Transcript of "Muyambi Benda FORTUNATE "Land degradation assessment in the IGAD Region - Its extent and impact""
Land Degradation Assessment in the IGAD Region- Its Extent and Impact Muyambi Fortunate Natural Habitat Thematic Expert IGAD Climate Prediction and Applications Centre African Monitoring of Environment for Sustainable Development Email: email@example.com
AMESD political framework• A partnership between theRECs, ACP Secretariat, AUC andEU African Union Commission• A continental wide, pan-african project Europeanfor the development of geoinformation Unionservices Commission 9th EDF 5 Regional Economic Communities CEMAC, ECOWAS, IGAD, IOC, SADC + ACP Secretariat International partners (JRC, Eumetsat, WMO, UNEP, UNECA, FAO)
INTRODUCTION TO AMESDGeneral overview: Use of Earth observation monitoring technologies in support of development of policies for sustainable development of natural resources.Objective of AMESD IGAD: Establish operational information services to assess land degradation and monitor land cover changes in natural habitats. Improve policy and decision making process in the IGAD region. Identify local hotspots for comprehensive assessment.
SCOPE• Objective of Land Degradation Assessment Identify extent and severity of land degradation at the regional and national levels To identify local hotspots for comprehensive assessment.• Land Degradation: Temporary or permanent reduction in the productive capacity of land to provide ecosystem goods and services (FAO, 2010)• Expected products and outputs: Biannual Maps Bulletins at regional scale with focus on national products (depending on the number of seasons)
Frequency/Season of Service 1 product Season Product 1 Season 2 Product 2 1Djibouti May-Oct 1 December Feb-May 1 JulyEritrea Jun-Nov 1 January Dec-May 1 JulyEthiopia May-Oct 1 December Feb-May 1 JulyKenya Mar-Sep 1 November Oct-Mar 1 MaySomalia Apr-Aug 1 October Oct-Mar 1 MaySudan May-Sep 1 November Oct-Mar 1 MayUganda Feb-Jun 1 August Sep-Dec 1 FebruaryRwanda Feb-Jun 1 August Sep-Dec 1 FebruaryBurundi Feb-Jun 1 August Sep-Dec 1 FebruaryIGAD Region May-Sep 1 November Oct-Mar 1 May
LDIM PROCESSING CHAINInput and processed data Intermediate products Principal LULC productsVEGETATION INDEX VEGETATION COVER AND QUALITY NDVI A1 RAINFALL DEPTH DAILY RAINFALL W1 ACTUAL LDIM DATA RAINFALL EROSIVITY RAINFALL INTENSITY SLOPE STEEPNESS W2 DIGITAL ELEVATION SLOPE FACTOR MODEL A2 SLOPE LENGTH SOIL TEXTURE W3 SOIL DATA SOIL ERODIBILITY WATER HOLDING CAPACITY POTENTIAL LDIM GRAVEL CONTENT POPULATION HUMAN POP. POPULATION W4 COUNTS DENSITY LIVESTOCK POP.
DATA SOURCE FOR INPUT LAYERSInput layer Raster/ Data Way of Format Projection Spatial Spatial Frequency Vector Provider access Coverage ResolutionBaseline Administrative GAUL, ILRI, http/www.di Vector(sha Geographic IGAD - -layer boundaries, DIVAGIS va- pefiles) lat/long, WGS Region roads, rivers, gis.org/gdat 84 towns a;Vegetation GlobCover ESA http://ionia1 Geotiff Geographic IGAD 300m*300m Global 2006,Cover and Land Cover Globcover .esrin.esa.int lat/long, WGS Region 2009Condition data / 84 Spot VGT NDVI Vito e-station Geotiff Geographic IGAD 1km*1km 10day,dekadal lat/long, WGS Region 84Rainfall TRMM NASA ftp://trmmo Esri Bil Geographic IGAD 25km*25km Dailyerosivity pen.gsfc.nas lat/long, WGS Region a.gov/pub/gi 84 s
DATA SOURCE FOR INPUT LAYERSInput layer Raster/ Data Way of Format Projection Spatial Spatial Frequency Vector Provider access Coverage ResolutionSlope Factor SRTM NASA,NGA http:srtm.csi Esri Grid Geographic IGAD Region 90m*90m Year 2000 .cgiar.org/ lat/long, WGS 84Soil HWSD FAO, SOTER http://www. Esri Grid Geographic IGAD Region 1km*1km -erodibility iiasa.ac.at/r lat/long, esearch/LUC WGS 84 /External- World-soil-Socio- Landscan – ORNL http://www. Esri Grid Geographic IGAD Region 1km*1km Year 2009economic Human ornl.gov/sci/ lat/long, Population landscan/ WGS 84 density FAO FAO http://www. Esri Grid Geographic IGAD Region 5km*5km - LIVESTOCK GRIDDED fao.org/geo lat/long, DATA LIVESTOCK network/srv WGS 84 OF THE /en/main.ho WORLD me/GLIHPA
LAND DEGRADATION INDEX MAP: MODEL USED•An overlay mathematical geo-processing tool is used tocombine input factors for the Actual LDIM. ViSKRP ACTUAL LDIM Weighted Sum
ACTUAL LDIM WEIGHTSVegetation Index 40Rainfall Erosivity 20Pop. Density 10 Soil Erodibility 30 Slope-LS Factor 50
LAND DEGRADATION REGIONAL LEVEL: PRINCIPA PRODUCTS
VEGETATION TYPE & CONDITION NDVI • Derived from Spot VGT with a resolution of 1KM. • Seasonal average was computed and reclassified into 5 main classes. LEGEND NOMENCLATURE CLASSES 1. 0.68 – 0.98 VERY GOOD 2. 0.50 – 0.68 GOOD 3. 0.30 – 0.50 NORMAL 4. 0.15 – 0.30 POOR 5. -0.10 – 0.15 VERY POOR
VEGETATION TYPE & CONDITION Land Use Land Cover Land use land cover class aggregation: 1. Forest 2. Agriculture:[ shrubs, bush land, perennial crops] 3. Grassland:[Annual crops, grassland savanna, grassland] 4. Woodland:[Woodland, woodland savanna 5. Bare Soils:[Bare soils, Bare rocks]
RAINFALL EROSIVITY RI R• RD= ∑ Seasonal rainfall amount D• RI= ∑Seasonal rainfall above 40mm per day RE=0.4RD +• Reclassification to 5 classes is 0.6RI done on both RD and RI.• Rainfall erosivity: computed using weighted sum overlay as a R combination of RD and RI. E• RI was found to be the most significant factor that influences the erosiveness of the rainfall.• RE = 0.4RD + 0.6RI
SOIL ERODIBILITY WEIGHTED SUM OVERLAYWHC 1.0STONINNESS 1.0TEXTURE - 0.5
TERRAIN SLOPE AND LENGTH Slope-Length Factor (SL Factor) • SL factor layer (intermediate product) • Susceptibility classes developed 1. Very low susceptibility 2. Low susceptibility 3. Moderate susceptibility 4. High susceptibility 5. Very High susceptibility
SOCIO ECONOMIC LAYERHUMAN POP.DENSITY Combined W: 1:1 SE = LPD + HPD LPD = livestock Population densities, HPD = Human Population densitiesLIVESTOCK POP.DENSITY
LAND DEGRADATION HOTSPOTS• These are areas of socio-economic importance that require close monitoring.• Very High Resolution (Worldview & GeoEye) images of the area of interest are acquired (100 Sq Km).• Some of the areas in Uganda include Moroto, Mpigi and Kabula.
Conclusion• Land degradation index map of the IGAD region focuses on areas that are exposed to nat soil erosion. The importance of the slope, the soil sensitvity and the current state of the l cover observed by the satellite imagery are the most important factors of this assessmen takes into consideration also the highly density populated places and rainfall intensity factors potentially responsible for an increase of the land degradation. Most of the time land degradation generates pressure on cropped areas and as a result it can lead to f insecurity. This land degradation index map has helped warn about the possible food secu problms by giving an index of potential risk of agricultural disturbances on highly expo areas.• According to our assessment, 45% of the IGAD region (10 African countries) is affected considerable degradation. This means that the exposure to this phenomenon is well extend The most extended area of land degradation is located on the East part of IGAD region. A la part of coastal areas appears quite well affected due to steep slopes, highly sensitive soil poor vegetation cover. A bit further from the coastal areas, North and high plateaus of Ethio appear also well concerned by the land degradation. The land degradation is covering also important part of south-west of IGAD region. The eastern part of Kenya, around the rift va and Turkan Lake, the southern part of Uganda and almost all Rwanda and Burundi concerned phenomenon.• The western part of Sudan around Darfur area shows land degradation closely linked to topography. Despite of low population density, the dryness of this area can be put locally part of IGAD in a very critical situation. Finally, the less exposed part of IGAD region is loca in the south of Sudan and in south-east coastal area where the topography is almost flat. T assessment indicates the extent of land degradation in the IGAD region.