ef107065-aaa8-4e7d-895c-dc278a26a1f6 SANBI The Metadata Manager +27 21 799 8738 Kirstenbosch Research Centre Cape Town Claremont 7735 South Africa bgishelp@sanbi.org.za 2017-07-03T09:28:22 SANS 1878 FGDC-STD-001-1998 WGS 1984 Archived National Wetland Types 2010 1.0 This layer maps the distribution of wetlands and their types This data is developed for improving conservation plans and prioritization for biodiversity purposes of wetlands, natural water features, artificial water features including dams. Developed under National Freshwater Ecosystem Priority Areas a national wetland conservation planning. Namhla Mbona SANBI Project Manager National wetland inventory 0128435200 2 Cussonia Avenue, Brumeria Pretoria 0186 South Africa n.mbona@sanbi.org.za wetlands South Africa Pretoria SANBI 50000 environment 2016-01-01 16.474175 32.882392 -34.821463 -22.124687 SANBI bgishelp@sanbi.org.za ZIP 1 http://bgismaps.sanbi.org/server/rest/services/BGIS_Projects WWW:LINK-1.0-http--link A list of services published are available at this URL. BGIS Map Services http://bgis.sanbi.org/SpatialDataset/Detail/253 WWW:LINK-1.0-http--related A list of spatial data-sets are available at this URL. BGIS Spatial Datasets Citation: Van Deventer et al. 2010. Using landscape data to classify wetlands for country-wide conservation planning. In press. National Freshwater Ecosystems Priority Areas (NFEPA) Wetland Types for South Africa The final (September 2009) version of the National Wetland Classification System (NWCS) has been adopted for the NFEPA and NSBA 2010 projects, and preliminary automation of the classification system has been undertaken (up to Level 4A) for the NFEPA project, using i.a. the Riversdale Plain area that was mapped as part of the C.A.P.E. Fine-scale Planning as a test case. The approach that was taken builds on that followed by Amis (2009) but rather than applying the TPI approach, the landform tool (part of the Topography Tools for ArcGIS 9.3 Suite written by Thomas Dilts, 2009, available from http://arcscripts.esri.com) was used to distinguish between different broad-scale landforms at a national scale. TPI's allow the setting of only one neighborhood size, which is problematic in assessing the regional context of individual landforms. The landform tool used in the preliminary automation for the NFEPA project allows for the setting of a local and regional neighborhood sizes or search distances, which enables an improved assessment of the landscape setting of wetlands. In order to take the topographic variability of the country into account in assigning landform classes, different 'local neighborhood thresholds' were used for each of the Geomorphic Provinces in the country (after Partridge et al. 2009), based on the maximum valley width for the Geomorphic Province plus 1 km in each case. The 'regional neighborhood threshold' was based on the width between tertiary catchment interfluves plus 1 km. The ten default landform classes that the landform tool generates were then each translated into one of the four Landscape Units at Level 3 of the NWCS (Table 1). Table 1: Translation between the ten landform classes generated by the GIS "landform tool" and the four Landscape Unit categories at Level 3 of the NWCS, as used in the preliminary automation of the classification system undertaken for the NFEPA project [taken from Van Deventer et al., 2009] Landform class NWCS Level 3A HGM Type 1. Canyons, deeply incised streams - Valley floor 2. Midslope drainages, shallow valleys - Slope 3. Upland drainages, headwaters - Slope 4. U-shaped valleys - Slope 5. Plains - Plain 6. Open slopes - Slope 7. Upper slopes - Slope 8. Local ridges / hills in valleys - Bench 9. Midslope ridges, small hills in plains - Slope 10. Mountain tops, high ridges - Bench For the automation of wetland classification to Level 4A according to the NWCS for the NFEPA project, ancillary data was used to classify the wetlands. An initial assessment of the accuracy of the resulting wetland classification was undertaken in a workshop using C.A.P.E. Fine-scale Planning wetland types and expert knowledge. Preliminary results from this assessment suggest that, while there were some discrepancies (as expected), there was generally a satisfactory level of agreement between the automated and manual (desktop-based) classifications of wetlands, particularly if it is considered at a national scale as a guideline or framework. Discrepancies need to be investigated in the field, because in some instances they may be a result of the automated classification providing a better depiction of reality than what the C.A.P.E. Fine-scale Planning Project could glean from aerial photographs and satellite imagery. SANBI (2009). Further Development of a Proposed National Wetland Classification System for South Africa. Primary Project Report. Prepared by the Freshwater Consulting Group (FCG) for the South African National Biodiversity Institute (SANBI). Citation: Van Deventer et al. 2010. Using landscape data to classify wetlands for country-wide conservation planning. In press. Available documentation: On NFEPA report