ernst Basler + Partner AG
The Rationale of this Workshop Dear Participants! We welcome you to our common workshop “enerGIS’10” in Dushanbe. Thanks to everybody from several institutions who has contributed to this event by their continuous inputs! After “openSolarCA’09”1 the same organizing team presents you the enerGIS’10 workshop using Geographic Information Systems (GIS) for energy issues, targeted to Central Asia, again under the ACA*GIScience umbrella. The motivation stems from climate change that affects all regions, and in a characteristic pattern also Central Asia. Fossil energy has to be replaced by renewable sources such as solar, wind and small hydro plants that abate CO2 emissions. Both the causes and effects of climate change are highly spatially related and call for professional instruments to understand and manage georeferenced facts, threats and opportunities. This is the theoretical deliberation and rationale behind enerGIS’10. At right you find the overall guiding idea of the practical workshop procedure. The lectures and the hands-on sessions will lead you through 1. motivation 2. data acquisition 3. data organization 4. data analysis 5. data presentation. Please find more information on our website http://energis.tugraz.at/ where you can also download this workbook. Our target is to foster skills and knowledge and to contribute to future networking. We wish you an enjoyable and a successful workshop and look forward to seeing you and collaborating with you again! The Austrian organization team Rainer Prüller Clemens Strauß Johannes Scholz Carolina Lehner Gilbert Ahamer 1
See link at http://www.aca-giscience.org/opensolar/.
Climate change requirements are “energetic” Gilbert Ahamer “Global climate change” is increasingly understood by scientists and increasingly communicated to the global citizenship. Politicians increasingly take into account climate protection in their policies. Additionally, energy supply security determines national and supranational energy planning. Based on above two globally understood motivations, this staff development workshop “enerGIS’10” suggests to: 1. first to reduce energy demand while guaranteeing suitable energy services 2. second to use renewable energy sources to cover remaining energy demand. Especially the climate change motivation is explained on a global scale using simple models, long-term projections and using a logical chain of cause and effect symbolised by the puzzle below. The mechanisms of the greenhouse effect are explained and lead to the conclusion that only abatement of global CO2 concentration will lead to lowering CO2 concentrations – whereas deforestation is of comparatively lesser importance. Only considerable decrease of energy consumption as such can lead to lower CO2 emissions – fuel switch to biomass or other has lower potential. However, the remaining energy demand must be covered as much as possible by other fuels than fossil fuels because their remaining reserves would boost the global CO2 concentration to several times the pre-industrial value. Within a countries options to reduce (a) energy demand and (b) to switch towards renewable and carbon neutral energy sources, the following result of analyses is stated: (a) the highest technical, economic and practical potential lies in the sector of household, namely heating (b) a high potential is biomass energy which, however, cannot be implemented in Kyrgyzstan for climatic reasons. (c) Hence solar, hydro and wind potentials take the lead of practice-oriented climate protection. (d) Strategies of solar energy for heating or wind energy for electricity generation appear as best adapted to the Central Asian situations because of (i) their practicality, (ii) relative low capital input, (iii) adaptability to local circumstances and (iv) openness to personal craftwork of local citizens.
climate change
energy supply
energy demand
renewable potential
Welcome to enerGIS’10!
> www.oeaw.ac.at/giscience
Gilbert Ahamer
Thursday
Sept 23rd 2010
data analysis
Wednesday
data organization
Tuesday
Sept 21st 2010
Monday
Sept 20th 2010
Friday
Sept 24th 2010
data presentation
Sept 22rd 2010
Workshop Schedule
Workshop Announcement
afternoon Presentation of user-created Maps, closing ceremony, 2:00 pm – 5:00 pm handover certificate of attendance, administrative work lunch Practical session: Presentation of spatial data (map morning making) 9:00 am – 12:30 pm
Lecture
afternoon 2:00 pm – 5:00 pm lunch
Practical session: Spatial data analysis
Conference session: Local application studies; presentations and poster session
morning 9:00 am – 12:30 pm
afternoon 2:00 pm – 5:00 pm lunch
Practical session: Organization of spatial data
data acquisition
Practical session: GPS Measurement
Lecture: Motivation: GIS, energy and climate
motivation
morning 9:00 am – 12:30 pm
afternoon 2:00 pm – 5:00 pm lunch
Practical session: Preparation of fieldwork
ACA*GIScience Austrian-Central Asia Centre for GIScience
morning 9:00 am – 12:30 pm
afternoon 2:00 pm – 5:00 pm
lunch Welcome, opening ceremony, introduction of all morning participants, administrative work, keynote presentations 9:00 am – 12:30 pm
Graz University of Technology Institute of Geoinformation
ener GIS
Tajik Agrarian University named after Shirinsho Shotemur
Austrian Academy of Sciences Institute for GISciences
Staff Development Workshop
Geographic Information Systems (GIS) for Energy Issues in Central Asia September 20th – September 24th 2010, Dushanbe, Tajikistan
Topics presented at the Workshop The aim of the Staff Development Workshop enerGIS is to provide participants with an introduction to Geographic Information Systems (GIS) based on energy issues relevant for Central Asia. GIS is able to support decisionmaking processes by assisting the management of renewable energy resources like biomass, hydro, solar or wind energy. Workshop language: English, no translation provided.
Workshop Lecturers (preliminary) Dr. Gilbert Ahamer, ÖAW, Uni Graz / Salzburg Global change, Climate change and energy strategies DI Mag. Rainer Prüller, TU Graz WebGIS, Geodatabases, Land use modelling DI Clemens Strauß, TU Graz GIS technologies, Location Based Services Mag. Gerald Griesebner, Uni Salzburg GPS and GIS lecturer Dr. Gernot Paulus, FH Kärnten Geoinformation, Spatial Decision Support Systems
Workshop Targets • • •
Theoretical and practical introduction to GIS and GPS. Understand the motivation for renewable energy sources. Ability to evaluate concrete energy potentials using GIS (ESRI ArcGIS).
Guidelines for Participation • • • •
Registration on http://www.energis.tugraz.at Sufficient knowledge of English language Interest in basic training on GIS Completion of the mandatory ArcGIS tutorial on http://tinyurl.com/energis2010 and submitting of the received certificate.
Important Deadlines: Participants August 15th August 30th
End of registration period Notification of acceptance
Website
Important Deadlines: Local application studies (15 min.) and lectures (45 min.) Workshop Committee Academician Prof. Dr. Josef Strobl, Director of ÖAW/GIScience, Austria.
Academician Prof. DVSc Izzatullo Sattori, Rector of Tajik Agrarian University named after Shirinsho Shotemur, Tajikistan.
Prof. Dr. Brigitte Winklehner, President of Eurasia-Pacific Uninet.
June
30th
Deadline for extended abstracts (1000 words) Notification of acceptance and review of submitted extended abstract August 15th Deadline for final version of extended abstract (to be published on the website) August 30th Review of presentation slides / completed poster September 10th Handover of final version of presentation slides / poster July 17th
http://energis.tugraz.at Tajik Workshop Partner Dr. Zamira Qodirova Tajik Agrarian University named after Shirinsho Shotemur email:
[email protected]
Austrian Workshop Organization Team Dr. Gilbert Ahamer Austrian Academy of Sciences - GIScience email:
[email protected]
Welcome...! ... from our organisation team: Clemens, Gilbert, Carolina, Rainer ... to our series of enerGIS‘10 presentations Covering the entire range: Î motivation & energy Î GPS measurement Î GPS methods & data analysis Î Map production
Today‘s presentations give the broad context Gilbert Ahamer
> www.oeaw.ac.at/giscience
Climate change requirements are “energetic” and motivate for renewable energy and for GIS Gilbert Ahamer, Dushanbe, 20.9.2010 > www.oeaw.ac.at/giscience
The global logical chain glob al cl imat e ch ange
climate change
energy supply
energy demand renewable potential
„global change“ is mainly „climate change“
Gilbert Ahamer
CO2 stems from fossil fuels
what we need is „energy services“
CO2 free, simple technology
housing sector > www.oeaw.ac.at/giscience
My motto: real science for real people Global Change
science
people
Gilbert Ahamer
Source: Executive Summary, Summary for Policymakers, 4th IPPC Report, www.ipcc.ch
> www.oeaw.ac.at/giscience
Global science and local effects Global warming
The greatest concern in Tajikistan has been an increase in air temperature.
science
Gilbert Ahamer
Source: Executive Summary, Summary for Policymakers, 4th IPPC Report, www.ipcc.ch
people
> www.oeaw.ac.at/giscience
Real people feel real climate change Droughts
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Local people feel global climate change
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Stability of climate and society
> www.oeaw.ac.at/giscience
Gilbert Ahamer
Glaciers accelerate melting
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Extreme weather events
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Results of climate change
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Effects on agriculture
> www.oeaw.ac.at/giscience
Gilbert Ahamer
Electricity generation
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Too little and too much of water
> www.oeaw.ac.at/giscience
Gilbert Ahamer
Resulting action in Tajikistan
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Resulting local action
> www.oeaw.ac.at/giscience
Gilbert Ahamer
What does this mean for us? This is exactly what we do here! See how this fits into our enerGIS‘10 program (and last year‘s openSolarCA‘09) Insulation of houses & energy efficiency Renewable energy sources: hydro, solar Agriculture & land use
All these issues are spatial Î GIS-related Gilbert Ahamer
> www.oeaw.ac.at/giscience
Renewable energy strategies in Central Asia Gilbert Ahamer Planning documents for international and national energy policies are analysed regarding their relevance to protect the global climate. Among other institutions and supra-national conglomerates, the documents of the European Union (EU), the European Union Neighbourhood Policy (ENP) and EuropeAid are doublechecked for their consistency both with national energy programs and practical feasibility. Data from the International Energy Agency are used to draw a picture of energy supply and demand in all five Central Asian States Kyrgyzstan, Tajikistan, Uzbekistan, Kazakhstan and Turkmenistan (see center of map below), focusing on the very diverse “fuel mix”, i.e. the share of coal, oil, gas, nuclear, hydro and other renewables. Intergovernmental organisms such as the Shanghai Cooperation Organisation, CIS, INOGATE, TRACECA, the Baku Initiative, develop energy relevant guidelines. Geographic Information Systems are useful and needed to quantitatively assess regional distributions of (i) energy supply, (ii) energy transport, e.g. by high-voltage lines and (iii) energy consumption. These patterns are not likely to match, hence require a consensus-based network of international policy-making.
Renewable energy strategies in Central Asia
Gilbert Ahamer, Dushanbe, 20.9.2010 > www.oeaw.ac.at/giscience
t expor ricity rt Elect po l im ue il f ss Fo
ca pi ta l kV l i ne s
Lo w
Gilbert Ahamer
es s s Lo
Theft
Ta riff s
ts ke ar m ew N y ienc Effic
Th e en er Sum gy me en rw at e te r fo rp rw inte rise r ga s Interna tional s coope ration Water for irrigation rity ... several Central u se c y Asian states ... g er ... on energy... En
The rmal in sulation Ce nt r a l As ian citiz ens
Let‘s take the perspectives of ...
> www.oeaw.ac.at/giscience
The argument: global climate change
energy supply
Gilbert Ahamer
> www.oeaw.ac.at/giscience
ressource limitation
large investment
decentralisation
local economy
Gilbert Ahamer
> www.oeaw.ac.at/giscience
The local causes for climate change Kazakhstan is among the world’ world’s three dozen largest GHG emitters, and emissions per dollar of GDP produced in Turkmenistan and Uzbekistan are among the world’ world’s highest. Still, none of the Central Asian countries can rely solely on national mitigation efforts to reduce the threats posed by climate change. Source: Tajikistan 2002: State of the Environment Report (http://www.caresd.net/site.html? en=0*id=13), Gilbert Ahamer
> www.oeaw.ac.at/giscience
Perelet, R. (2008), Climate Change in Central Asia, http://www.developmentandtransition.net/index.cfm?module=ActiveWeb&page=WebPage&DocumentID=683.
Energy economics in Central Asia - 1
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Central Asia - 2
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Europe and Asia - 1
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Europe and Asia - 2
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Tajikistan
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Kyrgyzstan
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Kazakhstan
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Uzbekistan
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Energy economics in Turkmenistan
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Correct priorities in energy use! 1.
First reduce energy demand
2.
Then take care of energy efficiency
3.
Last care for sustainable energy
> www.oeaw.ac.at/giscience
Gilbert Ahamer
What means „potential“? What nature offers
What can be built with “reasonable effort” …with “reasonable cost” What is “practically, politically feasible” & “demanded” Îalways, “potentials” are no constant figure but a function of costs: Gilbert Ahamer
Potential = f(cost)
> www.oeaw.ac.at/giscience
Hydro projects map
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Hydro electricity: need for export lines
Gilbert Ahamer
> www.oeaw.ac.at/giscience
Thank you for your attention!
Gilbert Ahamer
> www.oeaw.ac.at/giscience
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
GIS training at Tashkent Institute of Irrigation & Melioration (TIIM)
Tolmas Boltayev Land Tenure Development Center (LTDC), TIIM, Uzbekistan
Dushanbe 2010
BRIEF HISTORY OF TIIM
Established in 1920 and in 1934 by name of Tashkent Institute of Engineers for Irrigation & Agricultural Mechanization
In 2004 the Institute was re-organized into Tashkent Institute of Irrigation & Melioration (TIIM) www.tiim.uz
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
FACULTIES
TIIM
Irrigation & Drainage
Hydraulic Engineering
Automation & Mechanization
Land Management & Cadastre
Economics & Management
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
FACULTY MEMBERS
Figures Doctor of sciences, Professors
33
PhD, Associate Professors
155
Senior lectures
69
Teaching assistants
73
TOTAL
330
WOMEN
115
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
COOPERATION WITH INTERNATIONAL ORGANIZATONS
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
GIS Subjects taught at BSc level Introduction to GIS GIS and Technologies GIS application in Land Management Use of ArcView 3.2
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
GIS Subjects taught at MSc level GIS (Continuation) GIS in Environmental Sciences GIS in Land Management Remote Sensing Use of ArcGIS 9.3
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
RESEARCH CENTERS EcoGIS Center Land Tenure Development Center Information Analytical Center “Water Resources” BioEnergy Laboratory etc.
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
About Land Tenure Development Center
Established Sep.2007 in frame of Tempus funded Project LAREMA Our motto is
“Improving land resources management for socio-economic development and environmental sustainability”
www.ltdc.uz Licensed ESRI ArcGIS 9.3 Software EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Activities of LTDC
Training of highly qualified master students; Training courses in ArcGIS 9.3 for specialists as well as teachers; Support of projects implementation at relevant organizations and governmental agencies; Consultancy; Research;
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Projects of LTDC
Land Resource Management in Uzbekistan (Tempus) Support of Sustainable Livestock Sector in Uzbekistan (UNDP) Issues of Agricultural land use efficiency (USAID) Impact of land reform on salinity (IWMI) Sustainable water resources management in Central Asia (Tempus) GIS and Data Base Management (GTZ) Digital Mapping of WUAs of Ferghana Valley (IWMI)
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Partners of LTDC
EU-Tempus; Eurasia Pacific Network – UNINET (new) International Water Management Institute (IWMI) German Technical Cooperation (GTZ) Royal Institute of Technology (KTH) University of Stuttgart University of Helsinki University of Ljubljana EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Further goals of LTDC
Creation of GIS Center Creation of Data Base by ArcGIS in Uzbekistan GIS education in Engineering fields Development of Teaching materials in practical use of GIS hardware and software Organizing different GIS courses
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Classes of LTDC
EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Thank you for attention!
You are welcome to TIIM!! EnerGIS’10 Staff Development Workshop “Geographic Information Systems (GIS) for Energy Issues
Kyrgyz Republic
Kyrgyz State University of Contraction, Transportation and Architecture GIS spatial Tools: Design and Maintenance Optimization for Energy Efficiency, Passive and Healthy Buildings and Settlements, Adjusted to Daily and Seasonal Effects of the Sun, Wind and Environment
Professor Erkin Boronbaev
[email protected]
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment Central Asia region characteristics: Former Soviet Central Asia countries have transition economy, cold winter and hot summer with the big daily amplitude of the ambient temperature The buildings have low contraction quality, not healthy indoor comfort and 40…60% energy saving and CO2 emission reduction potential Now the poor people expend 30…60% of the family budget for energy use For example in Kyrgyzstan: The buildings consume 41% of a national energy production, the houses take 65…75 % of it It is needed the new knowledge and tools for energy investigation, design and maintenance of buildings and settlements 2
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment Our Department
“Heat-Gas Supply and Ventilation” •
since 1995 has and had the building energy efficiency projects of EC, UN, WB, ADB, EBRD, Denmark, Germany, Norway, Sweden, Switzerland, etc.
•
EC TEMPUS projects completed at 2008
“Development of Master Program in Environmental Protection and Rational Use of Natural Resources at KSUCTA” with KTH (Sweden);
started at 2010 :
1. “Creation of third cycle studies – Doctoral Programme in Renewable Energy and Environmental Technology” with KTH (Sweden);
2. “Geoinformatics: Managing Energy, Resources and Environment” with Salzburg University (Austria) 3
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment Climate of Kyrgyzstan:
Lines of Degree-days (Dd) Heating period: duration – from 133 to 365 days; average temperature – from 1,6 to – 9,4 ºC; Degree-days – from 2100 to 9500; The lowest temperature – minus 56,6 ºC.
4
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment General situation of building sector The energy consumption and CO2 emission structure of the houses in Bishkek city Heating/Cooling
Ventilation Hot water
Cooking
Domestic electricity Transport
Constructed – 2003 Building volume – 314 м3
Constructed – 1990 Building volume – 27000 м3
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment General situation of building sector
157
548
95 189
До
После
До
Project EC TACIS «Improving the Energy Efficiency of Buildings in Kyrgyzstan» (1995-96)
Energy saving – 40%
После
Project CAMP (Switzerland) «Thermal insulation of rural buildings in Kyrgyzstan, Tajikistan, Kazakhstan» Energy saving – 65%6 (2002-04)
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment General situation of building sector t, 0C
Q, кВт*ч
24
b
320
21
280
18
240
15
200
12
160
9
120
6
80
3
40
0
0
-3
-40
-6
-80
-9
-120
-12
-160
-15
-200 1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
February,02
Monitoring shows that there is needed: • Dissemination of knowledge • Improving of building energy efficiency • Managing of energy and natural resources • Use of renewable energy • Decrease of GHG emissions
7
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment General situation of building sector A new demonstration building
Project Basel city (Switzerland) «Straw-Bale passive-solar energy efficiency buildings in Kyrgyzstan» (2004-05) Energy saving – 95% 8
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment PC optimization of the Seasonal Thermal Effects of the Sun: • Summer shadowing • Winter max solar gain
Project Basel city (Switzerland) «Straw-Bale passive-solar energy efficiency buildings in Kyrgyzstan» (2004-05) Energy saving– 95% 9
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment
GIS spatial Tools: The district buildings location optimization on Daily and Seasonal Thermal and Lighting Effects of the Sun
(Video film)
10
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment GIS spatial Tools:
The Settlements location optimization On Daily and Seasonal the Sun shining effects
The shortest in KG the Sun shining duration 1698 h/y measured in Kysyl-Suu canyon (the next open site has 2655 h/y)
In Jety-Oguz resort the daily Sun shining starts very late because of East high hill
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment
Suggestion for a new national level demonstration project:
«Kyrgyzstan: Renewable energy use actions for reduction of buildings energy consumption and GHG emission: Strategy, Trainings, Measures and Monitoring» (2011-2015)
12
GIS spatial Tools: Design/Maintenance Optimization of Energy Efficiency/Passive/Healthy Buildings/Settlements, Adjusted to Daily/Seasonal Effects of the Sun/Wind/Environment
Thank you!
13
Geoinformatics: Managing Energy, Resources, Environment
GEM
Tempus 43 510978-TEMPUS-1-2010-1 Erkin Boronbaev Ainura Nazarkulova Josef Strobl
Topics Содержание Objectives Цели y Partners (18) Партнеры y Work Plan and Outcomes Рабочий план и Результаты y Success Factors Параметры успеха
GEM
y
Key Facts Основные факты y y
GEM
y
y
Starting in October 2010 (likely), 3 years Начало октябрь 2010, 3 года 18 Partners from EU and CA 18 партнеров из ЕС и ЦА Budget approx. € 900.000 (10% cofinancing) Бюджет ≈ 900000 евро (10% ‐ софинансирование) Development of int‘l MSc programs Разработка М/ународной магистрской программы
Coordinating Institution Координирующая организация y
GEM
y y y y
Centre for Geoinformatics, U of Salzburg Центр Геоинформатики, Университет Зальцбурга Experience with Tempus, Erasmus etc. Работал с Tempus, Erasmus и др. Central Asia activities since 2002 Работает в ЦА с 2002 г. 40 Researchers, expertise in GI+app‘s 40 Научных работников CA facilitator partner: KSUCTA Основной партнер в ЦА: КГУСТА
GEM
Objective Цели y
The main objective of the project is to develop and implement an international, interdisciplinary postgraduate curriculum in Geoinformatics, with a clear focus on the management of critical resources. In particular, important pillars of the success of emerging economies in the Central Asia region will be addressed. The program will focus on the contents, teaching methods, academic integrity and a collaborative form of delivery as well as laying the foundation for lifelong learning in accordance with the Bologna Declaration.
y
Основная цель проекта – разработать и реализовать международную, междисциплинарнуюй учебную программу на базе в.о.по Геоинформатике, сфокусированную на управление необходимыми и важными ресурсами. Программа будет нацелена на содержании, методике преподавания, академической целостности и совместной форме преподавания, а также на создании основы для длительного обучения согласно Болонской декларации.
Project Objectives Цели проекта y
GEM
y
y
y
Focus / Action: Curricular Reform Фокус / Деятельность: Реформа учебного плана Geoinformatics MSc at all Acad. Partners Магистратура по геоинформатике для всех академических партнеров Sustaining Program beyond Project (!!) Устойчивость программы после завершения поекты Contribute to Knowledge-Based Societies Вклад в общество основанное на знании
Why (Applied) Geoinformatics? Почему Геоинформатика? y
GEM
y
y
y
Sustainability always is ‚spatial‘ Устойчивость всегда связана с простанством Integrates information across domains Интегрирует информацию с разных областей Key for managing economiсs and societies Ключевое для управления экономикой и обществом GI is key competence, needed locally!!! ГИ – это основные знания необходимые на местах
CA Partners – Academic Академические партнеры в ЦА 1. 2.
GEM
3. 4. 5. 6. 7.
Kyrgyz State University for Construction, Architecture and Transportation (КГУСТА) Osh Technological University (ОшТУ) University of Central Asia (УЦА) Kazakh National University - Al-Faraby Korkyt Ata Kyzylorda State University Tajik Agrarian University (ТАУ) Tajik State Pedagogical University (ТГПУ)
CA Partners – Admin and Industry ЦА Партнеры ‐ Неакадемические Ministry of Education and Science – KG y Ministry of Education and Science – KZ y Ministry of Education – TJ y Osh Enterprise of High Voltage Station y Osh Engine Generating Station y Ministry of Industry, Power and Fuel Resources – KG y State enterprise Kyrgyzgilkommunsoyus
GEM
y
EU Partners Партнеры из ЕС University of Salzburg Centre for Geoinformatics y Vrije Universiteit Amsterdam Spatial Information Laboratory y University of West Hungary Faculty of Geoinformatics y European Geography Association for Students and Young Geographers
GEM
y
GEM
Work Packages Рабочие блоки 1.
Review of programs, demand, potentials Обзор програм, спроса, понтенциалов
2.
Establish curriculum, learning media Определение учебного плана, обучающего медиа
3.
Faculty development Повышение квалификации преподавателей
4.
Program implementation (Course start) Реализация програмы (Начало курса)
5.
Dissemination and outreach Распространение и информирование
6.
Sustainability: business model and market Устойчивость: бизнес модель и рынок
7.
QC: monitoring and academic integrity Контроль качества: мониторинг и академическая целостность
8.
Project Management Управление проектом
Main Activites Основная деятельность y y
GEM
y
y y
Curriculum and media development Разработка учебного плана и медиа Teacher training, starting courses Обучение преаподавателей, начала курса Integrated int‘l program, parts as eLearning Интегрированные международные программы, часть как eLearning Workshops and summer schools Семинары и летние школы Quality Assurance Гарантия качества
Innovative Learning + Pedagogy Инновационное обучение + педагогика Integrated courses across institutions (sharing teaching resources!) Совместные курсы y eLearning components eLearning компоненты y Active learning, collaborative learning Активное обучение, совместное обучение y Competence-based assessment
GEM
y
Success Factors Факторы успеха Full committment by partners! Выполнение обязательств партнерами y Realistic expectations: students, Реалистические ожидания: студенты y Faculty – teachers Штат ‐ преподаватели y Quality – academic integrity Качество – академическая целостность y Development of job market Развитие рынка труда
GEM
y
A Few Key Points … Summary Несколько основных пунктов ... y y
GEM
y
y
Identify ‚right‘ students Определение нужных студентов E-Learning to share teaching resources E-Learning ‐ обмен материалами обучения Building communities of stakeholders Создание сообщества заинтересованных лиц Outreach to broader public Информирование широкой общественности
Links and References http://eacea.ec.europa.eu/tempus y www.zgis.at y www.ksucta.kg y www.zgis.net/GEM (soon online)
GEM
y
Contacts: y
[email protected] y
[email protected]
GPS Measurement Problem definition: Practical session with GPS tools (Trimble Juno ST). Requested results: • • • •
Getting familiar with the usage of a GPS system Collecting point features in the surrounding of the university Process the collected data in the computer lab Short technical report with a workflow description
Assistance:
Getting familiar with a GPS system • •
• • • •
Switch on the device (Trimble Juno ST) Start the GPS software: Start – Programs - TerraSync
Check the different possibilities of the status of the GPS Receiver (Rover) 1. Pull-down menu: Status 2. Pull-down menu: Sky Plot Check other possibilities (like: Sat Info….) + different other parameters like PDOP, position, amount of satellites, accuracy……
Collecting point features in the surrounding of the university •
1. Pull-down menu: - Data - Create - height of antenna - Point, line or area (depending on which type of feature you are interested in)
• • • • • • •
Create = Start to measurement feature 1 Ok = Stop measurement feature 1 (but leave the file open) Create = Start measurement feature 2 Ok = Stop measurement feature 2 Close Close file and save it Close “Terrasync” Check files in the “File Explorer” Start – Programs – File Explorer Path: My Device / My Documents / TerraSync
Process the collected data in the computer lab (Data Transfer, Export…) • •
•
Connect the GPS device w via USB with the computer. The software “ActiveSync” should start automatically
Start the software “Pathfinder Office Pro”
•
Generate new project in “Pathfinder Office Pro” by using the button New
•
Type a name for this project and confirm it with OK
•
A new project was generated (! Keep the path for the project in mind !)
•
Transfer the collected data from the GPS device to the computer Utility – Data Transfer
•
Check if the GPS device is connected (upper right corner) Add “Data File” to the “Data Transfer” window Add – Data File
•
•
Select the file you have collected in the field Open
•
Transfer the selected file(s) Transfer All
•
Export the file(s) to a different file format (for example ESRI – shape format Utilities - Export
•
Check the properties for exporting the file(s) - Projection (like WGS84) - Attribudes (like height, GPS time and date… - Filters (like Uncorrect….) (! Keep the projection you will use in mind !)
• •
There will be a message that no projection has been found. Confirm with Yes You will get a short report about the export of the file(s) Confirm with Close
•
Define the projection with the software ESRI ArcCatalog
•
Start the software ArcCatalog
•
Navigate to the “Export” folder in your GPS project
•
Right click your exported files and click Properties
•
Select the same projection you used in the “Export” window in Pathfinder Office Pro (like WGS 84)
•
Confirm the the right projection with OK
•
Check the result with the Preview window
Technical report: Description of workflow to measure some features with GPS and to bring the results in a different data format (with some screenshots of the main tasks).
ИСПОЛЬЗОВАНИЕ НЕТРАДИЦИОННЫХ ИСТОЧНИКОВ ЭНЕРГИИ
Многофункционалная лабораторная биогазовая установка работающем на разрежение (Установка на 500 литров биомасс температурный режим которой 520с)
Биопруды для очистки канализационных отходов
Стратегические направления развитие энергетики в мире предусматривают широкое использование нетрадиционных источников – ветера, ветера, солнечные, солнечные, незкотемпературных источников энергии , в том числе и энергии органической биомассы (навоз, навоз, ботва, ботва, выжимки, выжимки, отходы полеводства и др.). др.).
Биогазовая завод на 100 м3 работающим птичьем помете в г. Чирчике Ташкентском области
Получение биогаза из высших растение из очистительных биопрудов
Биогазовые установки работающих (чистым свином навозе) навозе) неправильном режиме
Верхняя растение для очистки загрязнение
Биореактор на 50 м3 работающим в режиме разрежение чистого свиного навоза
Проблема обработки свиного навоза (басен
Wind Energy Creation of Wind Maps Modeling the location Data from Remote Sensing Existing Analogue Data Spatial Analysis of the Wind Maps for determination of correct location of the Wind Power plants
Спасибо за внимание!!!
Metodological approach to applicatcation of GIS & DSS for the management of water resources of the transboundary rivers Sobir Navruzov The questions of creation of GIS system for decision-making related to management of water resources in transboundary river basins are considered in this paper. Process of application of GIStechnology is described in the field of management of water-economic systems in general, and water resources managements of the Central Asia transboundary rivers, in particular. Various aspects of GIS application are analyzed: GIS database management, basic software, establishing the relationship of GIS and database; specific features of GIS mapping. The description of GIS software which contains functions and the tools necessary for storage, analysis and visualization of the geographical (spatial) information are resulted. Developed classifications of technologies by the formation of thematic layers are described based on the existing geographical basis. The technique of choice for GIS map projection is offered and also the structure of the GIS database as an example of Amudarya and Syrdarya transboundary river basins is developed. The method of applying coatings using the software Arc / View [1] developed a variety of maps, which are using for spatial data analysis. Maps of the level of soil salinity and irrigation area in selected areas of planning zones prepared on the basis of this method are examples of such constructions. The conceptual scheme the interaction of the main components of decision support system (DSS) is offered (see picture 1). Database management system (DBMS) is based on the methodology of databases (DB) construction. Effective use of accumulated data files of various departments (and the amount is typically a few thousand units of storage) is possible only with active involvement in the processing technology computers and the creation of special software. This interface system provides the user the opportunity to work in interactive mode with the database to search for acceptable solutions to the problems with the use of mathematical models [2,3]. The mathematical models of water management of transboundary basin as a natural object, surface runoff mainly governed by accumulating reservoirs are considered. Three levels of mathematical models are offered: analytical, optimization and imitational. Within the framework of analytical models [4], the theoretical game models for the distribution of water resources between the states of the Amudarya basin are considered. A number of characteristic examples of games with non-opposite interests are discussed.
DSS GIS
Interface
XII
1992
XI
1400
1200 X 1200
IX 1000 VIII 1000
1991
NST NST
1991 1992 1991 1993 1993
PFA PFA
200
Блок ввода информации из модели зоны планирования
DBMS
III II
I
II II
200 III III
IV
IV
400 V
600 V
VI
VII VI
800 VIII VII
IXVIII
1000 X IX XI
1200 XXII
1991
0 I
Field
WCL WCL
XI
WDR WDR
1400
База данных
XII
Instrumental System
Блок расчета ущербов Аралу и Арнасаю
WTD WTD
Industr Industryy
Блок водносолевого баланса
Блок формирования целевой функции
WGZ WGZ
Graund Graund W Water ater
Graund W ater
Блок гидроэнергетики
Блок расчетной информации для пользователя Drain
WDL WDL
Lake
WIR WIR
WTR WTR
WDT WDT
Drain Drain
Расчетные блоки Lake Lake
WGR WGR
Блок ввода информации из базы данных
I 0
WCR WCR
Поль з ова тель
Структурный блок Suppl Supplyy
WRI WRI
Supply
IV
400
WFA WFA
Field Field
Блок расчетной информации для модели зоны планирования
Canal
Информация
600
200
PAF PAF
Результаты
VI
400
WAF WAF
Canal Canal
WRS WRS
600 V
0
WCA WCA
WTS WTS
VRS VRS
Модель Бассейна Реки
VII 800 800
WCT WCT
NTS NTS
Модель Зоны Планирования
Управлени е Блоки выбора целевой функции, ограничений и начальных условий Industr y
WGT WGT
WDA WDA
WIL WIL
Filtration Filtration Field Field
Filtration Field
Mathematical Models
Pic. 1.
Optimization models [3] of the reservoir management of the upstream water resources of the Amudarya are offered, which use as a base the “block-hierarchical” principle [5], which at the initial stage provides for the development of different national models and their further coordination within the framework of regional models. According to this, we can divide the territory of the Amudarya basin into two zones: the zone of water demand and the zone of water production. The technique of finding a compromise solution among the needs of the states, in terms of the volumes of water consumed at the level of the coordination of management between zones of consumption and formation is offered. Construction of imitational models is carried out on example the Vakhsh–Amudarya cascade of reservoirs [2,5]. The cascade includes three large reservoirs, such as Rogun, Nurek and Tuymuyn. Mean while, these reservoirs are located in the territory of different Central-Asian republics, namely: Rogun and Nurek belong to Tajikistan and Tuymuyn to Uzbekistan. Using mathematical models and computer technologies provide improved reservoir management rules with a uniform approach to their preparation of specific water bodies located in both national and transboundary basins [6,7]. The developed mathematical models the general principles and approaches to water resources management of the transboundary rivers also have been approved for the Syrdarya basin. Relations of countries between zones of consumption and formation proposed procedure for finding a negotiated solution on the distribution of water resources: Kazakhstan and Uzbekistan (zone of consumption), receiving necessary extra water for the vegetative period at the same time accept also generated electricity by Kyrgyzstan and Tajikistan (zone of formation). During the winter (deficit
period) Kazakhstan and Uzbekistan return to the zone of formation generate electricity or an equivalent amount of other energy sources. The structure of the main menu of user (see pic. 2) is based on a block-hierarchical principle, where the user can choose one or another menu item is arbitrary, or based on strictly ordered logic view information. For example, selecting a block of background information, the user is satisfied with the information on the simulated object - Syrdarya transboundary river.
COMPUTER MODELING
Ka zak hst an
Tu rkm eni sta n
Central Asia River Basin
Uz bek ista n
01 Version, 2009
HELP HELP INFORMATION INFORMATION
Kyrgyzstan
PARAMETERS PARAMETERS
Ta jik ista n
SCHEMES SCHEMES (linear and survey) (linear and survey)
MODEL MODEL DESCRIPTION DESCRIPTION
WATER WATER BALANCE BALANCE
SCRIPTS
QUALITY QUALITY BALANCE BALANCE
REPORTS
GIS GIS (SPATIAL (SPATIALANALYSIS ANALYSIS) )
GRAPHIC GRAPHIC ANALYSIS ANALYSIS MENU
Pic. 2
With regard to the direct participation of the user in the process of scripting, it is part of the block "Inputs". This unit was granted by the opportunity to view a demo, or the most directly modify the input data for various objects. A similar structural arrangement is implemented for all blocks of the system (see pic. 3-7). Develop a scenario of using of water is an important component for making decisions on assessment of water balance in the basin of Syrdarya transboundary river. The interests of the forming zone countries centered on the energy use of water resources, while countries of the zone of consumption of using water basin meets the demands of irrigated agriculture. In these circumstances, there is a conflict of interest. In this regard, the main task is to find suitable options cooperation on water resources under review the basin, which contribute to reducing tensions in the region. To do this, in principle, it is proposed computer simulation of possible scenarios of water use in which users of the system will be able to simulate different situations of water distribution among water users and water users, as well as to determine the balance of water in selected areas of the transboundry river basin.
Gathering and processing of the monthly data
INPUT THE KEY PARAMETERS Parameters of water basins: • Volume, one million in m3 (full and useful) • Height, m ; • The area км3 • Length, km
Inflow: • to Toktogul (V1); • to Andijan; (V2); • to Kayrakum (V3);
• between Toktogul & st. Uchteppa • between st. Uchteppa & Kayrakum -
( ω , ω ); T 2
ω5K ,..., ω9K
• up & lower Kayrakum (
V5K
Other parameters: • Evaporation; • Minimal outflow; • etc.
A A • Below Toktogul ( ω3 , ω4 );
• Below Andijan
V2T V4A
• between Andijan & st. Uchteppa -
Irrigational requirements :
Input of parameters are carried out :
);
- Users
The aggregated irrigational requirements the countries of the bottom current (Uzbekistan + Kazahstan)
Akdjar
Hydropost:
Year
I
II
III
IV
V
1987
280,00
343,00
329,00
470,00
397,00
494,00
Chilmahram Акджар Akdjar Cal VII VIII IX X Uchkurgan 707,00 327,00 293,00 502,00 Uchteppa
712,00
657,00
1988
586,00
599,00
499,00
665,00
1027,2
936,60
954,62
678,32
620,33
545,30
597,77
579,91
1989
596,44
590,33
479,03
338,43
579,37
801,67
938,41
754,13
360,77
408,72
558,47
556,46
1990
492,57
524,31
423,23
401,53
446,81
336,87
604,42
634,13
340,03
483,87
646,63
599,76
1991
593,50
555,73
467,40
425,43
624,77
708,90
688,67
437,42
284,43
428,28
563,93
673,07
1992
583,13
574,81
530,93
461,60
771,50
560,97
472,23
459,55
309,10
511,19
638,27
711,80
1993
650,88
690,23
637,71
477,57
822,33
751,73
402,58
348,18
299,23
521,78
779,63
900,40
1994
655,90
898,13
907,73
813,07
892,42
503,93
511,81
350,62
543,88
502,09
752,13
952,02
1995
927,38
896,61
755,06
449,37
303,75
247,23
501,14
305,48
214,40
371,02
580,70
867,89
1996
859,28
846,41
722,57
614,35
429,96
645,47
398,77
327,58
260,33
482,77
785,13
960,33
1997
874,08
788,85
640,52
502,67
310,15
405,70
406,79
339,68
196,90
252,71
607,67
815,53
1998
826,33
857,84
714,54
464,74
611,06
930,70
474,66
342,27
433,25
469,61
617,90
953,00
Lateral Inflow:
HYDROELECTRIC POWER STATION: • The established capacities; • Factors energy generation; • Other restrictions;
T 1
The monthly data on objects gather in tables:
VI
XI
XII
or
The similar table of the monthly data is entered by the user on all to characteristic objects of the Syrdarya basin
- Selected
Pic. 3
Pic. 4 INTAKES Graphic illustrations (in a cut of month)
The survey scheme of an operative range of territorial managements in Syrdarya basin
Main intake of Golodnostepsko canal, April 1998.
Q, м3/сек Syrdarya
Toktogul
Uzbekistan
Kyrgyzstan
Kalles
200
Parke nt
ca na l
Uzbekistan Чардаринское
Ch rd Sy
BFK
150
Karadarya
100
K UG
Ta ji
kis
ta n
ik stl Du
Arnasay reservoir
Andijan Kayrakkum
a ary
Uzbekistan
LN K
hik irc ry n
Kis ilk um
250
Charvak
Kazakhstan
Na
Aral sea
50 Symbols:
Golodnostep territorial management Boundary of states Naryn-Karadarya territorial management
Canals
Verhnochirchik territorial management
Hydrounit
Management of Toktogul reservoir
Pamp station
Management of Charvak reservoir
Hydrostation
Pic. 5
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
t, сут
Pic. 6
Construction of such scenarios is the most important link to the creation of effective water balance model of the Syrdarya. Some formulated scenarios are presented below and its discussion should take place between the stakeholders involved in the process of water allocation of transboundry rivers. To assess the level of supply and demand of country of the consumption zone of water for irrigation purposes please explain or cite the algorithm who this was computed, provided that the Toktogul reservoir will be working in the energy mode discharges water; To assess the role of Andijan and Kayrakum reservoirs while meeting the requirements of country of the zone of consumption to cover the deficit of water in the growing season; Determine the water balance for selected reservoirs and watershed areas of transboundry rivers; Evaluate the volume of return water to the selected sites.
THE GRAPHIC ANALYSIS Having chosen object or some objects and the time period it is possible to overlook and analyze dynamics of parameters on time (schedules and the tabulated data): Kayrakkum
Dynamics of filling (realize) water reservoir:
Year
Show
Update Update
1990 1991 1992
1993 1994 1995 1996 1997
млн.м3 2500
2000
Data Data
1500
1993 1994 1995 1996 1997 1998 Year
Andijan Kayrakkum Toktogul Charvak
1000
500
0 I
II
III
IV
1993
I 1443 1389 1342 1132 1145
II 1447 1067 1315 1128 1072
III 1270 723 1079 1142 1008
IV 1251 716 1117 1598 1330
V 1613 1217 1597 1887 1838
VI 1857 1915 1811 1979 1997
V
VI
1994
VII 1969 1941 1569 2002 1822
VII
VIII
1995
VIII 1714 1737 1659 1609 1434
IX
X
1996
IX 1553 1661 1247 1619 1297
X 1708 1657 1219 1414 995
XI
XII
Месяцы
1997
XI 1574 1531 1176 1248 941
XII 2429 1993 2042 2335 1503
Pic. 7 In what sense can such figures help the decision makers to really! Understand the situation much better. Is this more than showing date? What is the essence of the model? What does it compute?
Block of “Instrumentation System” used to search for errors of input variables, as well as the restoration of missing data using analog series of observations or graphic information. Block "GIS" is designed to effectively address the problems associated with the spatial nature of information, and provides delivery information to the user in the most convenient form (maps, charts, tables, etc.). As an example we consider the basin area, which include of Kayrakum reservoir (Tajikistan). Built block of dynamics of water availability of Kayrakum reservoir maybe it is interesting to know how much power is produced and how many % of the total Tajik electricity production this is in which the user is offered a demo version of the regulation of the reservoir or choose options for scenarios. The user can modify the original data. Then based on inputting parameters and the selected scenario is calculated water balance with the actual water releases from reservoirs for irrigation purposes and for purposes of hydropower. In the structure of methodology of decision problem of multi-purpose management of water resources the original approach proposed to solution complex problem of planning and using water resources of the transboundary basin. The first aspect approach related to spatial division territory of considering basin on levels of management. The second determined by multi-purpose problems related with identifying appropriate compromise solutions between states on using water resources
by taking into consideration of economic interests. Combination of multilevel and multidisciplinary goals represents the key moment of methodology offered approach. The specialized applied program of DSS uses of program software MS Office operation system Windows XP & GIS Arc Info/Arc View. Information database is constructed based on MS Access and mathematical models are used for finding of optimal solution. Analysis and representation of spatial data is carried out based on GIS technology. References 1. Arc View GIS. Manual. - M.: Izdatel'stvo Date +. - 368 pp. 2. NAVRUZOV S.T. (1986) Calculation of management rules for a reservoirs cascade of the irrigation-power purpose. Moscow ,Computer Center of the USSR Academy of Sciences. . 3. NAVRUZOV S.T. (1990) On a method of constructing a zone guaranteed return for a linear cascade of reservoirs.Dushanbe, Report of Tajik Academy of Sciences, vol.33, no. 3.. 4. NAVRUZOV S.T. (1991) Qualitative research of a problem of optimum control to a cascade of reservoirs.Dushanbe, Izvestiya of Tajik Academy of Sciences, no. 3 (117).. 5. NAVRUZOV S.T. (2007) Optimization model of management of water and energy resources of transboundary river basin. Dushanbe, Bulletin of the Institute of economy of Tajikistan № 1.,, pp. 82-85. 6. USMANOV Z.D., NAVRUZOV S.T. (2008) Scenario water allocation in the model of transboundary river basin.Dushanbe, Reports of the Academy of Sciences of the Republic of Tajikistan, Vol.51, № 7. , pp.496-500. 7. NAVRUZOV S.T., SHOMURODOV Z.B. (2009) Creating a decision support system in transboundary river basins based on GIS technologies / / Third International Scientific Conference of young scientists and talented students "Water, Ecology and Hydrology security", Proceedings. Moscow, Organized by the Institute of Water Problem of the Russian Academy of Sciences, 16-18 December, pp. 13-15.
FME introduction course What is spatial ETL? How does FME work?
What is ETL? To overcome challenges and capitalize on the value of spatial data, organizations require the ability to: • Efficiently extract spatial data from a desired datastore • Transform it into the requested format and data model • Load it into a target system and present it to end users
ETL, FME concept
Source data
Extract, Transform and Load
Destination data
FME, Workflow
Transformers Source
Destination
Primary FME Components y FME Workbench (FME Workbench offers powerful
transformation and translation capabilities traditionally reserved for custom software solutions) y FME Universal Viewer (Inspect both attributes and geometry, and even check multiple sources in multiple formats) y FME Universal Translator (This is the fastest way to perform translations, simply by dragging and dropping files, and using the supplied defaults.)
FME Universal Viewer 1 2 4
3 5
6
7
8
FME Universal Viewer 1. 2. 3. 4. 5. 6. 7. 8.
Menu bar Toolbar Display control window Tab window View window Information window Log window Status bar
FME Universal Translator 1. Format of input data 2. Dataset of input data 3. Format of output data 4. Dataset of output data 5. Coordinate system of
output data
1 2
3 4 5
FME Workbench
FME Universal Viewer Format of input data Dataset of input data Coordinate system
FME Universal Viewer
FME Universal Viewer Filtering features
FME Universal Viewer Adding another format
FME Universal Viewer
We can see two different formats in one window and we can save this in another format
FME Universal Translator From Geography Markup Language (GML) format we get ESRI Shape format,and if you want change the projection than we need to change coordinate system.
FME Workbench Creating a workspace
FME Workbench
FME Workbench Adding 2DPointReplacer Transformer allow us to create geometrical objects from text file.
FME Workbench
Now we have points and we can see them with the help of Universal viewer
FME Workbench To connect points we use PointConnector Transformer.
FME Workbench Now we see that this is roads, but we don`t know the types of roads but we have attribute features in database and we adding them with Joiner transformer
FME Workbench
FME Workbench
FME Workbench
FME Workbench With the help of AttributeFilter transformer we can classify roads by attribute features
FME Workbench
If we connect Visualizer to MAJOR we will get such result
Carinthia University of Applied Sciences Austria
Theory on GIS & GPS Selected Aspects Dr. Gernot Paulus School of Geoinformation, Carinthia University of Applied Sciences, Villach, Austria.
Content Introduction Definitions
Representations – Data Models Raster Vector
Georeferencing Overview about methods for Georeferencing
Geodata Modelling Lab Exercise ArcGIS Introduction to GPS 2
1. Introduction
Geographical Information Systems and Science Longley P A, Goodchild M F, Maguire D J, Rhind D W (2001) John Wiley and Sons Ltd © John Wiley & Sons Ltd
3
Geoinformation is everywhere ! More than 80 % of all business data used world wide can be seen in a spatial context, e.g. customer adresses, post codes, or locations of industry. 4
Geospatial technology is one of the three most important emerging and evolving job fields, along with nanotechnology and biotechnology! Reference: US Department of Labour; Nature, Volume 427, January 22, 2004. 5
Motivation Application Examples: Road Planning River Basin Management Traffic Flow Optimization International Terrorism – 9/11 Flooding in Europe during summer 2002 Tsunami in Asia in December 2004 Forest fires in Portugal during Summer 2005: more than 170.000 ha forest destroyed, Greece 2007 Hurricanes: „Katrina“, „Rita“, “Ike”,….. Bird Flu
Fast, up to date and accurate analysis and visualization of the spatial situation is crucial for experts and decision makers. 6
Why GIS Matters – Technology for problem solving Almost everything happens somewhere Knowing where some things happen is critically important UN: Position of country boundaries Health Care Management: Location of hospitals Delivery Conmpanies: Routing delivery vehicles Forest company: Management of forest stands Government: Allocation of funds for sea defenses Tourists: Find sights, best route Farmers: bring out fertilizers National park: path maintainance ……. 7
Geographic Information System Organized collection of Hardware Software Network Data People Procedures
Software People Data Network
Procedures Hardware 11
Geographic Information System Technical Definition: Systems for input, storage, manipulation, analysis and visualization of geographic information a combination of software, hardware, data, a user, etc., to solve a problem, support a decision, help to plan 12
GIScience is Multidisciplinary (1) Geographic information technologies cartography, geodesy, surveying, remote sensing, photogrammetry, image processing
Digital technology and information in general computer science (databases, computational geometry, image processing, pattern recognition), information science
that have studied the Earth, particularly its surface and near-surface, in either physical or human aspect geology, geophysics, oceanography, agriculture, biology, environmental science, geography, sociology, political science, anthropology, ... 18
GIScience is Multidisciplinary (2) disciplines that have traditionally studied the nature of human understanding, and its interactions with machines psychology, particularly cognitive psychology, environmental psychology cognitive science, semantics artificial intelligence
19
2. Representing Geography
© John Wiley & Sons Ltd
21
Ancient and historic Representations Hand- drawn maps and speech Hunting and gathering information
Papyrus & paper as first communication media Printing Press - 15th century Knowledge distribution
Age of discovery in early 15th century as important period of geographic representation – maps media for sharing information about discoveries and administrating new colonies. 22
GIS Data Model The aim of a GIS data model is to provide a practical template for implementing GIS projects Constructing data models for GIS applications is the crucial first step of GIS projects. Already some Data Model evailable, e.g. developed by ESRI: ArcHydro, ArcMarine, Atmospheric
Role of Data Modeling Feature Feature
GIS Data Model Description and Representation
Line Line
Polygon Polygon
Building Building
Pump PumpHouse House
Street Street
Water Water Line Line
Operational GIS Analysis and Presentation
House House
People Interpretation and Explanation
Real World
Data Model Levels ANSI/SPARC Scheme (American National Standards Institute/Standards Planning and Requirement Comittee)
Humanoriented
External External Model/Reality Model/Reality Conceptual Conceptual Model Model Logical Logical Model Model
Computeroriented
Physical Physical Model Model
Increasing Abstraction
Modeling Process
Conceptual Model Lists, flow diagrams, etc
External Model Real World Objects and relationships
Logical Model Tables & Diagram in CASE Tool
Physical Model Database Schema (Object state)
CASE: Computer Aided Software Engineering
ANSI/SPARC – External Model 5 different views on the same part of the real world...
Remote Sensing specialist analyses spectral reflexion patterns of a quadratic part pof the earth surface..
Geologist is interested in subsurface rock formations and processes, tectonic structures. Suryeor defines exact boundaries of parcels.
Farmer has a lot of local experience and knowledge about his property.
Ecologist is interested in ecosystems, species distribution patterns, interaction 28 .... Different views can not directly be observed!
ANSI/SPARC – External Model Strategies for capture of focused, user-centered description of real world Expert interviews, literature research
Who will be the main GIS- user of your project, application – categorization - stakeholders? - User - Expert user with high analytical needs - Decision Maker Define project focus, scope – objectives – expected results? - selected user groups - client - involved departments Detailed requirement analysis (Object Catalog): - spatial objects, data types (geometry, attributes) - special analysis functions? - Evaluation of data sources, data formats, corrdinate systems 29 - spatial reference systems of the project?
ANSI/SPARC – Conceptual model E-R Diagram Forest Management (Spatial Data types)
Specific ESRI Data Model examples http://support.esri.com/index.cfm?fa=downloads.dataModels.gateway
Agriculture , Atmospheric , Basemap, Biodiversity, Building Interior Space , Carbon Footprint , CensusAdministrative Boundaries, Defense-Intel , Energy Utilities , Energy Utilities - MultiSpeak TM, Environmental Regulated Facilities , Fire Service, Forestry , Geology , GIS for the Nation, Groundwater , Health , Historic Preservation and Archaeology , Homeland Security , Hydro, International Hydrographic Organization (IHO) S57 for ENC , Land Parcels , Local Government , Marine, National Cadastre , Petroleum , Pipeline , Raster , Telecommunications , Transportation , Water Utilities
Example ArcHydro http://support.esri.com/index.cfm?fa=downloads.dataModels.gateway
The Fundamental Problem Geographic information links a place (geometry), and often a time, with some property (attributes) of that place (and time) “The temperature at 34 N, 120 W at noon local time on 12/2/99 was 18 Celsius”
The potential number of properties is vast In GIS we term them attributes Attributes can be physical, social, economic, demographic, environmental, etc.
GIS: GEOMETRY + ATTRIBUTES + TIME 36
5 Types of Attributes Nominal, e.g. land cover class, colour -
Classify
Ordinal, e.g. a ranking of soil quality - Order Interval, e.g. Celsius temperature - Measure Differences make sense
Ratio, e.g. Weight, distance, Kelvin temperature - Measure Ratios make sense
Cyclic, e.g. wind direction in – Measure 360° scale
37
Cyclic Attributes Do not behave as other attributes What is the average of two compass bearings, e.g. 350 and 10?
Occur commonly in GIS Wind direction Slope aspect Flow direction
Special methods are needed to handle and analyze
39
Discrete Objects and Fields – 2 conceptualized views of the real world Two ways of categorizing geographic variation Discrete objects Objects with well-defined boundaries in empty space Points (fire hydrants), lines (roads), areas (zones) Use vector representations in GIS
Fields Properties that vary continuously over space Elevation, Temperature, Air pressure Use raster representations in GIS 40
Field vs Discrete Object Representation FIELD: Objects of real world as continuous gray scale variation – Satellite Image
DISCRETE OBJECT: Objects of real world as geometrically distinct polygon objects 41
Discrete Object View World is empty except where it is occupied by objects. Points, lines, and areas – dimensionality Points (0-dim); lines (1-dim.), polygons (2-dim)
Countable Persistent through time, perhaps mobile Biological organisms Animals, trees, persons, cars
Human-made objects Vehicles, houses, fire hydrants,….
42
Continuous Field View World described by variables measurable at any point on the earth‘s surface. Variables (properties, attributes) that vary continuously over space Value is a function of location Property can be of any attribute type, including direction
Elevation as the archetype A single value at every point on the Earth’s surface The source of metaphor and language • Any field can have slope, gradient, peaks, pits
43
Examples of Fields Soil properties, e.g. pH, soil moisture Population density But at fine enough scale the concept breaks down
Identity of land owner A single value of a nominal property at any point
Name of county or state or nation Atmospheric temperature, pressure
44
Phenomena conceptualized as fields. The illustration shows elevation data from the Shuttle Radar Topography Mission draped with an image from the Landsat satellite, looking SE along the San Andreas Fault in Southern California, plus a simulated sky
Difficult Cases – Which to choose? Lakes and other natural phenomena Often conceived as objects, but difficult to define or count precisely Boundary Problem! Task: Count the number of lakes in Louisiana?
Weather forecasting Forecasts originate in models of fields, but are presented in terms of discrete objects • Highs, lows, fronts 46
Rasters and Vectors – 2 methods of representing spatial data in digital computers spatial entity location
attributes
basic geographical data primitives
Vector
Raster
47
Raster Data – “Top Down approach” Divide the world into square cells Register the corner (Center of upper left pixel) to the Earth Represent discrete objects as collections of one or more cells Represent fields by assigning attribute values to cells More commonly used to represent fields than discrete objects
(x,y)
Each color represents a different value of a nominal-scale field denoting land cover class.
48
Electromagnetic spectrum
49
50
Raster and Vector Models
Raster Structure and Metadata Array of cells (pixels) Stored as compressed file
1 attribute value per pixel (categories, integer, floating point numbers), assignment scheme Metadata (header file) Coordinate values of center of upper left pixel (location on earth surface) Pixel size (resolution) Number of rows and columns (dimension) Projection
(x,y)
N columns
N rows
pixel size (e.g. 5m)
Characteristics of Rasters Pixel size The size of the cell or picture element, defining the level of spatial detail All variation within pixels is lost
Assignment scheme Real world objects, measurements and observations are mapped on a pixel – „Averaging effect“ „“Mixed pixel problem“ • The value of a cell may be an average over the cell, or a total within the cell, or the commonest value in the cell • It may also be the value found at the cell’s central point • Important issue in remote sensing – e.g. urban environment with a lot of variation and heterogeneous spectral values 53
The mixed pixel problem
W ater dominate s
W inner takes a ll
E dges s epa rat e
W W
G
W G
G
W
E
G
W W
G
W W
G
W
E
G
W W
G
W G
G
E
E
G
(Zaslovsky, 2004)
The mixed pixel problem
Largest Share Rule
Center Point Rule
Vector Data – “Bottom up approach” Used to represent points, lines, and areas All are represented using coordinates defined by a coordinate system. set (xi,yi) (A1,A2,…An)
set (xi,yi) (A1,A2,…An) y
A1, A2,…An
y
y
(xi, yi)
x
x
x
56
Vector – Simple Geometry types
Point
Line
Polygon
Volume
Each vector geometry is a unique Object-ID assigned Used as „Primary Key“ and „Index“ in a relational database Link to corresponding attribute properties.
57
58
Raster vs Vector Volume of data Raster becomes more voluminous as cell size decreases
Source of data Remote sensing elevation data come in raster form Vector favored for administrative data
Software Some GIS better suited to raster, some to vector E.g. IDRISI vs. ArcView
59
Vector vs. Raster Representation
Real World
Discrete Object View
Vector Representation
Raster Representation (Heywood et al. 2006)
60
Vector vs. Raster Representation
(Heywood et al. 2006)
61
Vector vs. Raster Representation
(1) River in real world (2) Raster – Pixel (3) Vector: Simple Line (4) Vector: Complex line (5) Vector: Network (6) Vector: Polygon
62
Raster vs Vector Representation Raster
Vektor
Volume of data
Depends on cell size
Depends on density of vertices
Sources of data
Remote sensing, scanning, imagery, elevation
Survey, administrative, social, infrastructure
Applications
Resources, Environmental
Social, economic, administrative
Resolution
Fixed
Variable
Software
Raster GIS, e.g. IDRISI, ArcGIS Spatial Analyst, Geomedia Grid
Vector GIS, e.g. GeoMedia, ArcView 63
Summary Vector - Raster
Real World Reality
Objects or Entities
Smooth, continuous spatial variation
Set of discrete objects, their attributes and relations
Continuous Conceptual view smooth fields
Sets of simpler objects (atomic entities), their attributes and relations (vector data models)
tessellation (raster data models, TINs) continuous math. functions
GIS Data Models for digital representation
64
Geo-representation problems Defining what needs to be represented Accuracy of representation Volume of data required Fundamental problem Linking an “event” to a place and time Event properties are termed attributes World is vast & infinitely complex How do you represent it properly? 67
Conclusions GIS represents real world phenomena Uses (digital) models Many different types (raster, vector etc.) Simplifies the real world Breaks it into objects, fields etc. Used to answer questions / solve problems Representations vary depending on goals 68
3. Georeferencing
© John Wiley & Sons Ltd
Outline Introduction Placenames Postal addresses and postal codes Linear referencing systems Cadasters Coordinate System: Geographic Coordinate Systems (latitude, longitude) Projected Coordinate systems (x,y) 70 Converting georeferences
Commonly used georeferencing systems
71
Placenames The earliest form of georeferencing And the most commonly used in everyday activities
Many names of geographic features are universally recognized Others may be understood only by locals
Names work at many different scales From continents to small villages and neighborhoods Non-metric, can be very coarse e.g “Europe”
Names may pass out of use in time Where was Camelot, (…the ancient castle of King Arthur in Cornwall)? 72
Postal Addresses and Postcodes Every dwelling and office is a potential destination for mail Dwellings and offices are arrayed along streets, and numbered accordingly Streets have names that are unique within local areas Local areas have names that are unique within larger regions If these assumptions are true, then a postal address is a useful georeference Global, non-metric, spatial resolution may correspond to the size of one mailbox Many ways to write an address – Uniqueness? Address Geocoding: transforming the address (nonmetric) in a point location defined by coordinates 73 (metric).
Where Do Postal Addresses Fail as Georeferences? In rural areas Urban-style addresses have been extended recently to many rural areas
For natural features Lakes, mountains, and rivers cannot be located using postal addresses
When numbering on streets is not sequential E.g. in Japan
74
Positional uncertainty concerning postal addresses representing “mailbox coordinates”
75
Postcodes as Georeferences Defined in many countries E.g. ZIP codes in the US • five-digit ZIP code ZIP (Zoning Improvement Plan) code instituted by the U.S. Postal Service to facilitate mail handling and delivery. • The first digit represents one of ten areas of the country (0 = New England, 9 = West Coast). • The first three digits together represent a sectional center facility or main post office. The last two digits further define the destination point in terms of a post office or delivery center area within a large city or in terms of a small city or town whose residents share the same ZIP code.
Hierarchically structured The first few characters define large areas Subsequent characters designate smaller areas Coarser spatial resolution than postal address
Useful for mapping 77
ZIP code boundaries are a convenient way to summarize data in the US. The dots on the left have been summarized as a density per square mile on the right
Spatial Distribution of Middle/High School Students School Catchement Area BG/BRG St. Martin, Villach, 2005
79
Coordinate Systems: Geographic Coordinate System: Latitude/ Longitude
84
Coordinate Systems: Geographic Coordinate System: Latitude/ Longitude The most comprehensive and powerful method of georeferencing Metric, standard, stable, unique
Uses a well-defined and fixed reference frame Based on the Earth’s rotation and center of mass, and the Greenwich Meridian
85
Latitude and Longitude
Source: http://www.gs-enduro.de/html/navigation/karte.htm 86
Definition of Longitude Prime Meridian at Royal Observatory at Greenwich, London North Pole
Equator Greenwich
Definition of longitude. The Earth is seen here from above the North Pole, looking along the Axis, with the Equator forming the outer circle. The location of Greenwich defines the Prime Meridian. The longitude of the point at the center of the red cross is determined by drawing a plane through it and the axis, and measuring the angle between this87plane and the Prime Meridian.
Definition of Latitude Requires a model of the Earth’s shape The Earth is somewhat elliptical The N-S diameter is roughly 1/300 less than the E-W diameter More accurately modeled as an ellipsoid than a sphere An ellipsoid is formed by rotating an ellipse about its shorter axis (the Earth’s axis in this case)
88
Latitude and the Ellipsoid N
E
W
S
Latitude (of the blue point) is the angle between a perpendicular to the surface and the plane of the Equator WGS 84 Radius of the Earth at the Equator 6378.137 km Flattening 1 part in 298.257 89
Geoid – Ellipsoid- Geodetic Datum
North pole
South pole Source: http://www.gs-enduro.de/html/navigation/karte.htm 90
Geodetic Datums: What are they? Define the size and shape of the earth Used as basis for coordinate systems Variety of models: Flat earth Spherical Ellipsoidal
WGS 84 defines geoid heights for the entire earth
The History of Ellipsoids Because the Earth is not shaped precisely as an ellipsoid, initially each country felt free to adopt its own as the most accurate approximation to its own part of the Earth We must distinguish between national ellipsoids &
global ellipsoids
Today an international standard has been adopted known as WGS 84 Its US implementation is the North American Datum of 1983 (NAD 83) Many US maps and data sets still use the North American Datum of 1927 (NAD 27) Differences can be as much as 200 m 92
Longitude & Latitude & Distance Lat –Lon are equally far apart at the Equator; towards the poles lines of longitude converge Longitude (-180 ≤ λ ≤ + 180) Shortening towards the north pole (≈ cosine of latitude) 1° long (Equator) = 111km 1° long (60° N (North Boundary Alberta province, CA) = 55 km
Latitude (-90 (S) ≤ θ ≤ + 90 (N)) 2 points on same degree longitude separated by: • 1° lat: 111km • 1‘ lat: 1.86 km (1 nautical mile) 93 • 1‘‘ lat: 30m
Coordinate Systems: Projected Coordinate Systems: Projections and Coordinates There are many reasons for wanting to project the Earth’s surface onto a plane, rather than deal with the curved surface Cartesian Coordinate system The paper used to output GIS maps is flat Flat maps are scanned and digitized to create GIS databases Rasters are flat, it’s impossible to create a raster on a curved surface The Earth has to be projected to see all of it at once It’s much easier to measure distance on a plane
94
Distortions Any projection must distort the Earth in some way Two types of projections are important in GIS Conformal property: Shapes of small features are
preserved: anywhere on the projection the distortion is the same in all directions Equal area property: Shapes are distorted, but features have the correct area Both types of projections will generally distort distances 95
Cylindrical Projections Conceptualized as the result of wrapping a cylinder of paper around the Earth The Mercator projection is conformal
96
Conic Projections Conceptualized as the result of wrapping a cone of paper around the Earth Standard Parallels occur where the cone intersects the Earth
97
The Universal Transverse Mercator (UTM) Projection (Global) Developed 1940‘s by US Army Corps of Engineers A type of cylindrical projection Implemented as an internationally standard coordinate system Initially devised as a military standard
Uses a system of 60 zones Maximum distortion is 0.04%
Transverse Mercator because the cylinder is
wrapped around the Poles, not the Equator 98
N
S
Zones are each six degrees of longitude, numbered as shown at the top, from W to E
Comparison of 3 different map projections
103
Coordinate Systems - Summary Coordinate System Types: Geographic (lat, lon) • Ellipsoid (geodetic datum): Model of the earth – Global: WGS 84
Projected (x
(easting),y (northing))
• Projection algorthim, e.g. Gauss Krüger Projection • Ellipsoid (geodetic datum) – Global: e.g. WGS 84 – Local/national: e.g. Bessel 1841 (Austria)
104
Georeferencing Raster Datasets
Overview Why georeferencing raster datasets? Workflow Overview Ground Control Points Raster Transformation Quality assessment of transformation
Mean Square Error)
Resampling process
World file
(Root
Why georeferencing raster datasets? Raster data are obtained by Scanning maps Aerial photographs Satellite images
In order to align raster with other data in your project, spatial reference information (position of raster in relation to real world) is needed Georeferencing the raster to a map coordinate system
Spatial reference information Scanned maps No real world spatial reference information!
„Scanner geometry“
Aerial photographs & satellite images
N columns
May have spatial reference information in a separate header file Proprietary formats N rows Sometimes incomplete pixel size (e.g. 5m)
General steps for georeferencing a raster Use of existing spatial data with known map coordinate system (real world coordinates) Identify ground control points • Can be accurately definied on raster and in real world coordinates
Perform raster registration • If alignment quality is sufficient (RMS Error check) • Select transformation & resampling method
Permanent transformation of raster
Ground Control Points Accurately definied position on raster and in real world coordinates Often vector data, but also already georeferenced raster (e.g. orthoimage) can be used
Look for significant recognizable locations on raster • Road or stream intersections • Rock outcrops • Mouth of a stream • „Corner of a field“ (– really?), street or building
Ground Control Points Position of control point on raster (source)
Position of control point in real world (target)
Ground Control Points Use enough ground control points Spread over the entire raster
(“tent poles“)
• At least one at corner regions, and several in interior • Number depends on raster size
Accuracy of raster georeferencing is only as accurate as the data (e.g. vector data, orthoimage) which are used for the transformation (Motto: „Poor input, poor output“).
Raster Transformation Process of matching the raster to map coordinates of the target data („Rubber sheeting“) Different transformation algorithms/equations Polynominal (1st i.e. affine; 2nd; 3rd order) • Affine 1st order commonly used for georeferencing rasters • Global optimization
Spline • local optimization
Adjust
Raster Transformation (Example affine 1st order polynominal transformation)
x´,y´: New calculated coordinates of center of upper left pixel of raster
General formula (Least Squares fitting algorithm ) in order fit all control points (global accuracy, not a local one!)
Quality assessment of Transformation Interpretation of Root Mean Square Error (RMS)
Global adjustment optimization – not all control points may be matched to 100% Residual positional difference (in map units, e.g. m) between true position of a control point and calculated position by transformation algorithm. Calculated for each control point Total Error is Root Mean Square sum of all the individual residuals , ie. RMS Value Assessment for quality of transformation
RMS Error The RMS error measures the errors between the destination control points and the transformed, new locations of the source control points Minimum of 3 control points is needed to calculate a RMS Error
Resampling Process of changing the geometry of a raster data set and adjusting cell values Georeferencing („Rubber Sheeting“) Change in Projection Translation, Rotation Change in cell size
Resampling Cell values must be also adjusted! During georeferencing, a matrix of empty cells is computed using map coordinates Each empty cell is given a value based on original values in the ungeoreferenced data set and the resampling
process
Resampling techniques: • Nearest neighbor – Doesn‘t change input values – Nominal and ordinal data, e.g. land use, forest type
• Bilinear interpolation – Uses values of the 4 nearest input cells to determine the new value in the output raster – Continuous data, e.g. elevation, temperature
• Cubic convolution – 16 nearest input cells; aerial photography, satellite images
World file Georeferencing information for raster data sets (ESRI Format)
The y-scale (E) is negative because the origins of an image and a geographic coordinate system are different. The origin of an image is located in the upper left corner, whereas the origin of the map coordinate system is located in the lower left corner.
World file Georeferencing information for raster data sets (ESRI Format) After rectification and resampling, world file is assigned Simple text file accompanying an image file with the following naming convention • Same name as image file, but „w“ at end of file name
Georeferencing a raster data set in ArcGIS View video in ArcGIS Help Open ArcMap > ArcGIS Desktop Help > Search „georeferencing raster“
Intro Lab „Earthquake Risk Zones Tadjikistan“ • Task: Visualize Earthquake Riskzones in Tadjikistan using simples GIS techniques -
Natural Hazards Data Base on EARTHQUAKES: world_earthquakes.shp Administrative boundaries of Tadjikistan: TJK_admin0-3.shp
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Intro Lab „Earthquake Risk Zones Tadjikistan“
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Introduction to GPS
What is GPS? The Global Positioning System (GPS) A Constellation of Earth-Orbiting Satellites Maintained by the United States Government for the Purpose of Defining Geographic Positions On and Above the Surface of the Earth. It consists of Three Segments: User Segment Control Segment Space Segment
GPS – System Overview
GPS – Global Positioning System • Space Segment -
30 Satellites 20200 km 12 h Orbital 6 Inclinations (with 60° offset) Every time at every point 4 Satellites visible
• Control Segment -
5 Control Stations Observation and Synchronization der Sat-Clocks Transmitting of orbit information to the satellites
• User Segment -
Receiver WWW.FH-KAERNTEN.AT
Common Uses for GPS • Land, Sea and Air Navigation and Tracking • Surveying/ Mapping • Military Applications • Recreational Uses 179
How the system works Space Segment 24+ Satellites
The Current Ephemeris is Transmitted to Users
Monitor Stations
Diego Garcia Ascension Island Kwajalein Hawaii Colorado Springs
GPS Control
End User
Colorado Springs
GPS – Global Positioning System • Determination of Position -
Trilateration Distance measurement between satellites & receiver is based on signal runtime At least 3 Distances for x and y (Satellites) At least 4 Distances for x, y and z (Satellites) Position accuracy adjustment with every additional satellite (distance).
• Signals( 2 carrier frequencies L1 and L2) -
Navigation and system information is modulated on the carrier P-Code C/A Code WWW.FH-KAERNTEN.AT
Triangulation Satellite 1
Satellite 3
Distance Measuring The whole system revolves around time!!! Distance = Ratemiles x Time Rate = 186,000 per second (Speed of Light) Time = time it takes signal to travel from the SV to GPS receiver
Satellite 2
Satellite 4
Each satellite carries around four atomic clocks Uses the oscillation of cesium and rubidium atoms to measure time Accuracy? plus/minus a second over more than 30,000 years!!
SV and Receiver Clocks • SV Clocks 2 Cesium & 2 Rubidium in each SV $100,000-$500,000 each
• Receiver Clocks Clocks similar to quartz watch Always an error between satellite and receiver clocks ( Δ t)
• 4 satellites required to solve for x, y, z, and Δ t 184 ESSC 541 542
4 SOLUTION
• PROBLEM
Can’t use atomic clocks in receiver Cesium Clock = $$$$$$$!!! Size of PC
– Receiver clocks accurate over short periods of time – Reset often – 4th SV used to recalibrate receiver clock
Breaking the Code The Carrier Signal...
Transmission Time
combined with… The PRN code...
Satellite
produces the Modulated carrier signal which is transmitted... demodulated...
Receiver
And detected by receiver, Locked-on, but With a time delay...
Time delay 186
Sources of Error • Selective Availability o Intentional degradation of GPS accuracy o 100m in horizontal and 160m in vertical o Accounted for most error in standard GPS o Turned off May 2, 2000
187
Sources of Error • Geometric Dilution of Precision (GDOP) Describes sensitivity of receiver to changes in the geometric positioning of the SVs
• The higher the DOP value, the poorer the measurement QUALITY Very Good Good Fair Suspect
DOP 1-3 4-5 6 >6 ESSC 541 542
188
Sources of Error • Clock Error Differences between satellite clock and receiver clock
• Ionosphere Delays
nal g i S l
d a gn ct e e Si l f t c Re re Di GPS Antenna
Caused by local reflections of the GPS signal that mix with the desired signal
Re fle cte d
Sig
• Multipath Error
Satellite
na l
Delay of GPS signals as they pass through the layer of charged ions and free electrons known as the ionosphere.
Hard Surface 189 ESSC 541 542
GPS – Global Positioning System • SPS (Standard Positioning Service) -
Public available Originally 100 m accuracy Since May 2000 15 m accuracy (US military switched off artificial degradation (i.e. Selective Availability)
• PPS (Precise Positioning Service) -
Available for the US military Originally 22 m accuracy, but current accuracy is unknown. Signals are encrypted
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GPS – Global Positioning System • Accuracy factors -
Runtime errors of satellite signals Reflections on objects and earth surface (multi-path effects) To few satellites because of hidden horizon (in valleys or “street canyons”) Signal attenuation by dense vegetation (especially in the Forrest) Clock errors a) specially of the GPS-receivers! b) Satellites have atomic clocks!
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Differential GPS • Method of removing errors that affect GPS measurements • A base station receiver is set up on a location where the coordinates are known • Signal time at reference location is compared to time at remote location • Time difference represents error in satellite’s signal • Real-time corrections transmitted to remote receiver Single frequency (1-5 m) Dual frequency (sub-meter)
Reference location
Remote location
= Error
• Post-Processing DGPS involves correcting at a later time
GPS – Global Positioning System
GPS-Satellite
db1 + eb1
• DGPS Approach
d + e? db2 + eb2
eb1 Base station
eb2 Error Base station Correction D = F(d, eb1, eb2, …) + optional WAAS, EGNOS or MSAS
Error Correction
GPS – Global Positioning System • NAVSTAR GPS -
USA – Global Positioning System – 31 Satellites
• GLONASS -
Russia – 24 Satellites (since September 2010, planned 30 Satellites)
• GALILEO -
EU – 2 Satellites for Tests (planned 30 Satellites)
• KOMPASS -
China – planned 35 Satellites
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GPS – Global Positioning System • Applications -
Car navigation (z.B.TomTom) Theft protection (in combination with GSM) Outdoor Sport – Trekking, Biking, Running, … Seafaring (Standard) Aviation (Standard) Mobile Mapping (GIS) Precision Farming Fleet management (transport logistic) Land survey … WWW.FH-KAERNTEN.AT
Geocaching • A great way to introduce students to GPS - Teach latitude/longitude - Take advantage of the wonderful features and capability of your GPS unit
• An entertaining adventure for GPS users - Individuals and organizations all over the world have set up caches and shared the locations of these caches on the Internet - Participate in a cache hunt to find an existing cache or create your own
• www.geocaching.com WWW.FH-KAERNTEN.AT
“Mobile Mapping” • Integrates GPS technology and GIS software • Makes GIS data directly accessible in the field • Can be augmented with wireless technology
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Practical session To learn about the capability of GIS analysis some practical tasks will explain how to work with tools out of ArcGIS. The tasks begin with a familiarization of the software environment and lead over data capturing to data analysis and visualization skills. Some practical GPS measurements will be the base for the georeferencing of an aerial image of a part of Dushanbe. The following six tasks should give an introduction to the use of spatial analysis tools of ArcGIS 9.3. After completing Task 1- 6 a map layout will be created as one publication option of spatial data. Following assignments have to be done: Task 1: Familiarization with the given spatial data Task 2: Georeferencing of given aerial images and measuring of image related attributes Task 3: Proving that more than one half of Tajikistan is situated above 3000m Task 4: Calculation of the mean height above sea level of neighboring countries Task 5: Investigation of connectivity of Tajikistan to its capital Dushanbe Task 6: Detection of potential solar power areas plants within Tajikistan After these GIS analysis a map out of one of these 6 tasks will be produced. For every task the requested results and assistance how to come to these results is added to the problem definition. The required spatial data will be provided by the lecturer.
Practical Session: Task 1 Problem definition: Familiarize with the given spatial data. Requested results: •
List all spatial data sets and give information about data type – raster, vector – and about the spatial reference system.
Assistance: Data investigation within ArcMap • • • •
:
File > Add Data… or Right mouse click on data set > Open Attribute Table Right mouse click on data set > Zoom To Layer Right mouse click on data set > Properties…
Data investigation within ArcCatalog : • Navigate to the data set. • Select Contents/Preview/Metadata tab. • Right mouse click on data set > Properties…
. . .
.
Practical Session: Task 2 Problem definition: Do a georeferencing of the given aerial images and measure image related attributes. • • • •
Use the self-measured GPS reference points to georeference the potanical_garden.tif. Use corresponding matching points between potanical_garden.tif and university.tif to georeference the university.tif image. Measure the spatial size, length and width in meters, of the aerial images. Measure the geometrical resolution, length and width in meters of a pixel, of the aerial images.
Requested results: •
Specify the spatial size and the geometrical resolution of the given aerial images.
Assistance: Show Georeferencing Toolbar in ArcMap for georeferencing images: • View > Toolbars > Georeferencing. • •
New Toolbar: Select aerial image to georeference in drop-down menu Layer.
In case you have control point coordinates: • Add a control point in the aerial image; single left mouse click! • Single right mouse click to control point context menu:
•
.
.
Enter self-measured GPS coordinates: (X = Longitude in DD, Y = Latitude in DD) .
In case you use corresponding matching points: • Add a control point in the ungeoreferenced aerial image; single left mouse click; you have set a green cross. • Add a matching point in the georeferenced aerial image; single left mouse click; you have set a red cross. Show Tools Toolbar in ArcMap for distance measurement: • View > Toolbars > Tools.
• •
New Toolbar: Start measuring:
. .
Practical Session: Task 3 Problem definition: Prove that more than one half of Tajikistan is situated above 3000m – as it is said in travel guides. Requested results: •
Contrast the size of area below 3000m with the size of area above 3000m. Quote the absolute size in square kilometers and the relative size referred to the total size of Tajikistan in percent.
Assistance: Show Toolbox window in ArcMap for a variety of functions: . • Window > Toolbox Create a raster data subset masked by a polygon: • Toolbox > Spatial Analyst Tools > Extraction > Extract by Mask. • Input raster: initial raster data set. • Input raster or feature mask data: masking polygon data set. Find raster cells above a special value: • View > Toolbars > Spatial Analyst. • • •
New Toolbar: Spatial Analyst > Raster Calculator… Express a pseudo SQL statement and execute it. A new raster with true (1) and false (0) values results.
Get statistic information: • Toolbox > Spatial Analyst Tools > Zonal > Zonal Statistics as Table. • Input raster or feature zone data: Result of Raster Calculator. • Zone field: VALUE (1 for true and 0 for false). • Input value raster: Result of Raster Calculator. • Open resulting table in ArcCatalog.
Practical Session: Task 4 Problem definition: Calculate the mean height above sea level of all countries which name ends on ‘-stan’ and which is neighbor to Tajikistan including Tajikistan. Requested results: •
List all detected countries including their mean height above sea level.
Assistance: Select features by attribute values: • Selection > Select By Attributes. • Layer: Country data set. • Method: Create a new selection. • Express the Where clause of the SQL statement and apply. Export selected features as new shape file (It will be necessary to export Tajikistan form the world country data set!): • Right mouse click on data set > Data > Export Data… • Export: Selected features. • Use the same coordinate system as: this layers’ source data Select features by location: • Selection > Select By Location. • I want to: select from the currently selected feature in (If the result of the previous selection is still active!). • the following layer(s): Country data set. • that: touch the boundary of. • the feature in this layer: Tajikistan data set Get statistic information: • Toolbox > Spatial Analyst Tools > Zonal > Zonal Statistics as Table. • Input raster or feature zone data: Features of the requested countries (data export). • Zone field: NAME. • Input value raster: Digital elevation model of the region. • Open resulting table in ArcCatalog.
Practical Session: Task 5 Problem definition: Investigate the connectivity of Tajikistan to its capital Dushanbe based on the slope values of the terrain as cost indicator. • • • • •
Create a new point shape file and digitize the city of Dushanbe. Calculate a slope model based on the given digital elevation model. Do a general area based distance investigation to Dushanbe using the slope values as cost indicator. Create a new point shape file and digitize four arbitrary cities of Tajikistan. Calculate the shortest routes from the four cities to Dushanbe based on the slope model.
Requested results: • •
Create a map which shows the connectivity of Tajikistan to its capital. Show four shortest routes from the cities to Dushanbe.
Assistance: Create a new point shape file within the ArcCatalog: • Right mouse click on the folder where you want to create a new shape file > New > • • • • •
Shape file… . Name: arbitrary, but wise. Feature Type: Point. Edit… for Spatial Reference System > Select… > Geographic Coordinate System > World > WGS 1984.prj Several times OK Right mouse click on new created shape file > Properties… > Fields: Type in a new Field Name for city names from Data Type Text.
Show editing toolbar for digitizing new features: • View > Toolbars > Editor •
New Toolbar:
Creating new features in point shape file: • Editor > Start Editing • Check if Source is highlighting the folder which contains the new created shape file. Otherwise click on the correct folder. • Editor toolbar activates more menu buttons. • Task: Create New Feature. • Target: new created shape file. • •
Click on the sketch tool to start digitizing Click on the places you want to digitize in the map. One click, one new feature!
• •
After digitizing click on Attributes button to add attribute information, e.g. name. Editor > Save Edits and Editor > Stop Editing quits edit mode.
Calculate a slope model: • Activate the Spatial Analyst Toolbar (cp. Task 3). • Spatial Analyst > Surface Analysis > Slope… • Input surface: Digital elevation model of Tajikistan. Calculate distances: • Activate the Spatial Analyst Toolbar (cp. Task 3). • Spatial Analyst > Distance > Cost Weighted… • Distance to: City of Dushanbe point shape. • Cost raster: slope model. • Activate Create direction and Create allocation for following route computation. Calculate routes: • Activate the Spatial Analyst Toolbar (cp. Task 3). • Spatial Analyst > Distance > Shortest Path… • Path to: Point shape of four digitized cities. • Cost distance raster: Results from distance calculation. • Cost direction raster: Results from distance calculation. • Path type: For Each Cell.
Practical Session: Task 6 Problem definition: Detect all areas within Tajikistan which can be seen as potential locations for solar power plants. • • • • • •
Calculate a slope model based on the given digital elevation model. Calculate an aspect model based on the given digital elevation model. Areas which hold slope values between 10 and 30 degrees and aspect values between south east and south west can be seen as optimal. Potential locations should be placed near areas of high population – maximum distance of 50km. Do detect highly populated areas use the nightlight data set. Create a data subset of nightlights raster for Tajikistan. Potential location should be placed near road infrastructure – maximum distance of 15km. Create a data subset of roads for Tajikistan. The size of a single potential location should not be smaller than 10km²
Requested results: • •
Create a map which shows the connectivity to the major centers of Tajikistan. Show four shortest routes from the cities to Dushanbe based on the minimum slope values of the terrain.
Assistance: Calculate an aspect model: • Activate the Spatial Analyst Toolbar (cp. Task 3). • Spatial Analyst > Surface Analysis > Aspect… • Input surface: Digital elevation model of Tajikistan. Create a raster data subset masked by a grid value: • Toolbox > Spatial Analyst Tools > Extraction > Extract by Attributes. • Input raster: initial raster data set. • Where clause: Express a SQL-Where clause e.g. “VALUE” > 0. Convert raster to polygon features: • Toolbox > Conversion Tools > From Raster > Raster to Polygon. • Input raster: Raster to convert. • Field: Value for polygon attribute field. Create a vector data subset masked by a polygon (For extraction of the Tajik road infrastructure): • Combine Select By Location and export selected feature as new shape file. or • Toolbox > Analysis Tools > Overlay > Intersect. • Input Features: Polygon of the Tajik country and Line of the Asian road infrastructure.
Create a buffer around a vector data set: • Toolbox > Analysis Tools > Proximity > Buffer. • Input Features: Vector data set. • Linear unit: 50 / 15 Kilometers. Convert a vector data set to a raster data set: • Toolbox > Conversion Tools > To Raster > Polygon to Raster. • Input Features: Buffer of the centers of Tajikistan / Buffer of Tajik roads. • Value field: GRIDCODE • Cellsize: should be same size as digital elevation model (e.g. 882). Upgrade vector data set – Area size attribute: • Right mouse click on vector data set > Open Attribute Table. • Options > Add Field… • Name: area • Type: Float • OK • Right mouse click on headline of the new area attribute > Calculate Geometry… • Property: Area • Units: Square Kilometers.
Map Layout Problem definition: Create a map out of one of the results from Task 1 – 6. Requested results: • • •
Complete map layout with map features like title, north arrow, scalebar, legend, overview map, copyright information and a brief description of the map content. Technical report with a workflow description Prepare a short presentation of the generated map for the closing ceremony on Friday, 24th afternoon.
Assistance: Preparation of Overview map: • Insert a second Data Frame for the overview map with Insert > Data Frame (see Fig. 1) • •
File > Add Data (e.g. country boundaries) … or Right mouse click on data set > Properties…
• •
Layer Properties > Label … Layer Properties > Symbology > Show: Categories > o Unique values, many fields
•
.
> ‘Tajikistan’ o Add Values o Change color of Tajik polygon Right mouse click on New Data Frame > Properties > Extent Rectangles
•
Add Layer with frames’ list
•
Click Frame Button
to ‘Show extent rectangle for these data to format the rectangle
Fig. 1: Insert Menu
Layout of the map • Change to Layout View with View > Layout View … • Insert Title of the map with Insert > Title (see Fig. 1) • Insert the same way Legend, North Arrow, Scale Bar, Scale Text • Insert Text with a copyright information and a brief description of the map content • Arrange a attractive design of the map Export of the map • File > Export Map • Choose PDF as file format and edit the export options Technical report and presentation • TR: Description of workflow to generate the map with screenshots of the main tasks • Presentation of max. 5 slides for the presentation of the map
Dushanbe GIS Training Hydrological Run-off Modelling for Determination of Hydroelectric Potential in ArcGIS, SAGA and GRASS
Andrew D. Smith Department of Geodesy and Geoinformatics Kyrgyz State University of Construction, Transport and Architecture
A couple of words on raster (or cell based) processing z
Raster vs vector (include why raster)
z
Types of raster analysis −
Cell arithmetic (one or more rasters)
−
Neighbourhood processing
−
Zonal processing
−
Modelling of movement
−
Interpolation
Vector/Raster? GIS data can be represented in either raster or vector format. Vector format represents data as objects and has three different types:- Point - Line and - Polygon (or Area)
This diagram shows how the same objects are represented in both vector and raster format
Raster format is like a digital photo and uses cells (or pixels) to represent data.
Raster/Vector Raster
Vector
type of data
discreet and continuous
discreet
boundary representation
fuzzy
exact
file size
large
small
3200 m pixel 15 KB
Raster Resolution
1600 m pixel 60 KB 800 m pixel 239 KB
400 m pixel 960 KB 200 m pixel 3.75 MB
Sm Mo all Mo re er c re det ell m ail /pix em el or siz y e
Two Types of Raster Data z
Continuous Elevation
z
Discrete Landcover
Regions
Population
Cell Arithmetic Raster 1
+
Raster 2
= Raster 3
Source of Diagrams – ESRI: Using ArcGIS Spatial Analyst 9
Neighbourhood, or Focal, Processing Neighbourhood functions can return the sum, mean, maximum, minimum, standard deviation for the cells in the immediate or extended neighbourhood
e.g. 24 is the sum of all the surrounding cells
So for the whole raster the result would look like this diagram
Neighbourhood functions are often used for filtering data Source of diagrams ArcGIS Desktop Help http://webhelp.esri.com/
Neighbourhood, or Focal, Processing example Focal Mean
Focal mean is often used to filter a dataset
Zonal Processing Zonal functions uses two input layers and is useful for example: z
z
z
to calculate the populations per oblast Or highest point in each oblast Or the total rainfall in each oblast
Source of diagrams ArcGIS Desktop Help http://webhelp.esri.com/
Value Raster
Zonal Processing example Zonal Sum Result Raster
Zones Raster
Modelling of movement To model the flow of water we don't need to look at the entire area first off – we consider only how water will flow from one cell to the next for example:If the diagram left represents a DTM (height) then water will flow from one cell to the lowest of the neighbouring cells (e.g. 55 to 35) and from there it will continue to flow to the lowest cell. and so on as in the diagram on the right
and process is simply repeated for all for all cells in the study area
Interpolation Interpolation is the process that predicts values for cells in a raster from a limited number of sample data points.
For example predicting rainfall from weather gauge stations
Our data & goal Study Area
Digital Terrain Model
Our Our goal goal is is to to determine determine how how much much of of this this rainfall rainfall will will be be available available to to generate generate electric electric power power Rainfall
Runoff Curve Number (a measure of drainage)
Preprocessing 1 Rainfall to volume/cell z
Rainfall is in mm per month
z
Each cell is 50x50 metres (i.e. 2500m2)
z
Therefore to obtain a volume per cell in m3 per month the following formula can be used:-
;;
Preprocessing 2 Rain volume to runoff volume The SCS Runoff Equation
Where Q = run-off P = precipitation, and S is a simplified parameter representing losses (that is the water that doesn't become run-off) S is a function of the Run-off Curve Number (CN) which are a function of land-use and soil type, S is defined as:
NRCS. Module 205 – SCS Runoff Equation. July 1999
Hydrological Modelling
Preprocessing 1 - Sinks
Sinks are depressions in the DTM which prevent water from flowing flowing out. Sometimes sinks are valid e.g. lakes but for hydrological modelling modelling we usually want to remove them
Hydrological Modelling
Preprocessing 2 - Filling Sinks Sinks Unfilled
To fill sinks we need to replace them with the lowest value of the surrounding cells
Hydrological Modelling
Preprocessing 3 - Filling Sinks Sinks Filled
To fill sinks we need to replace them with the lowest value of the surrounding cells
Hydrological Modelling – 1 Flow Direction
From the DTM it is possible to calculate Flow Direction
Hydrological Modelling 2 Flow Direction
Flow Direction is usually represented by numeric values – this example is for SAGA GIS
0N
1 NE
2E
3 SE
4S
5 SW
6W
7 NW
Hydrological Modelling 3 Flow Accumulation
Flow Direction can be used to calculate Flow Accumulation which will be used to provide runoff volume
Hydrological Modelling 4 Stream Network
Flow Direction can also be used to generate a vector stream network
References z
z
z
z
z
z
z
z
NRCS. Module 205 – SCS Runoff Equation. July 1999 Texas Dept. of Transportation, “Hydraulic Design Manual” Chapter 5, Section 7 — NRCS Runoff Curve Number Methods. 2009 Vandal N. Using GIS to Model Runoff Time, Runoff quantity, and Stream Flow. 2005 Middlebury College Wikipedia. Runoff model (reservoir). http://en.wikipedia.org/wiki/Runoff_model_(reservoir).htm - access date 23February-2010 Wikipedia. Surface runoff. http://en.wikipedia.org/wiki/Surface_runoff.htm access date 23-February-2010 Wikipedia. Runoff curve number. http://en.wikipedia.org/wiki/Runoff_curve_number.htm- access date 1-March2010 ESRI: Using ArcGIS Online help. http://webhelp.esri.com/arcgisdesktop – access date 13-September-2010 ESRI: Using ArcGIS Spatial Analyst - 2001-2002
Dushanbe GIS Training
Hydrological Run-off Modelling for Determination of Hydroelectric Potential Practical using ArcGIS Spatial Analyst and Model Builder Andrew D. Smith Department of Geodesy and Geoinformatics Kyrgyz State University of Construction, Transport and Architecture
Open ArcGIS project
ArcGIS/RunoffModel_Start92.mxd And examine each data layer...
Activate the Spatial Analyst and 3D Analyst extensions From the “Tools” menu select “Extensions” Ensure that there is a check in the bod by Spatial Analyst and 3D Analyst and select “Close”
Open ArcToolbox and create a new model Step 1 – Open Arc Toolbox
Step 3 – Create a new Model
Step 2 – Create a new Toolbox
NB you can rename this toolbox
Add the base data to the model 1, Drag the Layer “Rainfall” onto The Model
2, Repeat for all three Raster layers
3, You should save your model Now, and after every step
Set up basic model properties 2
1 3
1) Select “Model Properties” Properties” from the “Model” Model” menu 2) Check “Current Workspace” Workspace” and “Extent” Extent” in the “General Settings” Settings” and “Cell Size” Size” in the “Raster Analysis Settings” Settings” 3) Click the “Values” Values” button and update as shown
Processing rainfall for model Before we start hydrological modelling proper we need to convert rain fall to runoff, this is a two stage process: −
First we need to convert rainfall in mm to rain volume in cubic metres (m3) as we are working with a 50 metre grid square we can use the following conversion: This is Step 1
−
Secondly we need to work out how much of this volume will actually become run off. This is Step 2
Adding processing for Step 1 - “Rainfall to Volume” (part a) 1, Drag the Tool “Single Output Map Algebra” onto The Model
2. Double click on the tool to open it
Step 1 - “Rainfall to Volume” (part b) 2
3 1) Select the dropdown box to select “Rainfall” as the input raster 2) Enter the formula in the Map Algebra field as shown* 3) Change the raster to Rainvolume 4) Select OK when finished
1
4
*Note the formula:
int ( 2500 * ( float ( [rainfall] ) / 1000 ) )
Is the same as that shown right but we need to use the functions int() and float() to cntrol the format of the answer and the input
Step 1 - “Rainfall to Volume” (part c)
You can now right click on the tool and rename it to something meaningful
☺ ☺ ☺ It would be a good idea to save your model now
Test the model so far
1
1) Right click on the tool and select “Run” 2) Right click on the rainvolume raster and select “Add to Display”
2
☺ ☺ ☺ It would also be a good idea to save your ArcMap Project now
Adding processing for Step 2 - “Volume to Run off” The process for this step is very similar to the previous, except that there are two inputs CN and RAINVOLUME. The combined “Run-off” equation:
Corresponds to the following in ArcGIS: Pow( [rainvolume] - 0.2 * ( (1000 / [CN] ) - 10 ) , 2 ) / ( [rainvolume] + 0.8 * ( (1000 / [CN] ) - 10 ) )
Your task is to complete this step on your own Don't forget to save your work
Adding processing for Step 3 – Filling Sinks 1, Drag the “Fill” Tool, from the “Hydrology” section of the “Spatial Analyst Tools”, onto the Model
This Fill process will take some time to run so be patient
2, Edit the input and output to match the diagram
Adding processing for Step 4 – Flow Direction
In the same way add the “Flow Direction” tool and add update the inputs and outputs as shown NB the drop raster is an optional output that can use later
Step 4 – Flow Direction Run the model and add the result to the display to view the output
East Southeast South Southwest West Northwest North Northeast
NB the numbers refer to the direction of flow as indicated
Adding processing for Step 5 – Flow Accumulation
Flow Accumulation has two inputs it is important that you set “dtm_flowdir” as the “Input flow raster” and “runoff” as the “Input weight raster”
Step 5 – Flow Accumulation (cont.) Now run the model Note that Flow Accumulation will take some time to run so be patient
Add the result to the display. Note you will need to change the colour-ramp to the one shown.
Now zoom in and view the result – also use the identify tool to view pixel values in a number of locations Note this raster “Riverflow” represents the cumulative runoff in m3 at every point in the study area
Step 6 – Extracting riverflow volumes to pourpoints The shapefile “pourpoints” has points just downstream of all significant river intersections. We will nor use our “riverflow” raster to calculate flow volumes at each of these intersections The steps to follow are:−
Add the “pourpoints” layer to the model
−
Add the tool “Extract values to Points” from the “Extraction” section of the “Spatial Analyst”
Step 6 – Extracting riverflow volumes to pourpoints The resultant point shape file,once added to the map, can be symbolised to represent the flow volumes at these pour points
The completed model
Additional – Making the Model Generic and Repeating Processing for Tajikistan Using Parameters Tajik Data Different rainfall coverages
Preparing Small-Scale Hydropower Projects for Private Sector Participation Consulting Services to Government of Tajikistan Presentation of the current findings enerGIS’10 Dushanbe / Tajikistan
Authors: • Ernst Basler & Partner • ITECO • GeoIdee.ch
enerGIS‘10, 23 September 2010
2
Project scope and timeline Phase I: Strategic Review December 2009 - July 2010
Baseline assessment of SSHP-Development Elaboration of SSHP-Development Strategic Plan (Initial Site Screening) Site selection for Phase II/III Review of existing regulatory/commercial framework regarding SSHP-Integration Elaboration of action plan to improve regulatory/commercial framework
Commitment of GOT to immediate implementation of action plan Letter of invitation to potential investors on EBRD website with results of Phase I Government should receive several Expressions of Interests to above invitation for EoI
Phase II: (Pilot) Project Preparation 5 Months
Elaboration of Preliminary Site Documention – feasibility assessment (33 sites) Envrionmental and Social Impact Assessment (2 sites) Refinement of financing framework
Phase III: Concession Tender Assistance 6 Months 19.10.2010
Concession tender assistance
enerGIS‘10, 23 September 2010
3
Development Strategic Plan PHASE I - Development Strategic Plan
Data collection for 46 sites (sites proposed by MEI)
Transparent assessment and ranking
Selection of 33 sites for further specification (Phase II) and subsequent tendering (min. 20 sites)
Potential SSHP sites identified in previous SSHP-programmes (more than 160 sites) Proposed 54 potential sites as per UNDP SSHP Strategy (2007) - medium/ longterm development programme) Selected 46 potential sites by the MEI / (February 2010)
Site specific data
Initial Site Screening
Technical criteria Social and environmental criteria Commercial criteria Economical criteria
GIS Data Ranking 1 2 3 4
... 46
Site Name ... ... ... ...
...
19.10.2010
enerGIS‘10, 23 September 2010
Selection Criteria I/II
Economical criteria Power = Economy of Scale Gradient (Head) = Economy of Density of Resource Geology, Natural Hazard, etc. Length of Feed-in Line (Distance to high tension grid) As far as available for selection
Distance to next transport road Synergies and conflicts with other (water-) infrastructures
10/19/2010
4
enerGIS‘10, 23 September 2010
5
Selection Criteria II/II
Qualitative criteria Risks (Natural hazards, hydrology, data accuracy, …) Climate change risks Social impact Considered positive and negative impact Ecological impact Fish migration Reserved flow (riparian flow) Landscape … 10/19/2010
enerGIS‘10, 23 September 2010
6
Screening Sites
19.10.2010
Category
Nr. of sites
< 1MW
29
1 -10 MW
15
10 – 30 MW
2
Reconstruction
1 (< 1 MW) 3 (1-10 MW)
enerGIS‘10, 23 September 2010
7
Small Hydropower – Site Database I/III Collection of site specific data (Access-Database)
Technical scheme data Site conditions
Site hydrology Site access (grid, road) Environmental and social impact
Issues/ Remarks Desk work No onsite-data collection in this phase Limited data availability
19.10.2010
enerGIS‘10, 23 September 2010
Small Hydropower – Site Database II/III
19.10.2010
8
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9
Small Hydropower – Site Database III/III
19.10.2010
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10
Small Hydropower – GIS I/VI Collection of available GIS-data Digitalization of analog data Simple Modeling
Topographic basemaps Digital elevation model (ASTER)
Electrical Grid-Data Various geographical mapsets Sociological data ... -> Open system for further data Issues No central data host Restricted access to official data Limited digital data availability – e.g. El. Grid only on paper!
10/19/2010
enerGIS‘10, 23 September 2010
11
Small Hydropower – GIS II/VI Scale
Base data (Maps, Population, DEM, Glacier, …) Specific Information (Geology, Hydrology, Precipitation, Observation Stations, Protected Areas, …) Project data (Site location, Scheme, Catchment …)
1:800’000
Level Of Detail 1:50’000
10/19/2010
enerGIS‘10, 23 September 2010
Small Hydropower – GIS III/VI
19.10.2010
12
enerGIS‘10, 23 September 2010
13
Small Hydropower – GIS IV/VI
19.10.2010
enerGIS‘10, 23 September 2010
14
Small Hydropower – GIS V/VI ite:31
Schematics of all Sites which have to be ranked Scale 1:50 000 Main features of the Site (Power House, Diversion # Structure, Reserved Flow Segment, …) !
41
Legend # !
Transmission Line
PowerStation DischargePoint AbstractionPoint
")
HeadPond Headrace Pipe
Uplink to Main Grid
Headrace Channel Headrace Tunnel Penstock Tailrace Dam Reservoir
0.1 Kilometers
19.10.2010
± 0
Reserved flow segm
d
d
GridConnection Transmission line
enerGIS‘10, 23 September 2010
15
Small Hydropower – GIS VI/VI ite:45
Legend #
PowerStatio
!
DischargePo AbstractionP
")
HeadPond Headrace P Headrace C Headrace Tu Penstock Tailrace
45
Dam Reservoir
1.25
0
±
Kilometers
Reserved flo
44
d
GridConnec Transmissio
19.10.2010
enerGIS‘10, 23 September 2010
Hydrology I/V Observation Stations Mean Run-Off Catchment Catchment Characteristics Flow Duration Curve Estimation Accuracy Cross-Check
19.10.2010
16
enerGIS‘10, 23 September 2010
17
Hydrology II/V Hydrological observation stations Location of observation stations
Base Information Localization of Observation Stations 4 5
91
86
51 49 52
85
94 72
No data available
79
81
84
Data collected (see annex)
X
3
Name of Station and River 92
X
Catchement of hydrological observation stations
53
93
Run-Off Data
59
65 64
75
38
Catchment
32
40
23
29
36
22
35
43
45
26 27 44
12
13 19 18 20
6
19.10.2010
enerGIS‘10, 23 September 2010
18
Hydrology III/V Characteristics of catchment 3
Size
4
91
5
79
Mean Altitude / Slope 81
92
84
85
51 49 52
86
Altitude Classes (Rain, Rain / Snow, Snow / Glacier) 94 72
75
53
93
65
59
64
Glacier Coverage
40 43
45
38
32 29
36
22
26 27 44
12
13
19 18 20
6
19.10.2010
23
35
enerGIS‘10, 23 September 2010
19
Hydrology IV/V Summary Report for each Hydro Observation Station Catchment Characteristics Run-Off Graphs
19.10.2010
enerGIS‘10, 23 September 2010
20
Hydrology V/V Classified Discharge
35
Monthly mean
30 25 Monthly mean
Monthly maximum
25
Monthly max
20
Monthly min
Monhthly minimum
m3/s
20 Max. /Minimum value recorded [m3/s]:
m3/s
15
15 10
10
5 5
0
0
Jan
1
Feb
2
March 3
April 4
May 5
Jun 6
Month Month
19.10.2010
Jul 7
Aug 8
Sept 9
Oct
10
Nov
11
Dec
12
enerGIS‘10, 23 September 2010
21
Precipitation I/I Observation Stations Mean precipitation per Observation Station Accuracy estimation Cross-Check
19.10.2010
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22
Electrical Grid I/II Digitized from schematic layouts
!
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Substations
!
Voltage in kV
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Transmission Lines (High Voltage, Medium Voltage)
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220
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110/35/10
Oblast Boundary
!
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!!
110/10 to 110/35/10
!
!!!
! !! !
! !! ! ! ! ! !! ! !
110/10
!
National Boundary
!
!
35/10
Transmission Line
!
!!
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35/0,4
!
! ! !
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!%
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19.10.2010
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Partly uplink of SSHP
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/
Existing Power Stations Substation, Transformers
Legend
! !
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!!! !
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!!
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0
35
70
140 Kilometers
!
enerGIS‘10, 23 September 2010
23
Electrical Grid II/II
!
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!! ! !
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25!
! !! !
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24
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16
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! 19.10.2010
enerGIS‘10, 23 September 2010
24
Protected Areas I/I Aktosh Aktosh
7
Source of Information
8
6
Digitized from different Sources
9
12 10 11
Kusavlin
Zaravshon
4
5
Difficult to obtain 2
13 Sayvatin 14
1
41 40 39
37
3
38
Pamir
Kamarob
Sites and Infrastructure within Protected Areas rated with care Iskanderkul
35
43
36
45 Romit 44
Shirkentskyi
Almosi
19
Nurek
Sarihissor
42
15
18
Childukhtaron
46
Sangvor Tajik National Park
34
Muzkol
28
33 29
27
20 25
17
26 24 23
21
22 31 Dashtijum
16 Dashtijum Karatau
Zorkul
30
Tigrovaya Balka
32
19.10.2010
!
enerGIS‘10, 23 September 2010
25
Geoprocessing and –analysis I/III Geoprocessing
Geoanalysis
Compilation of Base Maps
Catchment Characteristics (Altitude, Slope, Aspect, Glacier Coverage)
Derivation of Catchments of Hydropower Station and Hydro Observation Station
Local Benefit Run Off and Precipitation
¾ Python scripting
19.10.2010
enerGIS‘10, 23 September 2010
Geoprocessing and –analysis II/III Example Characteristics of Catchments Geometry and Size of Catchment Mean Altitude Glacier Coverage Classification of Altitude
19.10.2010
26
enerGIS‘10, 23 September 2010
27
Geoprocessing and –analysis III/III Example Local Benefit Amount of beneficiaries around Grid uplink 10 kV
Beneficiary Radius: < 1 MW -> 15km 1 – 10 MW -> 20km 10 – 30 MW -> 40km
10 kV
19.10.2010
enerGIS‘10, 23 September 2010
Limitations of GIS I/III Difficult available Data (analog data, …) Uncertain ownership of Data (Government, Ministry, Committee, Agency, Private, …) Legislation and State Secrecy of the Republic of Tajikistan Limitation in Spatial Resolution / Scale Not updated Base Information (Maps, …) / Temporal Resolution Location of SSHP sites not suitable for GIS analysis (Irrigation channels, …)
19.10.2010
28
enerGIS‘10, 23 September 2010
29
Limitations of GIS II/III Site:26
Example Location of SSHP sites on Irrigation channels Difficult to locate Catchment is not driven by topography Run-Off is not driven by hydrological regime 26
Available DEM are not detailed enough to represent the topography
Legend # !
PowerStation DischargePoint AbstractionPoint
")
HeadPond Headrace Pipe Headrace Channel Headrace Tunnel Penstock Tailrace Dam Reservoir
0.250.125 0
±
Kilometers
Reserved flow segmen
d
GridConnection Transmission line
19.10.2010
enerGIS‘10, 23 September 2010
Limitations of GIS III/III Example State Secrecy Top maps with scales 1:25 000 – 1:100 000 are secret information Top maps with scale 1:200 000 only for internal use Satellite images only for areas < 20 km2
19.10.2010
30
enerGIS‘10, 23 September 2010
31
Evaluation Matrix I/III Rating of all Sites based on the Information in the DB and GIS Hydrology and Resulting Power Construction Geology Environmental and Social Impact Main Grid Risk Other Investor Risks ¾Transparent assessment and ranking
10/19/2010
enerGIS‘10, 23 September 2010
32
Evaluation Matrix I/III
n ⎛∑ ⎜ ∑ j =1 ⎝ i =1 m
f p i j 10/19/2010
f
⎞ ⎟ i⎠ j
p
j
Factor derived from DB and / or GIS Weight per Group of factors Number of Factors Number of Groups of Factors
enerGIS‘10, 23 September 2010
33
Evaluation Matrix III/III Final Result Total amount of points per site Ranking of all sites
10/19/2010
enerGIS‘10, 23 September 2010
GIS approach – What for / Benefits Goals Optimization of resource harnessing Watershed management optimization Synergies and conflicts Quality and efficiency Tools Exchange of information between experts Common database between different projects Planning tool Public accessible information 10/19/2010
34
enerGIS‘10, 23 September 2010
19.10.2010
35
Agenda
Flächendeckende GIS-gestützte Identifikation potentieller Standorte von Kleinwasserkraftwerken
1. 2. 3. 4. 5. 6. 7. 8. 9.
Entnahme Rückgabe
Ausgangslage Ziele Datengrundlage Methodik Potentialstudie Kanton Bern Standortanalyse sol-E suisse Probleme und Restriktionen Weitere Arbeiten Fazit
Dipl. Ing. Yvo Weidmann, WaterGisWeb AG, Bern WaterGisWeb AG Donnerbühlweg 41 CH-3012 Bern
Tel. 031 / 305 18 11 Fax 031 305 18 14
www.watergisweb.ch
[email protected]
Ausgangslage Verschiedenste Anforderungen an die Energieversorgung der Schweiz • Klimaproblematik / CO2 Ausstoss • Energieversorgung • Sozialer und politischer Druck für die Förderung von erneuerbaren, dezentralen Energie • Revision Stromversorgungsgesetz (StromVG) und Energiegesetz (EnG) -> 5400 GWh bis 2030 aus erneuerbaren Energien • Einführung der Kostendeckenden Einspeisevergütung (KEV) durch den Bund -> Anfrage von Energieversorger (sol-E suisse) und Kanton (Bern) für die Erstellung einer flächendeckenden Analyse an die WaterGisWeb AG
Ziele Unterschiedliche Zielsetzungen bei der Durchführung einer Potentialstudie bei Energieversorger und Behörden Energieversorger
Behörden Wissen über hydroelektrisches Potential
Vorevaluation möglicher Kraftwerksstandorte
Grundlagen für politische Entscheide
Ausweisen spezifischer Kraftwerksleistungen
Hilfsmittel für Bewilligungsverfahren
Erkennen attraktiver Regionen für Neubauten
Gesamtübersicht über hydroelektrisches Potential
Begriffe
Datengrundlage
Einige Begriffsdefinitionen
Erforderliche Geodaten sind beim Bund und bei den Kantonen in ausreichender Güte vorhanden
Kleinwasserkraftwerk
Bis 10 MW Leistung (mittlerer Haushalt ca. 1 kW)
Theoretisches Potential
Basierend auf Gelände und Abfluss berechnetes Energiepotential
Genutztes Potential
Bereits durch Konzessionen aus einem Gewässerabschnitt bezogene Energiemenge
Ausgeschlossenes Potential
Energiemenge, welche durch kantonale und eidgenössische Verordnungen nicht genutzt werden darf
•
Limitiertes Potential
Energiemenge, welche durch kantonale und eidgenössische Verordnungen nur in Grenzen genutzt werden darf
•
Unbeeinflusstes Potential
Aus vollzugstechnischer Sicht nutzbare Energie
Geodatenbank
• • •
Mittlere monatliche Abflüsse (MQ-CH) Digitale Gewässernetze (GWN25, GN5) Digitale Höhenmodelle (DHM25, DHM25_10) Beeinflussende Faktoren (Auen, Hochmoore, Grundwasserschutz, Amphibien, …) Bestehende Kraftnutzung (Konzessionierte Restwasserstrecken)
Abfluss Zeit
Grundwasser Tourismus Naturschutz
MQ-CH Rasterdatensatz der mittleren jährlichen und mittleren monatlichen Abflüsse über die ganze Schweiz
MQ-CH Abschätzung der Genauigkeit der mittleren monatlichen Abflüssen basierend auf einzelnen Regimetypen
Periode 1981 – 2000 Fusion zweier Datensätze unterschiedlicher Auflösung Validierung mit realen Abflüssen Quelle: BAFU und WSL, 2006: Rasterdatensatz mittlere Abflüsse der Schweiz für die Periode 1981-2000
MQ-CH Natürliche Variabilität des Abflusses ist z.T. grösser als der Schätzfehler der modellierten mittleren Abflüssen
Quelle: BAFU und WSL, 2006: Rasterdatensatz mittlere Abflüsse der Schweiz für die Periode 1981-2000
Einflussfaktoren Schutzgebiete können die Kraftnutzung in einem Gewässer einschränken, resp. verhindern. Verhinderung Einschränkung (Killerfaktoren) (Einflussfaktoren)
Quelle: BAFU und WSL, 2006: Rasterdatensatz mittlere Abflüsse der Schweiz für die Periode 1981-2000
Bestehende Kraftnutzung Gewässerabschnitte mit bestehenden Wasserkraftkonzessionen können nicht mehrfach genutzt werden. Bestehende Konzessionsmengen geben Aufschluss über den Ausnutzungsgrad des theoretischen Potentials.
Unterschiedliche DatenWasserkraftrechtlichRestwasserkarte (schweizweit) relevanten Objekte lage zwischen Bund (Kanton Bern) Und Kantone
Methodik Berechnen geographischer und hydrologischer Kennwerte für diskrete Gewässerpunkte • Diskrete Gewässerpunkte festlegen • Räumliche Entsprechung der Abflusslinie im DHM25 suchen • Einzugsgebiet und Abfluss ermitteln • Kennwerte speichern
Abfluss Zeit
Abfluss 876.8
Zeit
882.4
869.3
Abfluss
870.7
863.1
Zeit
863
854.1 859.7
848.8
841.8
m 50 m 50 m 50
844.6
836.1
836.5 833.6 832
834.5 825.5
838.8 842.2 847.5
829.4 864.3
825.2
818.9 819
876.4 839.7
Methodik
Methodik
Das digitalisierte Gewässernetz und die Abflusslinie eines Höhenmodells stimmen nicht überein.
Zwischen Abflusslinie und digitalisiertem Gewässernetz muss eine Zuweisung der Geometrien vorgenommen werden. Quelle
Berechnung von Einzugsgebieten auf Gewässernetz führt zu Fehler
Festlegen von Quelle und Mündung Mündung
Herleitung von Abflusslinie aus Höhenmodell
NetzwerkRouting
Berechnung von Einzugsgebieten auf Abflusslinie
Speichern der Zuordnungen
Methodik
Methodik
Das Gewässernetz wird in diskrete Punkte aufgeteilt. Zu jedem Punkt auf dem Gewässernetz wird der korrespondierende Punkt auf der Abflusslinie ermittelt.
Korrespondierende Punkte auf Abflusslinie
Bestimmung der monatlichen und des jährlichen Abflusses für jedes Einzugsgebiet
Speicherung der beiden Koordinaten (2D und 2.5D)
Methodik
Software Verwendung von ArcGIS als Framework.
Ermittlung des hydroelektrischen Potentials über die Abflussmenge, Erdbeschleunigung und Fallhöhe. Abfluss Zeit
P = ρ · g · Q · Δh · η Leistung [kg · m2 / s3], [W] Dichte [kg / m3] Erdbeschleunigung [m / s2] Abfluss [m3 / s] Fallhöhe [m] Wirkungsgrad
Für jeden Gewässerpunkt wird das Einzugsgebiet und die modellierten Abflüsse (monatlich, jährlich) bestimmt. Bestimmung der Einzugsgebiete für alle Punkte
Punkte auf Gewässernetz
P ρ g Q Δh η
?
Programmierung von spezifischen Tools für die Berechnungen: ¾ ca. 15 Tools ¾ ca. 30‘000 Zeilen Code
Δh
ΔL
Speicherung
Standortanalyse vs. Potentialstudie
Sämtliche berechneten Daten werden in einer relationalen Datenbank gespeichert und stehen für die weiteren Auswertungen zu Verfügung. Gewässer
Energieversorger (sol-E suisse)
Gewässerpunkt
Rangierung von möglichen Anlagen
Inventar in unterschiedlichen Massstabsbereichen
Berücksichtigung von Restwasser, Wirkungsgrad und techn. Limitierungen -> wirtschaftliches Potential
Fluss- und Gebietsbasierte Auswertung mit potentieller Leistung pro 1000m Gewässerlänge
Potentialstudie Kanton Bern
Potentialstudie Kanton Bern Basierend auf der Länge der Restwasserstrecke: 200 m Konzessionierte Leistung: 350 kW Information von Spezifische Leistung: 350 kW / 200 m = 1.75 kW/m Restwasserstrecken wird die konzessionierte Nutzung pro GewässerPunkt ermittelt.
Ermittlung von StandortFaktoren an jedem Gewässerpunkt mittels geografischem Verschnitt Aufteilung in Einflussklassen • Einflussfaktoren • Killerfaktoren • Bestehende Kraftnutzung
m
Einflussfaktoren
Abfluss
50
Abschnittsleistung
Einzugsgebiet
Information zu theoretischem, genutztem, möglichem und ausgeschlossenem Potential
m
Gewässerpunkt
Hinweiskarte möglicher Standorte von Kleinwasserkraftwerken
0
Gewässer
Potentiale
m
Potential pro Gewässerpunkt
20
Potential pro Gewässer
Behörden (Kanton Bern)
75
Potential pro Gewässersystem
Unterschiedliche Auswertung der Resultate je nach Zielsetzung der Studie
75
m
Leistung: 1.75 kW/m * 50 m = 87.5 kW Leistung: 1.75 kW/m * 75 m = 131.25 kW
Leistung: 1.75 kW/m * 75 m = 131.25 kW
Grundwasser Berechnete Punkte
DB
Nicht berechnete Punkte
BLN
Gewässer Restwasserstrecke
Naturschutz
Relevanzlänge
Potentialstudie Kanton Bern Das theoretische Potential wird in 4 Klassen aufgeteilt:
1
Potentialstudie Kanton Bern 13
Darstellung der Resultate in zwei Kartenmassstäbe:
12
Gewässerpunkt Gewässer
11
Restwasserstrecke (Kraftnutzung)
¾ Detailkarte 1:25‘000 ¾ Übersichtkarte 1:100‘000
10
Killerfaktor 9
Einflussfaktor 8
¾ ¾ ¾ ¾
7
Genutzt Ausgeschlossen Limitiert Unbeeinflusst
5
1187
6
4 3 2 1
1 Potential [kW] Theoretisch Genutzt Verfügbar Killerfaktor Nutzbar Einflussfaktor Unbeeinflusst
3
4
5
140 125
2
95
70
90
140 125
95
70 70 0
90 90 0
140 125 125 140 0
95 95 0
0
0
Gewässerpunkt 6 7 8 100 120 40 100 80 100 100
80 80
75 40 35 35 35
Blatt Süd
Münsingen 9
10
11
12
13
80 40 40
90 40 50 50 0 0 0
105
75
60
105
75
60
40 40 0
105 105 0
75 75
60 60
Summe 1225 160 1065 210 855 365 490
Wa s s e r k r a f t Po t e n zi a l s t u d i e K ant on Bern
Wa s s e r k ra ft Po t e n zi a l s t u d i e K a n t o n B e rn
1087 1105 1106
1107 1108
1124 1125 1126
1127 1128
1144 1145 1146
1147 1148
1:25 000
Ausgabe 2009
Ausgabe 2009
1165 1166
1167 1168 1169
1185 1186
1187 1188 1189
1206
1207 1208 1209
1210 1211
1226
1227 1228 1229
1230 1231
1245 1246
1247 1248 1249
1250
1265 1266
1267 1268
1285 1286
1:100 000
Blatt Nord
Blatt Süd
A WA Amt für Wasser und Abfall Bau-, Verkehrs- und Energiedirektion des Kantons Bern
A WA Amt für Wasser und Abfall Bau-, Verkehrs- und Energiedirektion des Kantons Bern
Potentialstudie Kanton Bern
Potentialstudie Kanton Bern
Detailkarte 1:25‘000
Übersichtkarte 1:100‘000
Standortanalyse sol-E suisse
Standortanalyse sol-E suisse
Berechnung von möglichen Kraftwerksstandorten in 3 Leistungsklassen: ¾ 0.25 MW, 0.5 MW und 1.0 MW
Für die Berechnung von möglichen Standorten wurde die Abflusswerte Q120 verwendet. Bestimmung der Jahresganglinie
Berücksichtigung technischen, ökologischen und ökonomischen Limitierungen: ¾ Wirkungsgrad (η = 0.7) ¾ Restwassermenge (Q120) ¾ Maximale Länge Ausleitstrecke (Leistungsabhängig) ¾ Berücksichtigung der Abflussvariabilität (Q120 ± 20%)
160
140 140
60 60 40 40 20
21 J u 0 li: Au 24 gus S e 0 t: p Q tem 27 be 0 r: O Q kto 30 be 0 r: N ov Q em 33 be De 0 r: z Q em 36 be 0 r: Q
1 8 J un 0 i:
Q
Mit der Berücksichtigung der Abflussvariabilität (Q120 ± 20%) kann die Robustheit der Standorte eruiert werden.
Q120 AEZG = 26 km2 Q120 = 1200 l/s
Δh
Leistung [kg · m2 / s3], [W] Dichte [kg / m3] Erdbeschleunigung [m / s2] Mind. Abfluss an 120 Tagen im Jahr [m3 / s] Fallhöhe [m] Wirkungsgrad
15 M a 0 i:
Standortanalyse sol-E suisse
Berechnung der für die gewünschte Leistung benötigten Fallhöhe.
P ρ g Q120 Δh η
Q
Jahresgang Dauerkurve
Standortanalyse sol-E suisse
P = ρ · g · Q120 · Δh · η Δh = P / (ρ · g · Q120 · η)
Q
0
12 Apr 0 il:
20 0
J Q anu 30 a r : Fe Q br u 60 ar :
Darstellung der Resultate: ¾ Hinweiskarten 1:25‘000 ¾ GoogleEarth
80 80
Q Mä 90 rz :
Wahl des Wertes Q120
100 100
Q
Sortierung der Abflüsse
Abfluss Abfluss [l/s] [l/s]
120 120
ΔL
P = 500 kW
Standort detektiert bei: • Q120 + 20% • Q120 • Q120 - 20%
Standortanalyse sol-E suisse Darstellung der berechneten möglichen Standorte in Hinweiskarten.
Standortanalyse sol-E suisse Hinweiskarte 1:25‘000
Entnahmestelle Konzessionsstrecken mit Schlüsselwerte
Restwasserkarte Schutzgebiete Karst
Probleme und Restriktionen
Probleme und Restriktionen
Falsche Übereinstimmung der Tallinie und digitalisiertem Gewässernetz
Anthropogen überprägte Regionen erschweren die korrekte Berechnung von Einzugsgebieten
Regionen mit schwachem Relief
Kanäle und Druckleitungen
Karstregionen
Drainagen
Veränderte Gewässerläufe
Umleitungen
Nicht analysierte Gewässerpunkte
Probleme und Restriktionen Regionen mit (Pump-) Speicherkraftwerke besitzen veränderte hydrologische Regimes Berücksichtigung Von Zu- und Ableitungen Speicherbetrieb verändert AbflussCharakteristik eines Gebietes
Abflusslinie des generischen Gewässers
Digitalisiertes Gewässer
Weitere Arbeiten Aktuell werden weitere Projekte bearbeitet. Dabei werden verschiedenste Software- und Methodikverbeserungen vorgenommen. BFE – Forschungsprojekt (Erhebung des Kleinwasserkraftpotentials der Schweiz): ¾ Zusammenarbeit mit Geografischem Institut der Universität Bern (PhD-Thesis) ¾ Gesamtheitliche Beurteilung der Nutzung von Gewässer durch Kleinwasserkraftwerke
Weitere Arbeiten Swiss Mountain Water Award: ¾ Berechnung möglicher Standorte schweizweit ¾ Web – Portal für die Publikation der Standorte GEWISS – Web: ¾ Berechnete Einzugsgebiete werden für Web-basiertes Gewässerinformationssystem weiterverwendet ¾ Berücksichtigung der Bodenbedeckung pro Einzugsgebiet ¾ Weitere hydrologische Parameter Ausland: ¾ Abklärung für die mögliche Portierung der Methodik ins nahe und weitere Ausland
Schluss
Vielen Dank für Ihre Aufmerksamkeit! Fragen?
Fazit Potentialstudie Kanton Bern: ¾ Flächendeckende Studie mit grosser Aussagekraft ¾ Datensatz für weitere Analysen ¾ Kartografische Darstellung verschiedenster Parameter ¾ Werkzeug für Planer und Behörde Standortanalyse sol-E suisse: ¾ Erarbeitung der Methodik mit Industriepartner ¾ Praxiserprobte Methodik ¾ Problemorientierte Darstellung ¾ Prüfung der Resultate im Feld
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