1. The Natural Capital/Ecosystem Capital Accounting (ECA) project for Mauritius Production of the urban areas land cover layer from high resolution data on buildings, using smoothing (Gaussian filter) techniques & Land cover change account 2000 – 2010 / Urban sprawl Jean-Louis WEBER Consultant European Environment Agency Scientific Committee Honorary Professor, School of Geography, University of Nottingham jlweber45@gmail.com

2. Introduction The land cover layers for urban areas have been produced using the geo- database of buildings of Statistics Mauritius. It includes data of 2010 and circa 2000. The processing consists in data rasterisation at 10 meters followed by smoothing (SAGA Gis Gaussian filter) in order to agglomerate buildings into « urban areas », thus assimilating small holes and streets. Deanse and dispersed urban areas (e,g, in the countryside) can be mapped. Accounts compare the stocks and change between two dates.

3. The buildings Shapefile

4. The buildings raster (tif) 10 meters x 10 meters

5. The buildings Shp and Raster 10 m

6. Smoothing (blurring) with SAGA Gis/ Grid Filters/ User Defined Filter Input: raster 10 m, values 1 to 101 Filter Matrix (for gaussian blur at 10 pixels radius or 100 m, using a kernel of 21 x 21 cells): here Kernel_21_10

7. Sequence of treatments with SAGA GIS: Input: shapefile, scale circa 1/5000 or finer Raster (tif) at 10 meters Smoothed (Gaussian blur) raster, radius of 100 meters (kernel = 21)

8. The buildings raster smoothed at 100m (values in the neighbourhood)

9. Building raster, 10 m and smoothed at 100m (values in the neighbourhood)

10. Building Shp and smoothed tif (values in the neighbourhood)

11. Agglomeration/generalisation: cells > 20% of the smoothed value NB: cells are of 10 x 10 meters

12. Agglomeration/generalisation: shp and cells > 25% of the smoothed value NB: cells are of 10 x 10 meters – here, the threshold captures dispersed urban

13. Agglomeration/generalisation: shp and cells > 50% of the smoothed value NB: cells are of 10 x 10 meters – here, the threshold eliminates dispersed urban…

14. Provisional conclusion The 20% threshold seems a priori more appropriate for urban areas mapping. The same or different thresholds can be chosen for different classes (e.g. forêts, wetlands…) and in differnt geographical contexts. The urban layer will be overlaid and combined with the other layers on agriculture, forêts, natural zones. Smaller themes will be given priority to the larger ones in order to minimise the relative errors. Adjustments will be done accordingly. The method is to some extent a simulation of visual photo-interpretation.

15. Land cover change account 2000 – 2010 / Urban sprawl Sources: the databases of buildup areas 2010 (LAVIMS) and ~2000

17. Land Cover / M01 Urban 2000

18. Land Cover / M01 Urban 2010

19. Land Cover change / M01 Urban 2000 - 2010

20. Land Cover stock and change / M01 Urban

21. Urban density (%) by Districts 2000

22. Urban density (%) by Districts 2010

23. Urban density (%) by Districts / Increase 2000-2010

24. A first account of Land Cover change/ Urban sprawl 2000-2010 by districts

25. A firs account of Land Cover change/ Urban sprawl 2000-2010

26. M01-Urban 2010 by river catchments