UNCCD 2nd Scientific Conference

1. 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: fbenda@icpac.net

2. AMESD political
framework
• A partnership between the
RECs, ACP Secretariat, AUC and
EU African Union
Commission
• A continental wide, pan-african project
European
for the development of geoinformation Union
services Commission
9th EDF
5 Regional Economic
Communities
CEMAC, ECOWAS, IGAD, IOC,
SADC
+ ACP Secretariat
International partners
(JRC, Eumetsat, WMO, UNEP, UNECA,
FAO)

3. INTRODUCTION TO AMESD
General 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.

4. Regional Partnership and
Associates

5. 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)

6. PRODUCTS DESCRIPTION

7. Frequency/Season of Service 1 product
Season Product 1 Season 2 Product 2
1
Djibouti May-Oct 1 December Feb-May 1 July
Eritrea Jun-Nov 1 January Dec-May 1 July
Ethiopia May-Oct 1 December Feb-May 1 July
Kenya Mar-Sep 1 November Oct-Mar 1 May
Somalia Apr-Aug 1 October Oct-Mar 1 May
Sudan May-Sep 1 November Oct-Mar 1 May
Uganda Feb-Jun 1 August Sep-Dec 1 February
Rwanda Feb-Jun 1 August Sep-Dec 1 February
Burundi Feb-Jun 1 August Sep-Dec 1 February
IGAD Region May-Sep 1 November Oct-Mar 1 May

8. LDIM PROCESSING CHAIN
Input and processed data Intermediate products Principal
LULC products
VEGETATION 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.

9. DATA SOURCE FOR INPUT LAYERS
Input layer Raster/ Data Way of Format Projection Spatial Spatial Frequency
Vector Provider access Coverage Resolution
Baseline 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 2009
Condition data / 84
Spot VGT NDVI Vito e-station Geotiff Geographic IGAD 1km*1km 10day,dekadal
lat/long, WGS Region
84
Rainfall TRMM NASA ftp://trmmo Esri Bil Geographic IGAD 25km*25km Daily
erosivity pen.gsfc.nas lat/long, WGS Region
a.gov/pub/gi 84
s

10. DATA SOURCE FOR INPUT LAYERS
Input layer Raster/ Data Way of Format Projection Spatial Spatial Frequency
Vector Provider access Coverage Resolution
Slope Factor SRTM NASA,NGA http:srtm.csi Esri Grid Geographic IGAD Region 90m*90m Year 2000
.cgiar.org/ lat/long,
WGS 84
Soil 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 2009
economic 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

11. LAND DEGRADATION INDEX MAP:
MODEL USED
•An overlay mathematical geo-processing tool is used to
combine input factors for the Actual LDIM.
ViSKRP ACTUAL LDIM
Weighted Sum

12. ACTUAL LDIM
WEIGHTS
Vegetation Index 40
Rainfall Erosivity 20
Pop. Density 10
Soil Erodibility 30
Slope-LS Factor 50

13. LAND DEGRADATION REGIONAL LEVEL: PRINCIPA
PRODUCTS

14. REGIONAL DYNAMIC PRODUCTS

15. REGIONAL STATIC PRODUCTS

16. 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

17. 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]

18. 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

19. SOIL ERODIBILITY
WEIGHTED SUM
OVERLAY
WHC 1.0
STONINNESS 1.0
TEXTURE - 0.5

20. 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

21. SOCIO ECONOMIC LAYER
HUMAN POP.DENSITY
Combined
W: 1:1
SE = LPD + HPD
LPD = livestock Population densities,
HPD = Human Population densities
LIVESTOCK POP.DENSITY

22. 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.

25. 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.

26. Thank You.
Danke
Merci