ERRAGMap: Visualization Tool

ERRAGMap: Visualization Tool Saira Gillani

Sheneela Naz

Center of Research in Networks & Telecom (CoReNeT)

Center of Research in Networks & Telecom (CoReNeT)

M. A. Jinnah University

M. A. Jinnah University

Islamabad, Pakistan

Islamabad, Pakistan

[email protected]

[email protected]

Muhammad Naeem

Muhammad Tanvir Afzal

Center of Excellence in Data Mining

Distributed & Semantic Computing

M. A. Jinnah University

M. A. Jinnah University

Islamabad, Pakistan

Islamabad, Pakistan

[email protected]

[email protected]

AmirQayyum Center of Research in Networks & Telecom (CoReNeT) M. A. Jinnah University Islamabad, Pakistan [email protected]

Abstract-

Earthquakes

are

considered

one

of

the

major

I.

disastrous situations for any nation. The horrible earthquake may

claim

hundreds

of

lives,

thousands

of

injuries

and

An

demolishing thousands of houses. When an earthquake hits a non-government

organizations

(NGOs»

deadly

earthquake

Saturday morning October 8, 2005.

nation then number of management bodies (such as: government organizations,

anomalous

INTRODUCTION

struck

Pakistan

on

Beautiful hilly areas of

Azad Kashmir, northern and northeastern territory of Pakistan

are

were completely altered due to this earthquake. This was the

actively involved in reinstating the damages. Generally, these and still-to-be build

strongest earthquake in the area during the last hundred and

infrastructure (roads, buildings, and houses etc). Currently, this

fifty years. This horrible earthquake claimed 73,338 lives, a

organizations deal with

stats of build

information is presented to the organizations as a raw text in

large

huge amount. Therefore, it becomes difficult to highlight key

number

annihilate

areas where an immediate start of rehabilitation process is

of

more

injuries than

figuring

600

69,412

thousand

people

houses.

while

Pakistan

government established a new authoritative organization,

inevitable. In the past, some systems have been developed to present such information in structured form by using some

Earthquake

visualization techniques. However, these tools are inadequate

(ERRA) on October 24, 2005. The authority was given a

because of the following reasons:

1)

Most of these tools are about

target

geotechnical conditions of effected area and can provide help to describe

seismic

hazards

2)

Some

earthquakes in specific region. the

rehabilitation

process

3).

in

systems

show

trends

of

None of the systems describe an

easily

conceivable

Reconstruction

for

relief,

Rehabilitation

reconstruction

partially

and

or

earthquake.

One task of ERRA is to find donor

damaged

agencies

buildings

to work

Authority

rehabilitation

annihilated international

way.

and

out

affected partner

for

of by like

assistance

Therefore, this becomes an interesting and challenging research

purposes. So for this purpose, ERRA published their review

problem to build such a system that can overcome the above

reports on their web site in tabular form for electronic access

mentioned limitations of current techniques and systems. In this

to

research, we present such a system called ERRAGMAP. This geo

providing a non-programming environment for exploratory

spatial tool discovers and presents deep insight into the data related

to

rehabilitation

of

the

destroyed

houses

in

1)

2)

develop

and

evaluate

an

reports

of

progress

of

ERRA,

This way of presenting information is quite

rehabilitation process is inevitable.

propose and develop a

Research community is agreed on this fact in general that

3)

tabular data is not impressive enough to elaborate proper

visualization

visual illustration according to user perception while imposing

framework for converting raw data into actionable knowledge, propose,

tabular

inadequate to highlight key areas where an immediate start of

critical analysis of existing tools of visualization for

earthquake rehabilitation systems

but

data analysis.

the

earthquake affected areas. Our contributions in this research are as follows:

everyone

innovative

technique.

cognitive sense. Such impotency of tabular data has motivated

Keywords- Earthquake, geographical visualization

researchers

to

techniques.

Knowledge

attention

with

management. technologies

736

move the

towards

increase

Visualization can

be

knowledge

visualization

used

in tools

to

has

interest along

integrate

visualization

received in

more

knowledge

with

recent

knowledge

and

information visualizations. Numbers and objects represented

automatically this change will update in our designed map and

in a two dimensional map become difficult to analyze with the

chart.

increase in volumes of data. This also poses limitations on

The remaining paper is organized as follows. Section 2

human visual and cognitive processing sense. Therefore

presents related visual information proposed techniques about

reliable and flexible data analysis tools are required to fmd

earthquakes, and system architecture of proposed visualization

hidden patterns and trends lurking in huge volume of data.

technique is defmed in Section 3. Visualization system is

Conventional 2D map plotting techniques are found inefficient

proposed in Section 4. In Section 5 we have illustrated our

to present vital information hidden within the data. Therefore,

results with discussion followed by Section 5 in which we

interactive visualization tools incremented with visual clues

gave our concluding remarks and future direction.

are found useful to extract intuitive meaning of the data. Here

II.

the intention is to give priority to visualize information to users over irrelevant information

There is variety of ways to visually present any type of

The effects of Earthquake and aftershocks in Japan have

data. In the following decades a large number of complex and

been shown through different visualization techniques such as

detailed

time lapse visualization and Google Earth etc. Time lapse

etc using

activities in Japan. The magnitude of each quake is presented

between two locations. This tool visualizes the movement just

plots the colored bubbles that represent when the earthquake

like

occurred, size of the bubble represents the size of the earthquake and ridges in water is the pacific ring of fire ridge.

Earthquake represent

Therefore, there is a need to develop a system that can map

technical characteristics of these implications using these service

and

some

visually

such

as

present

different

Earthquake

information about

Location,

LocationMaps,

[10] presented the visualization of seismic data that consider both small magnitude events and large earthquakes for remote

known examples for this [14]. A highly related technology of

analysis.

these APIs known as Google earth provides rich globe­

Authors [11] have shown the working of concept maps

viewing features, road, terrain, street views etc. In addition,

through

the paper demonstrates how SAS real-time processes can be

CmapTools

software.

They

have

shown

that

repositories of information can be organized to become easily

used to drive map overlays (heat map) and map markers.

brows able by using concept map based knowledge models.

As this paper focuses on destruction information about

Searching algorithms for the web can also be improved by

earthquake of October 2005 with geographical position, the

using concept maps. They have also explained that how

proposed visualization system has a capability of visualizing

knowledge models can be complemented by the available

visualization

information

technique has been proposed and implemented, motivated

that

also

help

to

improve

the

process

of

constructing concept maps.

see

Eiman et al. [6] presents the MobGeoSens which is an

information about total destruction in different areas of with

map

ShakeMap, Google Earth KML, aftershock Map. Dave at el.

Maps, Google Ride Finder, and Google Transit are well

equipped

which

earthquake

non-commercial basis. Many map-based services, Google

also

the

deaths during the japans' earthquake. There are number of maps

application technology which is freely provided by Google on

is

Map etc. Few of them on

the map. Peter et al. [5] also displayed the information about

maps. We have used Google Maps which were formerly

system

location

Earth. This visualization displays the earthquake location on

integration into earthquake data. We have elaborated the

The

aftershock

earthquake data through the visualization tools such as Google

demonstrates a way of accessing publicly available maps with

Pakistan.

Location, earthquake

specific areas. Greg Sterling [4] was visually representing

and altitude comparison in one glance. This paper also

can

and

visualization tools display the total number of deaths in

and divide geographical locations and geographical terrain,

anyone

visualization

Many different techniques for analyzing earthquake data or

earthquake size data according to the countries. There is some

chart

The

disaster data have been developed such as Google Earth,

limitation in existing visualization.

this

people.

disasters.

with the black circle size. Individual bars are presenting

Through

and

exploration of most affected areas due to earthquake or

as USA, China, Japan etc. it showed the earthquake statistics

chart.

traffic

active research area. So, not much has been written on the

last 60 years (since 1952 to 2011) in different countries such

donet

network

exploration of earthquake data or disaster data is also a very

Another visualization [13] plot the largest earthquake over the

from

visualization tools like Web Trend Map, Google

another visualization tool that shows the interaction or flowing

it display the total earthquakes. This visualization technique

innovative

visualize

colors which identify the global regions. JFlowMap [1] is also

activity around the world. If zoom any country e.g. Japan then

an

that

latency and traffic density information is presented through

visualization technique uses Google Earth that plot earthquake

Furthermore

proposed

internet traffic information on the world map. Network attack,

just selected one day seismic activities on map. The other

map.

are

Akami Web Real-time Monitor tool [9] shows the real time

different colored small circles. It visualizes all of the days or

Google

tools

Maps, TwittEarth, Akami Web Real-time Monitor.

on the map with a circle and quake depth is presented with

as Google Local. It is a web mapping

visualization

following types of data such as earthquake, disaster, and flood

visualization map is a technique that shows all of the seismic

known

RELATED VISUAL TECHNIQUES

environmental sensing toolkit using mobile sensing devices.

real-time

MobGeoSens

information. If we make any change in our database then

monitored

the

local

environment

such

as

variation in pollution throughout the journey which is visually

737

Google Earth tool for presenting the multifaceted spatio-

presented using Google Earth. Jo et al. [7] also used the

Dataset

i Figure. 1. System Architecture of ErraGMap

temporal datasets. Another research shows the Affymetrix

steps, this step consumed most of the time. In geographical

exon arrays data using the GoogleMap [8]. Boyandin et al. [2]

mapping step, hierarchy of dataset was defined and declared.

[3] used JFlowMap visualization tool. This tool presents

We have defmed three levels of hierarchy. The top level of the

UNHCR Refugee Dataset.

hierarchy was comprised of country followed by provincial

Visual analysis is also performed on time dependent data

territory level. The last level was limited to sub district or

which is used in many applications. Christian et al [II]

tehsil.

spatio­

We restricted to only tehsil level although in Pakistan more

temporal data using maps. This approach hides the information

administrative level branching exist. However including these

and visualizes 3D information. This visualization approach

sub branches may cause confusion on the map due to limited space on web page. The next modular dataset namely processed dataset constituted of tabular formatted dataset. This dataset was made available at electronic spreadsheet for cross verification and examination. The last two modules collectively represent the output of the system. Visual representation is depicted by using Google maps in which

presents

the

visualization

tool

which

visualizes

used the icons of 3D pencil and helix for the presentation of time dependent attributes on maps. It

also

considered

the

characteristics

of

underlying

temporal dependencies such as linear or cyclic time. This technique

visually

guide

users'

attention

to

relevant

information and hide irrelevant details.

technique is depicted in figure 1. We have divided this

Google API based control was used. The doughnut chart is merely a pie chart except a hole inside it. It is assumed that bar chart is the most ubiquitous chart among different available graph charting systems. However bar chart has limitations in displaying true visualization impact for some particular datasets. Keeping in view of this limitation, we adopted a robust visualization display in charts. Pie chart or doughnut delivers better visual results in our case. The doughnut chart was divided into three layers. Each layer was further spliced into segments. In this way, doughnut can exemplify various layers of tabular dataset. Another reason for using three layers

architecture

was that a single layer of doughnut can represent data

Zhicheng et al [12] presented the human mental models through the visualization technique. This paper intended and instanced a particular form of internal representation and mental models. The association between mental models and external visualizations is presented through this visualization technique. III. The

underlying into

USING THE TEMPLATE

driving various

mechanism modular

for

our

components

proposed including

effectively when share of each splice ranges from 25% to 50%.

dataset repository, data preprocessing, standard icon web pages,

geographical

mapping,

processed

tabular

dataset,

visualization of dataset into Google map and its graphical

IV.

representation in form of doughnut. We shall briefly describe

ERRAGMAP: VISUALIZATION TOOL

Based on the literature review investigated so far, we can

each of them: The first and foremost module 'Dataset' is

conclude that geographical information has been portrayed for

composed of raw text dataset files. In preprocessing step, we

volcanic enrapture data and refugee data. As far as earthquake

remove missing, erroneous and duplicate records. Some minor

data visualization is concerned, some Japanese earthquake

corrections were also made during this step. Among all of the

simulation has been provided with visual representation.

738

However, in Pakistan which is unluckily suffering from natural as well as manmade disasters from last decade, there was a dire need to portray horrible earthquake disaster, occurring in Pakistan's northern territories claiming half a million of citizens. For a poor country like Pakistan this disaster imposed numerous threats shattering whole of the social and economical structure. Therefore there is a need to provide help to public and private sector organization to

•

Abbottabad

•

Bagh

•

Batagram

•

Kohistan

•

Mansehra

properly visualize the most and less affected areas with

•

Muzaffarabad

consolidated reports. Statistical data is usually lacking the

•

Neelum

•

Shang."

appealing characteristic by virtue of its layout but visualization

Sudhn oti

tools can equip the end use of the data to give a deeper insight. Our proposed tool is a serious effort in this way. ..... :, , ...., j ,...1

Ie! .

I!I BEllS III

--!-

I

ItytIIICI

I

Figure. 3. Slices show total number of destroyed houses, partially damaged and negligible damaged houses.

S

. --

v.

RESULTS

& DISCUSSION

We have implemented Google map control system in Microsoft C sharp. Google Map web GUI control was obtained from Microsoft official web site. The dataset was taken from ERRA Figure. 2. ERRA GMap

preprocessing. Data pre-processing is usually neglected though it plays a critical role in any technique including data mining

Figure 2 is illustrating a graphical output of the tool. It is

and visualization. Data preparation and filtering steps are

evident from this view that the helping agency can quickly

tedious and cumbersome jobs consuming much of the time

observe the most effected and less effected areas. This

involved in development of any framework for visualization

visualization can provide us an inference of the area including

purposes. This step is collectively comprised of data cleaning,

tehsils Plass, Pattan, and Dasu of district Kohistan and tehsil

data normalization, data transformation, feature extraction and

Alpuri and Puran of district Shangla has not received much

selection, etc. Butler et aI., [10] coined a phrase "Garbage In

attention and they are still in need to get more focus in the

Garbage Out" which can be believed to be considerably

domain of reconstruction of damaged houses. On the other

applicable to our huge volume of data. The first phase of data

hand tehsil blab in Kashmir territory has been provided with a

preprocessing are the methods related to data gathering. Data

comparatively better aid. The other benefit of this tool is that

gathering methods are not tightly controlled methods by virtue

the tool represents the geographic landscape information regarding

height,

terrain

area

in

[10] official web site. The first and

foremost task related to our visualization framework was

connection

to

of their design. This may lead to generation of out-of-range

the

values as well as some invalid data including missing values.

rehabilitation efforts. For example Muzaffarabad is hillier area

Analysis of such data can yield undesired or fabricated results.

as compared to blab so this make sense that NGOs are facing

Thus in order to achieve a correct analysis, we have screened

more problem in providing access to these uneven surface

out all of the missing values, and invalid scores in order to

areas. This tool can give them information in prior to

improve data quality. The output of this step is a fine grained

implement their operational activity. Roads accessibility is a

high quality data which is quite suitable for the visualization

good example in this context.

purposes. Table I and Table 2 are representing the dataset for earthquake (2005) at Kashmir and north western frontier province (now Khyber Pukhtoonkhah). We have chosen only those districts which were highly affected. Each of these districts was further divided into its administrative subunits "Tehsil". The data is represented at tehsil level. Two types of data were selected: number of houses that are completely destroyed and number of partially destroyed houses. The last two columns represent the longitudinal and latitude axis of each of the tehsils. The geographic coordinate data including

739

is related to the past so the visualization quality of being near

longitude and latitude was retrieved from sources including

to the true value relies on the accuracy of original data related

Google map and Yahoo maps.

to natural disaster occurred in October 2005. Geoscientific

Table I. Dataset for Earthquake (2005) for Azad Jammu & Kashmir territory

TrJuil

District

Destroved

PartiaDv

Lon�tude

Bagh

6259

3931

34.48333

73.5

Haveli

12034

1085

34.45335

73.53636

3540

1288

34 .46727

73.5

Bagh

DhirKot

Muzaffarabad

Muzaffarabad

N eclum

Authmuq=

Hattian

Aba35pur Hajira Poonch

Raw alakot

Sudhnoti

Pallandari

data visualization furnishes a vivid environment to develop a

Latitude

5765

3670

34.31367

73.42701

17798

4985

34.36666

73.46666

2894

1085

34.38366

73.47323

2703

933

33.81652

73.97455

11267

1114

33.79613

73.90143

6002

3098

33.84806

73.79916

18275

4115

34.4444

73.444

graphical information exchange channel. Such exchange of information can give help to experts of geosciene domain with creative

Tehsil

Abbottabad

Havelian

Batagram

A1lai

Abbottabad Batagram Kohistan

Palas Pattan Dassu

Mansehra

Ogai Kala Dhaka Mansehra BalaKot

Shangla

A1puri

Province Destroyed Partially 6161 3818 7481 23982 2869 1079 4884 3149 13066 2110 1964 4179 7962 3183 3853 2345 1181 3003 21432 7076 9912 1868 13658 2690

3765

Puran

VI.

2299

Lonoitude 33.9707 34.1209 34.83 34.67839 35.0782 35.11015 35.26654 34.50549 34.44871 34.43319 34.53145 34.90455

Latitude 73.25134 73.21838 73.00648 73.02887 73.09877 73.00852 73.23667 73.03167 72.7746 73.21068 73.35709 72.64247

34.73333

72.68333

the

formation

of

[2]

Ilya Boyandin, Enrico Bertini, Denis Lalanne, "Visualizing the World's Refugee Data with JFlowMap". Poster paper at Eurographics/IEEE Symposium on Visualization 20 10, June 9 - II, Bordeaux, France

[3]

Ilya Boyandin, Enrico Bertini, Denis Lalanne Fig, "Visualizing Migration Flows and their Development in Time: mFlow Maps and Beyond,"

[4]

http://searchengineland.comlvisualize-earthquake-data-in-google-earth13254.

[5]

http://www.newscientist.comlblogs/shortsharpscience/20 1 1/03/interactiv e-graphic-japans-dea.html.

[6]

Kanjo, E., Benford, S., Paxton, M., Chamberlain, A., "MobGeoSen: Facilitating Personal GeoSensor Data Collection and Visualization using Mobile Phones," Personal and Ubiquitous Computing, vol. 12, No. 8, 2008.

[7]

Jo Wood, Jason Dykes, Aidan Slingsby, and Keith Clarke, "Interactive Visual Exploration of a Large Spatio-Temporal Dataset: Reflections on a Geovisualization Mashup," Ieee Transactions on Visualization and Computer Graphics, vol. 13, no. 6, november/december 2007.

[8]

Tim Yates, Michab 1. Okoniewski and Crispin 1. Miller, "X:Map: annotation and visualization of genome structure for Affymetrix exon array analysis," Nucleic Acids Research Advance Access published October 1 1, 2007.

[9]

http://w.ww greenm3.comlgdcblog/20 1 1I2/ 16/akamais-real-time-web­ monitorattacks-traffic-and-latency.htrnl

[l0] D. A. Yuen, B. 1. Kadlec, E. F. Bollig,W. Dzwinel, Z. A. Garbow, and C. R. S. da Silva. Clustering and Visualization of Earthquake Data in a Grid Environment. Visual Geosciences, pages 1- 12, 2005. (pubitemid 462 17982)

earthquake

rehabilitated data. Our overall objective was to discover a way to

extract

information

from

large

geospatial

communication

Ilya Boyandinl, Enrico Bertini2, Peter Bak3 and Denis Lalannel, "Flowstrates: An Approach for Visual Exploration of Temporal Origin­ Destination Data," Eurographics / IEEE Symposium on Visualization 20 1 1 (EuroVis 20 1 1) Volume 30 (20 1 1), Number 3.

CONCLUSION

general approach, underlying technique and methodology for of

information

[I]

We have implemented dynamic simulation of the formation

simulation

the

REFERENCES

of the earthquake rehabilitation data. We have discussed the dynamic

of

promoting knowledge discovery.

Table 2. Dataset for Earthquake (2005) for North Western Frontier

District

recognition

between geoscientific data and the human being's vision

datasets.

[II] A, J Canas, R. Carff, Carvalho, M., M. Arguedas, T. Eskridge, "Concept maps: Integrating knowledge and information visualization". In S.-O.

Therefore, we can conclude that the dynamic simulation and visualization technology using multi dimensional interactive

[ 12] Tergan & T. Keller (Eds.), Knowledge and information visualization: Searching for synergies (pp. 205-219), 2005.

modeling proved to be a reasonable way to illustrate the qualitative and quantitative knowledge.

[ 13] Christian Tominski, Petra Schulze-Wollgast and Heidrun Schumann, "3D Information Visualization for Time Dependent Data on Maps," Ninth International Conference on Information Visualisation (IV'05), 2008.

We can also conclude that it is substantive to recognize the visualization representation of the spatial and temporal data of the constitution and organization of natural disaster suffering

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geographical region. We have efficaciously rearranged and aggregated the existing geographical information to show the relationship underlying the surface. Complete representational,

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