Assessment land degradation using optical remote sensing and GIS in Saloum estuary, Senegal

Transcription

1 UNIVERSITY CHEIKH ANTA DIOP OF DAKAR GEOLOGY DEPARTEMENT Assessment land degradation using optical remote sensing and GIS in Saloum estuary, Senegal N.M. DIENG, S. FAYE, J. DINIS, M. CAETANO, M. PAINHO University C.A.Diop/Senegal LPAO-SF

2 ESA Tiger Initiative II: Water Assessment in Africa under Global Climate Variability Turning Science into Operations Project 08: Potential vulnerability of the Saloum and Casamance estuary systems: implication of climate change

3 Context (1) Saloum estuary: approximately between longitudes and W, and latitudes and N. Surface: 4,310 km2 Saloum, Djomboss, Bandiala Network of tideways Sangomar Spit

4 Context (2) agriculture (rainfed/irrigation) Salt mining fishing and shellfish harvesting tourism preserve wetlands, mangroves and water/soil resources

5 Context Salinization of soils and water resources Land loss flooding - erosion Degradation of Mangrove

6 increase in the total average temperatures- Dicrease of the precipitation 1400 increased salinity interannual variation of salinity and rainfall for Kaolack from 1927 to 1985 Hypersaline estuary (reverse estuary) 100 Annual rainfall (mm) Annual rainfall (mm) Average annual salinity g / L Sea water salinity Pagès et al., 1990;

7 Main issues Evolution and Extent of degradation Potential impact with regard to CC and sea level rise Mitigation adaptation vs. Economic losses (land, agriculture, mangrove, habitat, fishery

8 Objectives Overall objective Assess consequences of salinization during the last three decades in the Saloum estuary with regard to land, biodiversity and water degradation using remote sensing and GIS Specific objectives identify and map regional and local time serie flood, hydrology, wetlands, land cover/landuses, mangroves, salinity, mud flat, salt marshes; Change detection of land occupation, mangroves and soil degradation with regard to climatic variations.

9 ETHODOLOGY D A T A T R E A T E M N T S R E S U L T S REMOTE SENSING OPTICAL DATA: Landsat (1984, 1992, 1999, 2010 Spot (2006) - Supervised classification with linear discrimination (landsat) - «screen pattern digitizing Change Detection :In particular, a special attention on mangroves degradation and on the development of salt soils that can reflect the level of salinization seasonnal change Hydrogeology/hydrology IN SITU DATA ( eg: water samples, water table, water conductivity etc...) Conventional hydrogeological tools Groundwater and surface water salinity Climate Change impact in both land and water degradation, biodiversity using model

10 METHODOLOGY Landsat: -October November November November 2010 Landsat 5 image November 2010 Spot: - October September 2006

11 Classe types Water body High mangrove Savannah:Agriculture agricultue zone and savannah Denuded and Salty soil (Tan) Low mangrove

12 Change detection % of mangrove (low and high) were lost by immersion 55 % of high mangrove degradate to low mangrove; 6% of low mangrove degradate to barren and salt soil; Sangomar Spit rupture in 1987 forest, savannah, and cultivated land more or less stable

13 1992 Change detection % of mangrove (low and high) and 11% of barren soil lost by immersion 72 % of high mangrove transform to low mangrove; 7 % of low mangrove and 3 % of savannah shift to barren soil; In 1999 due to high precipitation level, flooding increased to 15%

14 1999 Change detection % of mangrove (low and high) and 11% of barren soil lost by immersion were lost by immersion Percentage of high mangrove transformed into low mangrove decrease (43 %) and 14 % of Low mangrove grow to high mangrove Barren soils decreased around Saloum river (4%) due to flooding

15 Land use/ Land cover with higher resolution Land use/land cover of Saloum estuary (spot image, September 2006

16 ONGOING WORK on RS / SENTINEL-2 EXPECTATION Generate elevation model with Radar data for the systems Higher resolution change detection to improve our results using SPOT Sentinel-2 images can offer opportunity specially for short interval time series and higher resolution (tide influence..) evaluate potential risk zones using mainly changes of the physical characteristics and Climate Change Elaborate strategy for adaptation

17 LPAO-SF