New approach for land use mapping in the Netherlands (LGN6)
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1 New approach for land use mapping in the Netherlands (LGN6) Gerard Hazeu & Rini Schuiling
2 Content Objectives Background LGN and its history National and European activities (e.g. INSPIRE) Methodology LGN6 Comparison/differences LGN5 LGN6 Monitoring land use changes
3 LGN in brief Raster database (25*25m grid) Update cyclus 3 4 year LGN1 LGN6 (1986, 1992, 1995/1997, 1999/2000, 2003/2004, 2007/2008) Based on satellite images, Top10vector and visual interpretation 39 classes (main classes urban area, forest, water, agricultural land and nature) (last) 6 th version of Landelijk Grondgebruiksbestand Nederland (LGN6) Dutch Land Use database
4 LGN and its history From experimental to highly integrated GIS database From mainly based on satellite imagery to combination of data sources From single to multi temporal classification From 17 to 39 land cover/use classes From 67% to 80 90% accuracy From no to monitoring land use changes for 8 main classes
5 LGN1 LGN2 LGN3 LGN4 LGN5 LGN6
6 National and European setting National user meeting Ministeries, provinces, water boards and environmental agencies Applications (WFD, baseline information, environmental water management,.crop statistics, spatial planning) Limitations, focus and requirements future LGN EU future land monitoring
7 Objective LGN6 Topographical database as starting point Common geometrical standard Integration with other national databases Exchange/tuning of information between databases Not to duplicate work Focus on agricultural and nature areas Backwards Compatible with earlier versions Monitoring land use/cover changes
8 Satellite Top10vector Aerial BBG2003 BKN2007 photograph image Databases (examples) Top10vector (version 2006) Land use database (BBG2003) of CBS Urban Areas (BG2003) Natural Areas (BKN2007) Satellite imagery Landsat 5 TM/IRS P6 (2007/2008) Aerial photographs (2003 and 2006) Statistical data on crops (BRP or LPIS)
9 Methodology (1) Top10vector (2006) Top10_agr LGN6crop Top10_forest BBG/BG2003 Top10_upd Top10_lgn6 Top10_heath Top10_chg Satellite images, aerial photographs, ancillary data BKN dunes Top10vector as starting point Integrate urban areas with Top10vector Select agricultural areas, forest and heath land Change detection 8 monitoring classes Attribute LGN main classes to Top10vector objects in combination with other databases: BBG/BG2003 (grass and forest in primary/secundary urban areas LGN5 (dune heath, mudflats and bogs) Changes (new land cover/use for 8 monitoring classes) LGN5
10 Top10vector Top10vector + BBG2003 Top10_lgn6 Top10_lgn6 + LGN6crop
11 Methodology (2) LGN6crop From feature to raster 25*25m raster Elimination infrastructure Integration other databases to refine LGN classes Crop classification BKN2007 (swamp, dune and natural grasslands) Main roads and railways Houses and buildings Heath and forest classification Final processing (majority ) Products Top10_lgn6 LGN6ras_agr LGN6ras_forest LGN6ras_heath LGN6ras_basis Top10_houses Top10_infra BKN2007 LGN5 LGN6 LGN6crop LGN56 LGN65 LGN6chg LGN6mon
12 Top10_lgn6 LGN6ras_basis Top10crop Top10houses LGN6 Top10_forest BKN2007
13 LGN6crop LGN6mon LGN6chg LGN56 LGN65 Results LGN6 LGN6crop LGN6mon LGN6chg LGN56 LGN65
14 LGN6 2007/ classes Changes: 0.62% or 25,906ha
15 Similarities LGN6 LGN5 Raster database with grid cells of 25*25m Methodology crop classification Top10vector as basis Multi temporal, crop parcel based classification Thematic detail: 39 land use/cover classes Monitoring land use changes
16 Differences between LGN5 LGN6 Methodology Top10vector vs previous LGN version as basis Integration with other databases (urban areas, dune areas, natural grasslands and swamp areas Level of detail & definition of classes Thematic detail New classes (fruit and tree nurseries, subdivision in primary and secundary built up) Renewed classification of forest, heath and dune areas Monitoring Changes and statistics (LGN56 and LGN65)
17 Urban areas LGN5 LGN6
18 Forest and heath land LGN5 LGN6
19 Fruit and tree nurseries LGN5 LGN6
20 Monitoring land use Snapshot versus land use changes Location of land use change Limited number of aggregated land use classes (LGN6mon) Location (LGN6chg) Real versus methodological change Type of land use change Changes from one class to another LGN6mon vs LGN5mon (Statistics vs spatial comparison)
21 Changes and monitoring LGN5 LGN6
22 Statistics monitoring databases LGN6, LGN56, LGN65 and LGN5 classes in ha LGN5 LGN56 LGN65 LGN6 LGN6-LGN5 LGN6-LGN65 7 agricultural land greenhouses orchards forest water urban infrastructure nature
23 Discussion points Timeliness different databases Comparability of versions Monitoring changes versus improvements in methodology a real change between two dates having same nomenclature statistics are difficult to compare between LGN5 LGN6 (LGN56 and LGN65)
24 Future Validation Crops (BRP/LPIS: 59 areas divided over (agricultural) Dutch landscapes; 200,000ha; 84.5%) Changes LGN6 Incorporation in EU land use database Temporal/thematic
25 Thank your for attention Time for questions Wageningen UR
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