CORINE Land Cover 2006 for Continental Portugal

Transcription

1 CORINE Land Cover 2006 for Continental Portugal Mário Caetano, Vasco Nunes and António Nunes July 2009 European Environmental Agency

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3 This report should be cited as Caetano, M., V. Nunes and A. Nunes, CORINE Land Cover 2006 for Continental Portugal, Technical Report, Instituto Geográfico Português. i

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5 Aknowledgments We thank Carlos Sarmento, Miguel Cardoso, Patrícia Pécurto, Pedro Sarmento and Ricardo Silva for the dedication in their image interpretation work and Maria Pereira for the revision of this document. iii

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7 Abstract This document reports the production of three maps for Continental Portugal: CORINE Land Cover Changes (CHA06_PT), CORINE Land Cover 2006 (CLC06_PT), and a revised version of the CORINE Land Cover 2000 (CLC00_PT). These maps were produced by the Remote Sensing Unit of the Portuguese Geographic Institute, within the Global Monitoring for Environment and Security Land Fast Track Service Precursor (GMES Land FTSP) for Continental Portugal. GMES Land FTSP is an initiative created by the European Environment Agency (EEA) and European Commission (EC), namely with the goal of updating previous CORINE Land Cover (CLC) mapping initiatives. A validation protocol was applied to the CLC06_PT map and the estimated overall accuracy was 90,2%, with an absolute precision of 1,3 at the 95% confidence level. The results obtained also show that 7,8% of the original CLC2000-PT database was corrected when producing CLC00_PT, and that 8,6% of the area of Continental Portugal was affected by land use and land cover changes, in the period from 2000 to Forest and seminatural areas, as well as Agricultural areas, continue to be the dominant land use and land cover (LULC) types in the territory and the main source of change dynamics. Keywords: Land use and land cover (LULC), CORINE Land Cover, CLC2006, Portugal v

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9 Index Abstract...v Index...vii Table index... ix Figure index... xi Acronyms...xiii 1 Introduction Production Production strategy Data sources Base data Ancillary data Development of specific tools to enhance the production process Production of CHA06_PT Revision of the original CLC2000-PT Production of CLC06_PT Quality control Metadata Validation of CLC06_PT Results and discussion Analysis of LULC change in Continental Portugal in the period Revision of the original CLC2000-PT Validation of the CLC06_PT map Analysis of LULC in Continental Portugal in Conclusions References Annex 1 Metadata of CHA06_PT Annex 2 Metadata of CLC00_PT Annex 3 Metadata of CLC06_PT vii

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11 Table index Table 1 - Characteristics of CHA06_PT, CLC00_PT and CLC06_PT... 4 Table 2 CORINE Land Cover (CLC) nomenclature Table 3 - General characteristics of the satellite images used as base data... 7 Table 4 Detailed characteristics of the satellite images used as base data Table 5 Summary of ancillary data characteristics Table 6 Technical specifications of the orthorectified digital aerial images Table 7 Examples of the tools created by the National Technical Team for the extension of Interchange Table 8 Key-features of the accuracy assessment strategy developed for CLC06_PT Table 9 - Areas gained (+) and lost (-) per CLC class between 2000 and 2006 in Continental Portugal Table land use and land cover change matrix for Continental Portugal (areas are presented in hectares) Table 11 - Top-10 level-3 changes in Continental Portugal between 2000 and Table 12 Area differences per CLC class between the revised and the original CLC2000- PT databases Table 13 Percentage area occupied per mapped land cover class (N h ). Estimates for percentage area occupied per reference land cover class (N g ), percentage overall accuracy (P), percentage user s accuracy (P h ), and percentage producer s accuracy (P g ). The absolute precision (d) was estimated at the 95% confidence level Table 14 CLC level-1 class areas in CLC06_PT and CLC00_PT Table 15 - CLC level-2 class areas in CLC06_PT and CLC00_PT Table 16 - CLC level-3 class areas in CLC06_PT and CLC00_PT ix

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13 Figure index Figure 1 - Methodological approaches for producing CLC-Changes and CLC2006 (source: EEA, 2007) Figure 2 Landsat ETM+ imagery of the year 2000 (summer). Source: Painho and Caetano (2006) Figure 3 - SPOT-4, SPOT-5 and IRS-P6 LISS III imagery for spring and summer of Figure 4 - Spring and summer satellite images of irrigated and non-irrigated arable areas Figure 5 Acquisition dates of the orthorectified digital aerial images Figure 6 Visualization of imagery at different scales. On top: 2006 satellite image. Below: digital aerial images from the 2004/2005/2006 national coverage Figure 7 - Software Interchange Figure 8 Menu and options of the extension developed by the National Technical Team for Interchange Figure 9 - Working units for the production of the CHA06_PT database Figure 10 - Team of photo-interpreters Figure 11 - Examples of corrections made to the original CLC2000-PT Figure 12 CHA06_PT map Figure 13 CLC00_PT map Figure 14 - Percentage of corrections made to the original CLC2000-PT database per NUTSIII Figure 15 - CLC06_PT map xi

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15 Acronyms APA Agência Portuguesa do Ambiente (Portuguese Environment Agency) CAOP Official administrative map of Portugal CHA06_PT - CORINE Land Cover Changes for Continental Portugal CLC CORINE Land Cover CLC00_PT - Revised version of the CORINE Land Cover 2000 for Continental Portugal CLC06_PT - CLC2000-PT - CORINE Land Cover 2000 for Continental Portugal CORINE COoRdination of INformation on the Environment COS 90 Land Cover Map of Continental Portugal for 1990 DGRF Direcção Geral dos Recursos Florestais (General Directorate of Forests) EC European Commission EEA - European Environmental Agency Eionet - European Environmental Information Observation Network ETC-LUSI - European Topic Centre for Land Use and Spatial Information ETRS - European Terrestrial Reference System GIS Geographic Information System GMES Land FTSP - Global Monitoring for Environment and Security Land Fast Track Service Precursor IFN National Forest Inventory IGP Instituto Geográfico Português (Portuguese Geographic Institute) IVV Instituto da Vinha e do Vinho (Institute of Wine and Vineyard) LULC Land Use and Land Cover MMU Minimum Mapping Unit NRC-LUSI - National Reference Centre for Land Use and Spatial Information NUTS - Nomenclature of Territorial Units for Statistics OGC - Open Geospatial Consortium PT - Portugal WMS - Web Map Service WU - Working Unit xiii

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17 1 Introduction This document reports the production of two maps: CORINE Land Cover Changes (CHA06_PT) and (CLC06_PT). These are two components of the Global Monitoring for Environment and Security Land Fast Track Service Precursor (GMES Land FTSP) for Continental Portugal. GMES Land FTSP is an initiative created by the European Environment Agency (EEA) and European Commission (EC), namely with the goal of updating previous CORINE Land Cover (CLC) mapping initiatives (EEA, 2006; EEA, 2007). This report also describes the production of a revised version of the original CLC2000-PT (CLC00_PT). GMES Land FTSP for Continental Portugal was funded by the EEA, Portuguese Environment Agency (APA) and Portuguese Geographic Institute (IGP). The Remote Sensing Unit of IGP, which is the National Reference Centre for Land Use and Spatial Information (NRC-LUSI) of the European Environmental Information Observation Network (Eionet), coordinated and carried out the GMES Land FTSP for Portugal. The Remote Sensing Unit of IGP was also responsible for the validation of the highresolution built-up areas layer for Continental Portugal (reported in Caetano et al. (2008)). This layer is another component of GMES Land FTSP. This document is organised in four chapters, including this introduction, a description of the main topics related with the production of CLC00_PT, CHA06_PT and CLC06_PT, an analysis of the results obtained, and final conclusions. 1

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19 2 Production 2.1 Production strategy The strategy designed in the framework of the GMES Land FTSP project considered two possible methodological approaches for producing CLC-Changes and CLC2006: (a) Update first approach and (b) Change mapping first approach. Figure 1 illustrates these two approaches. a) Update first approach revision of CLC2000 interpretation of CLC2006 GIS based derivation of CLC-Change b) Change mapping first approach revision of CLC2000 interpretation of CLC-Change GIS based derivation of CLC2006 Figure 1 - Methodological approaches for producing CLC-Changes and CLC2006 (source: EEA, 2007). In the Portuguese project the chosen approach was the change mapping first approach (b), the same as the one applied in the predecessor project, i.e. CLC2000 for Continental Portugal (Painho and Caetano, 2006). This approach consists in: i. Computer-assisted visual interpretation of 2000 and 2006 satellite images to detect real changes visible on the images and delineate change polygons that fulfil the technical specifications of the product (EEA, 2007); ii. Revision of the original CLC2000-PT database, simultaneously performed with i.; iii. Derivation of CLC06_PT based on spatial analysis within a Geographic Information System (GIS). The maps reported here, and produced in the framework of the Portuguese GMES Land FTSP project, are characterised in Table 1. 3

20 Table 1 - Characteristics of CHA06_PT, CLC00_PT and CLC06_PT. CHA06_PT CLC00_PT CLC06_PT Scale 1: : : Minimum Mapping 5 25* 25* Unit (MMU) (ha) Minimum distance between lines (m) Format Vector Vector Vector Nomenclature Code 2000; Code 2006 CLC nomenclature CLC nomenclature Geometric accuracy Better than 100m Better than 100m Better than 100m Thematic Accuracy % 85% Coordinate reference system Datum: ETRS89 (European Terrestrial Reference System 1989) Alias: ETRS89 / PT-TM06 Ellipsoid: GRS80 (New International) Projection: Transverse Mercator Central Meridian: 08º 07' 59'', 19 W Latitude of Origin: 39º 40' 05'', 73 N Linear Unit: Metre (1,0) Scale Factor: 1,0 False Easting: 0 False Northing: 0 *The MMU is 25 ha except for polygons intersected by the Portugal-Spain border. The CLC nomenclature is based on an a priori and hierarchical classification system, with three levels that correspond to different and increasing thematic detail. The third and most detailed level has originally 44 classes (Büttner et. al., 2006), but in Portugal only 42 classes were used since there are no Glaciers and perpetual snow (class 335), nor Peat bogs (class 412). Table 2 shows the classes in all three levels of the CLC nomenclature. 4

21 Table 2 CORINE Land Cover (CLC) nomenclature. Level 1 Level 2 Level 3 1 Artificial surfaces 2 Agricultural areas 3 Forest and semi natural areas 4 Wetlands 5 Water bodies 11 Urban fabric 111 Continuous urban fabric 112 Discontinuous urban fabric 12 Industrial, commercial and 121 Industrial or commercial units transport units 122 Road and rail networks and associated land 123 Port areas 124 Airports 13 Mine, dump and 131 Mineral extraction sites construction sites 132 Dump sites 133 Construction sites 14 Artificial, non-agricultural 141 Green urban areas vegetated areas 142 Sport and leisure facilities 21 Arable land 211 Non-irrigated arable land 212 Permanently irrigated land 213 Rice fields 22 Permanent crops 221 Vineyards 222 Fruit trees and berry plantations 223 Olive groves 23 Pastures 231 Pastures 24 Heterogeneous agricultural 241 Annual crops associated with permanent crops areas 242 Complex cultivation patterns 243 Land principally occupied by agriculture, with significant areas of natural vegetation 244 Agro-forestry areas 31 Forests 311 Broad-leaved forest 312 Coniferous forest 313 Mixed forest 32 Scrub and/or herbaceous 321 Natural grasslands vegetation associations 322 Moors and heathland 323 Sclerophyllous vegetation 324 Transitional woodland-shrub 33 Open spaces with little 331 Beaches, dunes, sands or no vegetation 332 Bare rocks 333 Sparsely vegetated areas 334 Burnt areas 335 Glaciers and perpetual snow 41 Inland wetlands 411 Inland marshes 412 Peat bogs 42 Maritime wetlands 421 Salt marshes 422 Salines 423 Intertidal flats 51 Inland waters 511 Water courses 512 Water bodies 52 Marine waters 521 Coastal lagoons 522 Estuaries 523 Sea and ocean 5

22 2.2 Data sources To produce CHA06_PT and review the original CLC2000-PT database, two different types of data were used: satellite imagery as base data and other types of data that served as ancillary information to enhance landscape interpretation Base data The base data that we used was constituted by satellite imagery collected in the summer of 2000 (Figure 2) and in the spring and summer of 2006 (Figure 3). The characteristics of the images are summarized in Table 3 and Table 4. Figure 2 Landsat ETM+ imagery of the year 2000 (summer). Source: Painho and Caetano (2006). 6

23 ID data year month date Month Mainland Portugal ID data year month date Month Mainland Portugal Figure 3 - SPOT-4, SPOT-5 and IRS-P6 LISS III imagery for spring and summer of Table 3 - General characteristics of the satellite images used as base data. Imagery Reference year Number of bands (available) Spatial resolution (resampled) (m) IRS-P6 LISS III 2006 (spring and summer) 4 20 SPOT (spring and summer) 4 20 SPOT (spring and summer) 4 20 Landsat-7 ETM (summer)

24 Table 4 Detailed characteristics of the satellite images used as base data. Landsat 7 SPOT-5 SPOT-4 IRS P6 Sensor ETM+ HRG HRVIR LISS III Swath width (km) x x x x x 140 (depending on looking angle) (depending on looking angle) Spatial resolution 60 (Thermal band) 20 (Middle-infrared) 20 (Multispectral) 23,5 (m) 30 (Multi-spectral) 10 (Panchromatic) 10 (Green, Red, NIR) 5 (Panchromatic) 10 (Panchromatic) Radiometric resolution (bits) Number of bands 7+1 (original) Blue band 0,45 0,52 µm (TM1) Green band 0,53 0,61 µm (TM2) 0,50 0,59 m 0,50 0,59 µm 0,52 0,59 µm Red band 0,63 0,69 µm (TM3) 0,61 0,68 m 0,61 0,68 µm 0,62 0,68 µm Near-infrared band 0,75 0,90 µm (TM4) 0,78 0,89 m 0,78 0,89 µm 0,77 0,86 µm (NIR) Middle-infrared 1,55 1,75 µm (TM5) 1,58 1,75 m 1,58 1,75 µm 1,55 1,70 µm band Thermal-infrared 10,4 12,5 µm (TM6) band Far-infrared band 2,09 2,35 µm (TM7) Panchromatic band 0,52 0,90 µm (PAN) 0,48 0,71 m 0,61 0,68 µm --- Observation mode Vertical only Tiltable sensor (up Tiltable sensor Vertical only to ± 31º) (up to ± 31º) Temporal resolution 16 days 2-3 days 2-3 days 25 days Reference system ETRS89-PT06 ETRS89-PT06 ETRS89-PT06 ETRS89-PT06 The images of the reference year 2006 were taken both in spring and summer periods in order to allow for the analysis of changes in vegetation phenological characteristics and thus improve the discrimination between land cover classes. Figure 4 shows an example of a region mainly occupied by agriculture, where irrigated and non-irrigated arable crops are better identified through the comparison of spring and summer images. 8

25 Spring 2006 Summer 2006 Figure 4 - Spring and summer satellite images of irrigated and non-irrigated arable areas Ancillary data In order to support and improve the visual interpretation of the landscape, additional data of Continental Portugal was provided to the photo-interpreters. Table 5 shows a compilation of the ancillary data used in this project. Table 5 Summary of ancillary data characteristics. Data Reference year Owner Scale MMU / Resolution (m) Format Orthorectified digital aerial imagery - national coverage 2004, 2005 and 2006 IGP/DGRF 1: ,50 m Raster Orthorectified analogue aerial imagery - national coverage Land Cover Map of Continental Portugal for 1990 (COS 90) 1995 IGP 1: m Raster 1990 IGP 1: ha Vector Yearly burned area maps DGRF 1: ha Vector National Forest Inventory 1995 (IFN1995) 1995 DGRF --- 0,5 ha Vector Vineyard Information System IVV Vector Official Administrative Map of Portugal (CAOP) IGP 1: Vector IVV Institute of Wine and Vineyard; DGRF General Directorate of Forests The main ancillary data used by the photo-interpreters was the 2004/2005/2006 national coverage of orthorectified digital aerial images. The characteristics of these ortho-images are summarized in Table 6 and the respective acquisition dates are shown in Figure 5. Figure 6 shows an example of the detail that can be achieved using these aerial images as ancillary information for land use and land cover (LULC) mapping. 9

26 Table 6 Technical specifications of the orthorectified digital aerial images. Camera Flight altitude Dates of flights Image swath Spatial resolution Radiometric resolution Spectral resolution Ultracam from Vexcel Approx. 5800m November, 2004; August and September, 2005; May and June, x 5 km 0,50 m 8 bits per band 4 spectral bands: Blue, Green, Red and NIR Years of flights 2004, 2005 and 2006 Image format Reference system Flights performed by Property rights TIFF ETRS89-PT06 DGRF DGRF / IGP Figure 5 Acquisition dates of the orthorectified digital aerial images. 10

27 Summer 2006 False colour True colour Figure 6 Visualization of imagery at different scales. On top: 2006 satellite image. Below: digital aerial images from the 2004/2005/2006 national coverage. The orthorectified digital aerial images were available through Web Map Service (WMS). This format allows the visualization of maps through a network connection. In order to use this service on an ArcView 3.x platform (the one used for CLC06_PT production), we installed an extension (WMS support) and created a series of files with Open Geospatial Consortium (OGC) format. This allowed the access to the various layers of information from the WMS. These layers were the following: Itinerary map of Portugal 1: ; 1: topographic map; 1: topographic map; 1: topographic map; 2004/2005/2006 aerial images. The layers are successively loaded as the visualization scale changes. For the aerial imagery there were two colour composites available: one for true colour and one for false colour. 2.3 Development of specific tools to enhance the production process The basic tool for map production was the software Interchange 2.0 (Figure 7). This software is an adaptation of ESRI s ArcView 3.2 software and not only allowed for a direct 11

28 comparison of the 2000 and 2006 images but also provided a series of editing and visualisation tools specifically designed for the production of CLC-Changes Figure 7 - Software Interchange 2.0. Furthermore, during the course of the production process, the National Technical Team developed important additional tools, essentially related to the virtual production workspace and to quality control procedures. These tools were compiled in an extension of Interchange 2.0 (Figure 8). Some of the tools developed by the National Technical Team are described in Table 7. Figure 8 Menu and options of the extension developed by the National Technical Team for Interchange

29 Table 7 Examples of the tools created by the National Technical Team for the extension of Interchange 2.0. Button Description of functionality This button zooms the view(s) to a previously defined scale. This button pulls the dialog box for searching the shapefile based on a chosen field. The script steps through all polygons coded in the chosen field with value 1. This button stretches the values of the Digital Numbers for each band of the image present in the view. This tool enables the user to click on a polygon and check the online official description of the respective CLC class. This tool is used to mark cells of a control grid as done. This tool transfers the clicked polygon(s) to Google Earth. This tool lists every available image for the clicked area in the view. The user then selects from the list, the ones to be loaded. This tool loads into the view orthorectified aerial images from 1995 available in the clicked area or location. 2.4 Production of CHA06_PT The main task in this project was the production of the CHA06_PT database, which consisted in computer-assisted visual interpretation of satellite images of the years 2000 and The image interpretation procedure included a visual comparison between the 2000 and 2006 satellite images, the detection of real changes visible in the images, and the delineation of change polygons that fulfilled the technical specifications of the product (EEA, 2007). The changes that were mapped were the ones that occurred between 2000 and 2006, and were detectable in the base data, larger than 5 ha and wider than 100m. The map production specifications for CHA06_PT differed from the ones of CLC- Changes PT, in the fact that for CHA06_PT all the changes larger than 5 ha were mapped. When CLC-Changes PT was produced the areas that were not contiguous to polygons of the same class already present in 1990, were only mapped if they had a minimum of 25 ha (b). The delineation of changes was based on the polygons of CLC00_PT in order to avoid the creation of sliver polygons when integrating that map with CHA06_PT to produce CLC06_PT. The CHA06_PT database was produced at Working Unit (WU) level. The same way as in the predecessor project, i.e. CLC2000 for Continental Portugal, each WU corresponded to a sheet of the National Map Series 1: (Figure 9). 13

30 a a b Figure 9 - Working units for the production of the CHA06_PT database. The production team consisted of five photo-interpreters (Figure 10), selected from more than 100 candidates. Each of the interpreters was responsible for producing the CHA06_PT database for a given area of Continental Portugal. Figure 10 - Team of photo-interpreters. 2.5 Revision of the original CLC2000-PT The interpretation of the territory of Continental Portugal in view of detecting land cover changes between 2000 and 2006, inevitably unveiled some problems in the original CLC2000-PT database. Furthermore, the use of more and better data than in the 2000 project, namely aerial imagery and spring and summer 2006 satellite images, promoted a better understanding of the landscape. The problems detected were corrected, which allowed for the improvement of the original CLC2000-PT and at the same time avoided 14

31 error propagation in CLC06_PT. Figure 11 shows some examples of the corrections that were made to the original CLC2000-PT database Original CLC2000-PT CLC2000r CLC00_PT CLC2000 Original CLC2000-PT CLC2000r CLC00_PT CLC2000 Original CLC2000-PT CLC2000r CLC00_PT Figure 11 - Examples of corrections made to the original CLC2000-PT. 15

32 2.6 Production of CLC06_PT The revised version of the original CLC2000-PT, i.e. CLC00_PT, was combined with CHA06_PT to produce the CLC06_PT map, as follows: CLC06_PT = CLC00_PT + CHA06_PT. The above operation produced polygons smaller than the MMU established for CLC2006. Thus, some generalisation procedures were applied, following the official guidelines for the project. These generalisation procedures were implemented using a dedicated ArcInfo script, provided by the European Topic Centre for Land Use and Spatial Information (ETC- LUSI). 2.7 Quality control During the production stage several quality control procedures were carried out. After producing CHA06_PT for a given WU, the photo-interpreter had a verification list to control several well-known sources of potential errors (e.g. questionable transitions, dynamic classes in 2000 to check for probable changes that were not mapped, zerocoded polygons, cross-boundary harmonisation between working units). Afterwards, the National Technical Team checked random areas for thematic and structural aspects. When errors were found, remarks were made, and the WU returned to the correspondent photointerpreter so that the respective corrections could be implemented. Additionally, ETC-LUSI carried out two verifications missions, the first after 25-50% of the area had been processed and the second when processing had reached %. In these verification missions, ETC-LUSI checked the CHA06_PT and CLC00_PT products, communicating several remarks and recommendations to the National Technical Team. These were implemented and only then the WU production and quality control cycle was considered completed. Finally, after several iterations of the previously described quality control procedures, the working units were merged and checked for structural, geometric and topology errors (e.g. polygons smaller than 25 ha, minimum distance between lines smaller than 100m). The errors found were corrected in all map products. 2.8 Metadata The metadata of CHA06_PT were produced both at WU level and at country level. These metadata were produced according to the forms provided by ETC-LUSI (EEA, 2007). In the cases of the maps CLC00_PT and CLC06_PT, only country-level metadata were produced. The metadata of the products can be found, respectively, in Annexes 1, 2 and 3. 16

33 2.9 Validation of CLC06_PT The accuracy of the CLC06_PT map was evaluated through a statistically sound method developed by the Remote Sensing Unit of IGP and has been successfully used in several projects of that Unit (e.g. Carrão et al., 2009; Araújo et al., 2009; Costa et al., 2009). This method follows the recommendations of Dicks and Lo (1990) regarding the design of a sampling survey for accuracy assessment, including the determination of the acceptable level of accuracy, the definition of the reference sample, sample size and sample selection strategy, and the choice of accuracy measures. Overall, the method is also based on the work of several others authors, such as Anderson et al. (1976), Jensen (1996), Card (1982), Carrão et al. (2007), Congalton and Green (1999), Stehman and Czaplewski (1998), Stehman (1999), and Stehman (2001). For a complete description of the accuracy assessment of CLC06_PT the reader is referred to Caetano et al. (2009a). The minimum level of acceptable thematic accuracy we defined was 85%. The validation of CLC06_PT was done through the comparison of the map with a reference database, which consisted in a sample of the LULC in Continental Portugal considered to be representative of the reality. The most important data used to construct the reference database were a national coverage of 2007 orthorectified digital aerial images and the 2006 satellite images used in the production of CLC06_PT. The sampling design followed a stratified random sampling approach to ensure the independence of the sample observations within the sample itself and in relation to the characteristics of the territory. The reference database was based on the CLC nomenclature and consisted in 100 sampling units per mapped class. This resulted in a global reference sample of 4200 sampling units. The protocol to determine the reference LULC classification of a sampling unit included: i) Labelling of primary and alternative reference land cover labels through interpretation of reference and ancillary data; ii) Labelling of location confidence ratings for each sampling unit, which allowed for the discrimination of the sampling units located in the vicinity of land cover class boundaries (i.e. at a distance smaller than 100m); iii) Labeling of primary reference land cover labels of the neighbour land cover classes, when these exist in the vicinity of the sampling unit. The most relevant features of the strategy developed for the accuracy assessment of CLC06_PT are summarized in Table 8. Table 8 Key-features of the accuracy assessment strategy developed for CLC06_PT. Target accuracy Sampling units Sampling scheme Sample size Attributes to be collected for reference sample At least 85% thematic accuracy at 95% confidence level Points Stratified random sampling 100 sampling units per mapped class Labeling of primary reference land cover labels, alternative reference land cover labels and location confidence ratings 17

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35 3 Results and discussion In this chapter we present a brief analysis of the results obtained for all map products. The chapter is sub-divided according to the three main topics related with production: LULC change detection between 2000 and 2006, based on CHA06_PT; revision of the original CLC2000-PT database; and CLC06_PT map production. All results refer to the area of Continental Portugal delimited by CAOP, which provides the official administrative limit defined by IGP (IGP, 2009). The total area of Continental Portugal given by CAOP is ha. 3.1 Analysis of LULC change in Continental Portugal in the period The analysis of land use and land cover changes in Continental Portugal was based on the CHA06_PT database. These changes occurred in 8,6% of the territory and are illustrated in Figure 12. CLC changes Figure 12 CHA06_PT map. 19

36 From the analysis of the map it can be easily concluded that the centre of the territory was the region with the highest occurrence of changes in the period This is related essentially to the well-known dynamic nature of the Portuguese forests, which constitute the main land cover type in that region. In order to further understand the LULC dynamics in Continental Portugal between 2000 and 2006 it is important to examine the areas that were gained and lost per class in that period (Table 9), as well as the change matrix (Table 10). Table 9 - Areas gained (+) and lost (-) per CLC class between 2000 and 2006 in Continental Portugal. Area (ha) CLC class Out In Difference

37 Table land use and land cover change matrix for Continental Portugal (areas are presented in hectares). CLC06_PT Total CLC00_PT Total

38 At level 1 of the nomenclature the main changes occur from classes: 2 and 3 to 1; 2 and 3 to 5; 3 to 2; and 2 to 3. These changes represent the growth of urban areas, the construction of new artificial dams and lakes, and the conversion of natural to agricultural areas and vice-versa. Within class 3, the changes from classes 311, 312 or 313 to 324, and vice-versa, are the most representative ones in terms of area, showing the dynamics in the Portuguese forest sector. The large area corresponding to occurrences of forest fires also has an important influence in this dynamics. Regarding agricultural areas, the classes that changed most were 211 and 244, often converted to new forest plantations (class 324). Table 11 shows the top-10 level-3 changes in terms of area. Table 11 - Top-10 level-3 changes in Continental Portugal between 2000 and Change Area (ha) Revision of the original CLC2000-PT As a result of the revision of the original CLC2000-PT database (see Figure 13), 7,8% of the area of Continental Portugal were corrected for geometric and thematic errors. In view of analysing which region of the territory was subjected to more corrections, the original and revised CLC2000-PT databases were intersected with the level-3 NUTS (Nomenclature of Territorial Units for Statistics) for Continental Portugal. Figure 14 shows the percentage of corrections made to the original CLC2000-PT database per NUTS III. Minho/Lima, Beira Interior Norte, Grande Lisboa and Alentejo Central were the most corrected NUTS. The Centre and North-Interior were the regions of the territory with fewer corrections. Table 12 shows the area differences per class between the revised and the original CLC2000-PT databases. Classes 423, 332, 333, 133 and 112 were significantly corrected relatively to their original area. This doesn t mean necessarily though that they correspond to the major part of the corrected area in relation to the total area of Continental Portugal. In fact, classes that occupy a larger part of the territory are likely to be subjected to more corrections than less represented classes. This was the case with 112, 211, 311, 322 and 324, which were the classes responsible for the major part of the overall improvements. 22

39 CLC2000 revised Figure 13 CLC00_PT map. Legend Corrections (%) Figure 14 - Percentage of corrections made to the original CLC2000-PT database per NUTSIII. 23

40 CLC class Table 12 Area differences per CLC class between the revised and the original CLC2000-PT databases. Original CLC2000-PT CLC00_PT Difference Area (ha) % of total area of Cont. Portugal Area (ha) % of total area of Cont. Portugal Relative to total area of Cont. Portugal (%) Relative to class area in original CLC2000- PT (%) , ,1-0, , , ,3 +0, , , ,3 +0, , , ,0-0,0006-2, , ,0 +0, , , ,0 +0, , , ,1-0,0089-6, , ,0 +0, , ,1 +0, , , ,0 +0, , , ,1 +0, , ,5-0,8213-6, , ,3 +0,104 +4, , ,6 +0, , , ,5-0,1139-4, , ,1 +0, , , ,0-0,0858-2, , ,5 +0, , , ,6-0,1641-3, , ,9-0,1455-2, , ,9 +0, , , ,1 +0, , , ,6-1,0792-7, , ,0 +0, , , ,1 +0, , , ,0-0,1020-4, , ,3-0, , , ,5 +0, , , ,5 +0, , , ,1-0,0027-2, , ,3-0, , , ,1 +0, , , ,3-0,0211-5, , ,0 +0, , , ,2-0,0047-2, , ,1-0,0037-4, , ,0 +0, , , ,2 +0, , , ,4 +0, , , ,1 +0, , , ,2 +0, , , ,0-0, ,0 24

41 3.3 Validation of the CLC06_PT map As a result of the accuracy assessment of CLC06_PT we obtained estimates for the overall and specific map accuracy indices (Table 13). These estimates confirm the good quality of the product CLC06_PT. In fact, the estimated overall accuracy was 90,2%, with an absolute precision of 1,3% at the 95% confidence level. This is well above the 85% thematic accuracy target that we had set. Regarding user s accuracies, only classes 231, 132, 222, 313 and 332 have confidence intervals completely below the 85% thematic accuracy target. In the case of producer s accuracies, only classes 231 and 423 present confidence intervals completely below the same target. However, while for user s accuracies the confidence intervals were small for all land cover classes, for producer s accuracies some classes were estimated with very large confidence intervals, which means that the estimates for these specific classes must be considered with care because larger confidence intervals indicate that we can have less confidence in the correspondent estimates. 25

42 Table 13 Percentage area occupied per mapped land cover class (Nh). Estimates for percentage area occupied per reference land cover class (Ng), percentage overall accuracy (P), percentage user s accuracy (Ph), and percentage producer s accuracy (Pg). The absolute precision (d) was estimated at the 95% confidence level. CLC class N N ˆ ± d( ˆ ) P ˆ ± d ( ˆ ) P ˆ ± d ( ˆ ) h g N g h P h g P g 111 0,1 0,1 ± 0,0 97,0 ± 3,3 100 ± 0, ,9 2,0 ± 0,2 99,0 ± 2,0 91,9 ± 7, ,3 0,3 ± 0,1 90,0 ± 5,9 86,8 ± 19, ,1 0,1 ± 0,1 93,0 ± 5,0 65,4 ± 34, ,0 0,0 ± 0,0 95,0 ± 4,2 100,0 ± 0, ,0 0,0 ± 0,0 100,0 ± 0,0 97,3 ± 5, ,1 0,2 ± 0,1 97,0 ± 3,3 74,3 ± 32, ,0 0,0 ± 0,0 71,0 ± 8,5 83,3 ± 27, ,1 0,0 ± 0,0 78,0 ± 8,1 98,1 ± 2, ,0 0,0 ± 0,0 95,0 ± 4,2 87,9 ± 14, ,1 0,1 ± 0,1 93,0 ± 5,0 63,6 ± 44, ,6 7,8 ± 0,6 86,0 ± 6,8 94,8 ± 2, ,9 1,7 ± 0,2 80,8 ± 7,8 90,1 ± 10, ,5 0,4 ± 0,0 86,0 ± 6,8 97,3 ± 3, ,0 1,9 ± 0,1 94,0 ± 4,7 99,5 ± 0, ,9 0,8 ± 0,2 72,0 ± 8,8 81,8 ± 17, ,3 2,3 ± 0,3 81,2 ± 7,7 81,8 ± 9, ,4 0,4 ± 0,2 51,0 ± 9,8 51,9 ± 24, ,5 3,7 ± 0,5 81,0 ± 7,7 76,6 ± 9, ,4 5,3 ± 0,7 79,0 ± 8,0 80,3 ± 7, ,1 6,6 ± 0,6 90,0 ± 5,9 83,1 ± 6, ,5 5,6 ± 0,6 89,0 ± 6,2 87,8 ± 7, ,9 9,7 ± 0,7 94,0 ± 4,7 85,8 ± 4, ,7 5,2 ± 0,4 96,0 ± 3,9 86,9 ± 6, ,2 3,4 ± 0,5 74,0 ± 8,6 91,0 ± 9, ,6 1,7 ± 0,2 84,0 ± 7,2 75,5 ± 9, ,6 2,3 ± 0,2 81,0 ± 7,7 91,3 ± 4, ,9 1,9 ± 0,2 91,0 ± 5,6 89,4 ± 7, ,6 12,6 ± 0,8 92,0 ± 5,3 92,0 ± 3, ,1 0,1 ± 0,0 96,0 ± 3,8 95,2 ± 5, ,2 0,1 ± 0,0 66,0 ± 9,3 100,0 ± 0, ,9 0,8 ± 0,1 80,0 ± 7,9 89,2 ± 9, ,3 0,3 ± 0,1 87,0 ± 6,6 90,0 ± 16, ,0 0,0 ± 0,0 95,0 ± 4,1 53,9 ± 32, ,2 0,2 ± 0,0 83,0 ± 7,4 86,2 ± 17, ,1 0,1 ± 0,0 97,0 ± 3,3 97,4 ± 4, ,0 0,0 ± 0,0 95,0 ± 4,2 51,5 ± 17, ,2 0,2 ± 0,0 98,0 ± 2,8 86,4 ± 17, ,5 0,5 ± 0,0 97,0 ± 3,4 99,0 ± 1, ,1 0,1 ± 0,0 97,0 ± 3,3 97,7 ± 4, ,4 0,4 ± 0,0 98,0 ± 2,8 99,7 ± 0, ,1 21,1 ± 0,0 100,0 ± 0 100,0 ± 0,0 Overall accuracy P ˆ ± d ( Pˆ ) 90,2 ± 1,3 26

43 3.4 Analysis of LULC in Continental Portugal in 2006 The integration of CHA06_PT with CLC00_PT and the implementation of generalisation procedures led to the creation of the CLC06_PT database (Figure 15). CLC2006 Figure 15 - CLC06_PT map. The main information that can be retrieved from the map is the dominance of Forest and semi-natural areas, and Agricultural areas. Table 14 confirms this, adding Artificial surfaces as the third most representative level-1 CLC class in Water bodies and Wetlands are the least representative level-1 classes in that year. These proportions are very similar to the reality as represented in the CLC00_PT map. Looking at the area differences between CLC06_PT and CLC00_PT we can see that Water bodies were the class that grew most relatively to the area in CLC00_PT, followed by Artificial surfaces. This growth originated mainly from Agricultural areas, which were the only level-1 CLC class that decreased. 27

44 Table 14 CLC level-1 class areas in CLC06_PT and CLC00_PT. CLC00_PT CLC06_PT Area difference CLC % of total area % of total area Relative to total Relative to class Absolute class Area (ha) of Cont. Area (ha) of Cont. area of Cont. area in CLC00_PT (ha) level 1 Portugal Portugal Portugal (%) (%) , , , , , , ,5727-1, , , , , , , , , , , , ,2 The same type of analysis can be done for the second and third levels of the CLC nomenclature (Table 15 and Table 16, respectively). From the analysis of Table 15 it can be concluded that the above-mentioned dominance of class 3 in 2006 is mainly due to Forests (31) and Scrub and/or herbaceous vegetation associations (32). In Agricultural areas, the most representative class in 2006 is Heterogeneous agricultural areas (24). As for Artificial surfaces, most of them are constituted by Urban fabric (class 11). These patterns can also be observed for the areas present in the CLC00_PT map. Table 15 - CLC level-2 class areas in CLC06_PT and CLC00_PT. CLC00_PT CLC06_PT Area difference CLC % of total area % of total area Relative to total Relative to class Absolute class Area (ha) of Cont. Area (ha) of Cont. area of Cont. area in CLC00_PT (ha) level 2 Portugal Portugal Portugal (%) (%) , , , , , , , , , , , , , , , , , , ,3654-2, , , , , , , ,0026-0, , , ,2811-1, , , , , , , , , , , , , , , , , , , , , , , , , , , ,0015-0,5 28

45 Table 16 - CLC level-3 class areas in CLC06_PT and CLC00_PT. CLC00_PT CLC06_PT Area difference CLC class level 3 Area (ha) % of total area of Cont. Portugal Area (ha) % of total area of Cont. Portugal Absolute (ha) Relative to total area of Cont. Portugal (%) Relative to class area in CLC00_PT (%) , , , , , , , , , , , , , , , , , , , , , , ,001 +2, , , , , , , , , , , , , , ,0 0 0,0000 0, , , , , , , ,4233-3, , , , , , , ,0177-2, , , , , , , , , , , ,0014 0, , , ,0026-0, , , ,0199-0, , , ,0315-0, , , ,1488-1, , , ,0810-1, , , , , , , , , , , , , , , ,0480-2, , , ,0548-1, , , ,2065-8, , , , , , ,1-8 -0,0001-0, , , , , , , , , , , , , , , , , , , ,0006-0, , ,1 0 0,0000 0, , , , , , , ,0081-3, , , , , , , , , , , ,0017-0, , ,0 0 0,0000 0,0 29

46 Considering the third and most detailed level in the CLC nomenclature (Table 16) it can be seen that the classes that occupy a larger portion of the Portuguese Continental territory in 2006 are 324 (Transitional woodland-shrub), 311 (Broad-leaved forest) and 211 (Nonirrigated arable land). The same happens for the CLC00_PT map, reinforcing the importance of the forest and agricultural sectors in Continental Portugal. Within Artificial surfaces, class 112 (Discontinuous urban fabric) is the most abundant, while for Wetlands and Water bodies, classes 421 (Salt marshes) and 512 (Water bodies) are respectively the dominant ones. Finally, it is important to mention that when comparing CLC00_PT and CLC06_PT, the percentages of change per class are not exactly the same as the ones that result from CHA06_PT. This is due to the generalisation procedures applied and also to the fact that the products have different minimum mapping units: whereas CHA06_PT has a MMU of 5 ha, both CLC00_PT and CLC06_PT have a MMU of 25 ha. 30

47 4 Conclusions This report described the production procedures and general results of the CORINE Land Cover 2006 for Continental Portugal. The National Technical team coordinated the production process of the project, carried out during 2008 and 2009 at the premises of the Portuguese Geographic Institute. The production process included visual interpretation of satellite imagery to detect land use and land cover changes in the period from 2000 to 2006, in Continental Portugal, and integration of the resultant product with the CLC00_PT database to create the CLC06_PT map. This process was accompanied by permanent quality control breakpoints to ensure demanded quality standards. A validation protocol was applied to the CLC06_PT map and the estimated overall accuracy was 90,2%, with an absolute precision of 1,3 at the 95% confidence level. The results obtained also show that 7,8% of the original CLC2000-PT database was corrected when producing CLC00_PT, and that 8,6% of the area of Continental Portugal was affected by land use and land cover changes, in the period from 2000 to Forest and seminatural areas, as well as Agricultural areas, continue to be the dominant LULC types in the territory and the main source of change dynamics. 31

48

49 References Anderson, J. R., E. E. Hardy, J. T. Roach and R. E. Witmer, A land use and land cover classification system for use with remote sensor data, Geological Survey Professional Paper 964 (presented in U.S. Geological Survey Circular 671), United States Government Printing Office, Washington. Araújo, A., H. Carrão and M. Caetano, An operational approach for annual land cover mapping at the national scale with MERIS images, in Remote Sensing for a Changing Europe (D. Maktav, editor), IOS Press, Amsterdam, pp Büttner, G., G. Feranec and G. Jaffrain, CORINE land cover nomenclature illustrated guide - addendum 2006 (draft version). Caetano, M., A. Araújo, A. Nunes, V. Nunes and M. Pereira, 2009a. Accuracy assessment of the CORINE Land Cover 2006 map of Continental Portugal, Technical Report, Instituto Geográfico Português. Caetano, M., A. Araújo, V. Nunes and H. Carrão, Accuracy assessment of the High-resolution Built-up Map for Continental Portugal, Technical Report, Instituto Geográfico Português. Caetano, M., V. Nunes and A. Nunes, 2009b. CORINE Land Cover 2000 e 2006 evolução das especificações técnicas, Proceedings of the 6 th National Conference on Cartography and Geodesy (CNCG 2009), 7-8 May 2009, Caldas da Rainha, Portugal, in press. Card, D.H., Using known map category marginal frequencies to improve estimates of thematic map accuracy, Photogrammetric Engineering and Remote Sensing, 48(3): Carrão, H., A. Araújo, P. Gonçalves and M. Caetano, Multitemporal MERIS images for land cover mapping at national scale: the case study of Portugal, International Journal of Remote Sensing, in press. Carrão, H., P. Gonçalves and M. Caetano, Use of intra-annual satellite imagery time-series for land cover characterization purpose, in New Developments and Challenges in Remote Sensing (Z. Bochenek, editor), Millpress, Rotterdam, pp Congalton, R.G. and K. Green, Assessing the accuracy of remotely sensed data: principles and practices, CRC/Lewis Press, Boca Raton. Costa, H., H. Carrão, F. Bação and M. Caetano, Land cover classification in Portugal with multitemporal AWiFS images: a comparative study, in Remote Sensing for a Changing Europe (D. Maktav, editor), IOS Press, Amsterdam, pp Dicks, S. and T. Lo, Evaluation of thematic map accuracy in a land-use and land-cover mapping program, Photogrammetric Engineering and Remote Sensing, 56(9): EEA (European Environment Agency), GMES Fast Track Service on Land Monitoring EEA Project Implementation Plan, Technical Report, EEA. EEA (European Environment Agency), CLC2006 Technical Guidelines, EEA Technical Report No 17/2007, EEA, Copenhagen. IGP (Portuguese Geographic Institute), Informação Cadastral Carta Administrativa Oficial de Portugal, available online at (last accessed: 29 July 2009). Jensen, J.R., Introductory digital image processing: a remote sensing perspective (2 nd edition), Prentice Hall, New Jersey. 33