ROUGHNESS LENGTH CLASSIFICATION OF CORINE LAND COVER CLASSES Julieta Silva, Carla Ribeiro, Ricardo Guedes MEGAJOULE - Consultants Rua Eng.º Frederico Ulrich, 2650 4470-605 Maia – Portugal Phone: +351 220 915 480 email:
[email protected] ABSTRACT: It is well know that surface roughness can play a relevant role in the wind flow characteristics and, thus, is a variable that can’t be neglected in flow modelling and resource assessment. Nowadays, like public earth scale orography data, geo-referenced data of land cover is becoming increasingly available for locations around the globe, with relevant detail and accuracy. The European Commission program Corine Land Cover is, perhaps, the first and best example of this progress. The CLC project is producing land use cartography, in the form of detailed descriptions of land occupation and features, for all European countries, with a definition of 25 ha. Corine digital land cover cartography is already available for 33 countries. The authors have studied the different CLC land definitions and proposed a set of corresponding roughness lengths. The classification was based in a broad study of the CLC methodology and roughness length theory found in the European Wind Atlas. The results were tested in three sites located in Mainland Portugal. If limitations are observed, CLC related roughness length scales can be a tool of practical use to wind analysts for European projects, namely in first blind approaches to soil occupation and surface roughness, when it is not possible to perform site visits. In the future the results can be extended, along with the CLC project itself, and can also be transposed to other similar land use cartography on other regions. Keywords: Roughness, Corine Land Cover, Land use, Land coverage
1. INTRODUCTION The correct evaluation of the land cover and characteristic roughness length of a site for wind resource assessment purposes is a hard and time consuming process. Good representations depend on effort of thoroughly inspecting the site’s and surroundings landscape and normally rely on specific site visits. Nonetheless this effort, the process always results somewhat subjective and imprecise, namely for the surrounding landscape. Unlike site’s altitude, which are easy to obtain in digital format and relatively constant with time, land coverage and land use are much more difficult to describe. Information in digital, or even paper, formats are less frequent and less accurate. Even when information is available aspects like, types of trees or crops, tree or house density, types of buildings, among many others, are seldom comprised. The time, resources and costs associated with this approach are clearly unattractive, and the capacity to reproduce results, by lack of uniform and universal roughness maps, is diminished. Not surprisingly, when studying distant and unknown locations, an informed guess is sometimes the only available option. Nowadays, like public earth scale digital information on sites altitude, descriptions of surface occupation are becoming more and more available for several locations around the globe, and with relevant detail and accuracy. The European Commission program Corine Land Cover (CLC) is, perhaps, the first and best example of this progress. One of the major tasks undertaken in the framework of the Corine (COoRdinate INformation on the Environment) programme has been the establishment of a computerised inventory on land cover, which is consistent and comparable across Europe. Corine land cover 2000 (CLC2000) is an update for the reference year 2000 of the first CLC database which was finalised in the early 1990s. It provides consistent information on land cover and land cover changes during the past decade across Europe. The CLC project is producing land use cartography, in the form of detailed descriptions of land occupation and features, at an original scale of 1: 100 000, using 44 Classes of the 3-level Corine nomenclature, for all European countries, with an definition of 25 ha. Digital land use cartography has already been produced for 33 countries. and is expected to expand its geographical coverage.
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Figure 1 – CLC2000 countries availability. Coloured countries (blue and pattern) are all part of CLC2000, but those with navy colour (darker blue) do not have LCC (Land Cover Changes database).
However, for the use of surface occupation cartography like the CLC in wind flow models it is necessary to assign to each different classifications or land cover Classes a equivalent characteristic roughness length. The authors propose a CLC based roughness length classification, obtained throw well known references of roughness classification. The CLC cartography has been adapted for its use in typical wind resource assessment studies, namely for use with the WASP model software, for which some technical problems had to be overcome. The use of the resulting roughness length cartography has been tested in 3 different sites in mainland Portugal and results were compared with most common approaches. In the future, these roughness maps can be extended, along with the CLC project itself, and can also be transposed to other similar land use cartography on other regions.
2. CLC ROUGHNESS LENGTH SCALE
The different CLC definitions have been studied and, according to the particular terrain characteristics, the 44 different CLC Classes were grouped into 14 roughness Classes. The grouping was not always obvious. One has to take into account that the main goal of the CLC project is to classify the land use and landscape, and not the particular roughness of the surface, in what respected their effect on wind. Typical roughness length Classes, as those proposed by the European Wind Atlas [Troen and Peterson, 1989], were compared with the CLC Classes and a set of roughness intervals were assigned to each group. Another roughness classification, by the Royal Netherlands Meteorological Institute (KNMI) [KNMI HYDRA project, 1998] was also considered for validation purposes. The resulting CLC Roughness Length table is shown in Figure 2. For each CLC group the roughness length value most likely to occur was pined out. Have in mind that this assumption is much more site dependent and, mainly, relate to the authors experience and to the Portuguese mainland landscape.
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Roughness [m]
Discription of Corine Land Cover Classes
CLC Codes
Images
Proposed CLC Roughness classification
Other roughness classifications
Value range
Most likely value
KNMI
European Wind Atlas
Continuos urban fabric
111
1.1 - 1.3
1.2
1.6
1
Broad-leaved forest; Coniferous forest; Mixed forest
311;312;313
0.6 - 1.2
0.75
0.75
0.8
Green urban areas; Transitional woodland/shrub; 141;324;334 Burnt areas
0.5 - 0.6
0.6
1.1
Discontinuos urban fabric; Construction sites; Industrial or commercial units; Sport and leisure 112;133;121 142;123 facilities; Port areas
0.3 - 0.5
0.5
0.1 - 0.5
Agro-forestry areas; Complex cultivation patterns; Land principally occupied by agriculture, with 242;243;244 significant areas of natural vegetation
0.1 - 0.5
0.3
Annual crops associated with permanent crops; Fruit trees and berry plantations; Vineyard; Olive groves
241;221 222;223
0.1 - 0.3
0.1
0.39
Road and rail networks and associated land
122
0.05 - 0.1
0.075
0.1
0.05
0.03 - 0.07 0.17
0.03 - 0.05
0.03
0.03
0.0075
0.0003 - 0.001
0.01 - 0.005
Non-irrigated arable land; Permanently irrigated 211;212;213 land; Rice fields; Salt marshes 411,421
Sclerophylous vegetation; Moors and heathland; Natural grassland; Pastures
321;322; 323;231
Dump sites; Mineral extraction sites; Airports; Bare rock; Sparsely vegetated areas
131;132;124 332;333
0.005
Glaciers and perpetual snow
335
0.001
Peatbogs; Salines; Intertidal flats
0.03 - 0.1
422;412;423
0.5
0.1 - 0.3
0.03 - 0.1
0.001
0.0005
Beaches, dunes, and sand plains
331
0.0003
0.0003 - 0.06
0.0003
Water courses; Water bodies; Coastal lagoons; Estuaries; Sea and ocean
511;512;523 522;521
0
0.001
0.0001
Figure 2 – CLC roughness length scale table
3. MAPPING OF CLC ROUGHNESS LENGHTS FOR PRATICAL USE The CLC information is provided in a shapefile or dxf format, and can be read in several geographical information system software. Some data handling and processing is necessary before this information can be used in state of the art wind resource assessment tools, namely in WASP modelling software and the map format of the Map Editor Wasp tool. In this chapter the tackle of some technical issues is discussed in order to help others interested in the use of his data. Figure 3 illustrates the procedure, which can be explained as follows. The CLC Classes to which the same roughness length has been assigned are first merged to each other, forming a single Class. Then, to avoid interceptions between different roughness change lines (aspect which sometimes result in errors and inconsistencies in WASP modelling), the Classes boundary were offset from each other, creating a gap between Classes of 5 m width. Each roughness Class border line has the respective roughness length inside and a default roughness length of 0.02 m, outside. As the WASP roughness model uses sector weighted roughness length for each site, the small gap that has been considered has no significant effect in calculations, for the usual orography map extensions and sector angle. Nonetheless, for small map extensions or small wind rose sector this gap could have significant effect in the results. Tests made confirmed these conclusions.
3
1
2
4
3
5
1 – Original CLC areas 2 – Dissolved areas based on the roughness length 3 – 5 m width buffer zones along the areas border lines 4 – Roughness map with 5 m separate and independent areas 5 – Roughness map on Map Editor (detail of separation between different areas)
Figure 3 – Scheme for the construction of the CLC roughness maps
4. TEST CASES The proposed classification and the CLC roughness maps were tested in three sites located in mainland Portugal. With use of local measurements, wind flow self-predictions were made for different roughness classifications: •
CLC based roughness length maps (CLC),
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•
Corrected CLC based roughness length maps (CLC-C)
•
Constant roughness length (CST) and
•
Custom digitized roughness maps (CTM)
The CLC-C corresponds to the correction of CLC roughness lengths after assessment on site visit. In fact, the only CLC Class effectively corrected was Class 324. Besides being the predominant Class in these sites its roughness assessment is quite difficult. The CST corresponds to considering the site’s most representative roughness length to the overall map area. The CTM approach corresponds to considering digitized roughness areas in the sites and nearby surroundings and a constant roughness length to the most distant region landscape, according to site visit. The roughness areas were digitized until approximately a 1 km distance from the sites.
4.1. SITE’S DESCRIPTION A summarized description of the sites follows: Area 1 - Site with a single met mast. Located in a hilly landscape. Land mainly occupied by agriculture, with significant areas of natural vegetation (CLC243). Non-irrigated arable land (CLC211), Complex cultivation patterns (CLC242), grassland (CLC322) and discontinuous urban fabric (CLC112) at the surroundings. Area 2 – Site in a moderately complex hilly landscape with 3 met masts. Manly transitional woodland (CLC 324) and broad-leaved and coniferous forest (CLC312, CLC311). Complex cultivation patterns (CLC242) and Sclerophylous vegetation (CLC323) in the surroundings. Area 3 – Located in a mountainous complex terrain, with 4 met masts. Mainly transitional woodland (CLC 324) grassland (CLC322) and mixed forests (CLC311, CLC312 and CLC313). All met masts have, at least, two measurement heights, from which vertical self-prediction could be made and compared with actual measured values.
A3
A1
A2 Figure 4 – Location of the 3 test sites along the Portuguese mainland
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CLC description for theses three sites and surroundings was extensively validated by local visit and by comparison with other sources of information, like official military 1/25 000 scale cartography and satellite images. In most cases CLC codes and areas delimitations are able to correctly translate the reality, although it’s necessary to have some aspect under careful consideration.
Figure 5 – Overlapped CLC areas and military 1/25 000 scale cartography
It has been noted that due to different soil and climatic characteristics, the predominant species differ from region to region, producing different landscapes even if classified with the same Land Cover occupation and therefore the same code. Figure 6 shows an example.
Figure 6 - Coniferous forest (code 312), on the left predominant specie in the North and Centre of the country and on the right predominant specie in the South
Another aspect is the transitional woodland/shrubs Class (code 324). This Class, whose definition is already ambiguous in what respects to its roughness length, can represent several and very different land cover, not only from region to region but also within the same region. At least in Portugal, this is one of the most representative land cover present at wind farm sites surroundings, and also one of the most variable regarding its characteristic roughness length. Figure 7 shows examples for the study cases.
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Figure 7 – Various aspects of the CLC code 324 (transitional woodland/shrubs Class)
The 25 ha minimal resolution for the classification of a distinct CLC Class, may ignore small occurrences. That happens especially in the case of small or discontinuous forested areas, which are sometimes diluted into the transitional woodland/shrubs Class (324), due to their small spatial distribution or to the existence of bare places.
Google earth image Figure 8 – Aspect of a CLC code 324 area with small occurrences of forest
5. MAIN RESULTS The following pictures show the results of the wind speed self prediction from the lowest measurement height, for each of the sites tested and each of the roughness formulation. Results are presented in terms of RMS error between predictions and actual measured values. Figure 9 shows the results for each site and Figure 10 shows the overall results for each roughness description used. Results show that the CLC based roughness maps allow the same level of performance as with other roughness formulations. Overall results show even the smallest RMS for CLC roughness map, and for the corrected CLC almost no BIAS. However, the number of cases do not seem representative to formulate this kind of conclusion. CLC based roughness (corrected or not), result in the best predictions for Area 2 and 3 cases. This was not the case for Area 1. Still, at this site, all cases present a great deviation of the same order, about 5.5% to 6.5%, meaning that, probably, the model used is not able to translate the wind flow complexity at that site. The variation between CLC and CLC-C results is mainly due to the contribution of CLC Class 324 areas and the great difficulty in correctly assessing and assigning its characteristic roughness length.
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-7% -6% -5% -4% -3% -2% -1% 0% 1% 2% 3% 4% 5% 6% 7% Prediction Error RMS
Area 2. Station 1 Area 1. Station 1_ 2 Area 2. Station 1 Area 2. Station 2 Area 2. Station 3_1 Area 2. Station 3_2 Area 3. Station 1 Area 3. Station 2 CST Area 3. Station 3
CTM CLC CLC-C
Area 3. Station 4
Figure 9 – Self prediction error for each met mats of the 3 test sites
-1%
0%
1%
2%
3%
4%
5%
Prediction Error CS T
CTM
CLC
RMS
CLC-C
BIAS
Figure 10 – Average self prediction error for each roughness description
Figures 11 and 12 show some examples of the modelled wind speed vertical profile. In the same way, when using the CLC roughness maps, the model is able to predict a vertical profile that best fits the measurement results, exception made, of course, for the Area 1 site (figure 11), but also for the cases where the predominant Class around the mast was the transitional woodland/shrubs Class (code 324). The correction made to the CLC 324 codes roughness values (CLC-C), which meant a significant reduction of the characteristic roughness length form 0.6 m to 0.05 m, only improved the results for the stations located far from any forest occurrences within the 324 code delimitations. These stations (Stations 1 and 2 of Area 3), are situated in areas of new threes plantations, which are still very small, or in open areas or bare places. When comparing with the results
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obtained by the same roughness modified CLC map for other station, it’s clear that there is no improvement from the prediction made with the original CLC maps, rather the results show an increase of error. This results prove that this CLC Class is, in fact, the one that presents the biggest variability of landscape and therefore of characteristic roughness length and, although the 0.6 m value is the most commonly found at this areas, in some cases, overestimations may occur.
100 90
80
80
70
70
60
60
50
50
40
Area 1 . Station 1 h [m]
90
Area 2 . Station 2 h [m]
100
CS T @ 20m CTM @ 20m CLC @ 20m CLC-C @ 20m Measurement
40 CS T @ 40m CTM @ 40m CLC @ 40m CLC-C @ 40m Measurement
30 20
30 20
10
10 U [m/s]
0 4
5
6
7
U [m/s]
0 8
4
5
6
7
8
Figure 11 – Comparison of different vertical wind profiles with site measurement, best (Area 2.Station 3) and worst adjustment (Area 1.Station 1)
90
100 90
CS T @ 30m CTM @ 30m CLC @ 30m CLC-C @ 30m Measurement
80 70
70 60
50
50
40
40
30
30
20
20
10
10 U [m/s]
0 6.5
7
7.5
CS T @ 30m CTM @ 30m CLC @ 30m CLC-C @ 30m Measurement
80
60
6
Area 3 . Station 3 h [m]
Area 3 . Station 1 h [m]
100
8
8.5
U [m/s]
0 9
6
6.5
7
7.5
8
Figure 12 – Comparison of different vertical wind profiles with site measurement, both masts located in a 324 CLC code area (Area 3.Station 1 in new plantations of small trees and Area 3.Station 3 in a area with some forest occurrences)
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5. CONCLUSIONS On the studied sites, CLC based roughness length has resulted in similar results as those obtain through detailed site description and site visits. Even on a sightless roughness description, without any other specific local reference, CLC allowed a good enough description of site’s roughness. Local and regional bioclimatic aspects should be taken into consideration. Due to different soil and climatic characteristics, the predominant species differ from region to region, producing different landscapes although associated with the same Corine Land Cover Class. Special attention should be given to transitional Classes, such as woodland/shrubs Class (CLC 324), as these will vary significantly from site to site. Additionally, these Classes tend to be more important in isolated hilly sites. The 25 ha minimal resolution for the classification of a distinct CLC Class will tend to dilute small but important occurrences. This will happen mostly on transitional Classes. Land cover may, and do change over time. Special care must be given to landscape changes beyond the CLC description time window.
6. REFERENCES 1.Bossard, M. Feranec, J. Otahel J.; CORINE land cover technical guide – addendum 2000; European Environment Agency; Copenhagen May 2000 2.Painho, M. and Caetano, M.; Cartografia de ocupação do solo: Portugal continental, 1985-2000; Corine Land Cover 2000; Instituto do Ambiente;Amadora 2005 3.Troen, I. and Petersen, E.L.; European Wind Atlas; Commission of the European Communities; Riso National Laboratory, Roskilde 1989 4. European Environmental Agency; http://www.eea.europa.eu 5. Instituto do Ambiente; http://www.iambiente.pt 6. Royal Netherlands Meteorological Institute; http://www.knmi.nl
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