This document discusses mapping land degradation and sustainable land management (SLM) interventions to support combating desertification. It describes assessing where and when to intervene based on the level of degradation and mapping specific technologies and approaches. The mapping involves assessing land use systems, degradation types and extent, conservation approaches, and their impacts. This provides spatial overviews to identify priority areas and guide the scaling up of effective SLM. Lessons include developing participatory and harmonized databases to inform policy, planning, and monitoring of projects combating land degradation.

1. Assessing and Mapping LD and SLM to
Directly Support the Planning and
Scaling Up of SLM Interventions to
Combat Desertification
Hanspeter Liniger, Godert Van Lynden, Riccardo Biancalani, Lehman
Lindeque, Déthié Soumaré Ndiaye, Gudrun Schwilch, Monica Petri
WOCAT/CDE, FAO, ISRIC, MOA S. Africa, CSE, Senegal

2. When / Where to intervene?
Preventio Mitigation / „Rehab“
n „Cure“ Fotos: H.P. Liniger

3. Which Technology / Approach?  local Decision Support
1 Approach: government SWC-Afforestation for Yellow river
basin, supported by World Bank (PRC-GEF), …
3
1
4
2
4 Technologies
Where? Costs? Impacts? Food security?
Combatting desertification, reducing floods/ DRR?
Adapted to climate change? Photo: H.P. Liniger

4. Scaling-up! Where? regional Decision Support
Starting degradation with
strong degradation trend?
 Prevention / Cure
What to spread?
Where best?
Worst degradation?
 Rehabilitation
What is the
impact???
4

5. Mapping: Land Degradation/Conservation & impacts
Degradation SLM  Where to invest?
Hot spots
Bright spots
Participatory
Expert Assessment
Supported by documents,
surveys,..
Photos: H.P. Liniger

6. Mapping Land Use, Degradation Conservation/SLM
Land Use System (LUS)
Type
Area trend
Intensity trend
Degradation per LUS Conservation/SLM per LUS
Type Name / Group / Measure
Extent (area) Extent (area)
Degree Effectiveness
Rate Effectiveness trend
Impact on ecosystem Impact on ecosystem
services (type and level) services (type and level)
Direct causes
Indirect causes Degradation addressed
Recommendation Source: WOCAT 2009 Questionnaire Mapping

7. L. Lindeque

8. Main degradation types threatening grazing land in the Nama Karoo
(Status indicator)
L. Lindeque

9. L. Lindeque

10. L. Lindeque

11. Rate of land degradation last 10 years (average for all degradation types
related to grazing land)
L. Lindeque

12. Main direct causes for LD - Vhembe
Land Use Class Degradation Type Main causes for LD
Savanna Reduction in Excessive gathering of fuel wood, timber, fencing
vegetation cover and construction material / Excessive numbers of
livestock
Conversion to agriculture
Detrimental effect of Large scale commercial forestry / Forest and
fires grassland fires / Road construction
Quantity / biomass Excessive gathering of fuel wood, timber, fencing
decline and construction material / Excessive numbers of
livestock
Soil erosion by water Floods / Lower infiltration rates – increased
surface runoff / Change of seasonal rainfall
L. Lindeque

13. Main indirect causes for LD - Vhembe
Land Use Class Degradation Type Main Indirect Causes for LD
Savanna Reduction in vegetation cover Population pressure / Land
Tenure / Poverty
Detrimental effect of fires Education, awareness raising, access
to knowledge and support services /
Poverty
Quantity / biomass decline Poverty / Lack of inputs and
infrastructure
Soil erosion by water Lack of inputs and infrastructure /
Education, awareness raising, access
to knowledge and support services /
Poor governance – institutional
arrangements / Land tenure /
Population pressure
L. Lindeque

14. L. Lindeque

15. L. Lindeque

16. Conservation measures – Savanna
Vhembe district
Land use Degradation SLM measures
Savanna Reduction in vegetation Grazing land management: Camping system,
cover rotational grazing, separation of grazing types,
Quantity / biomass adjusting stocking rates, reduction of invasive
decline species
Detrimental effect of Management measures: Controlled burning and
fires fire belts
Soil erosion by water Gully control and rehabilitation: Contour bunds
in combination with vegetative measures (both
trees and grass)
L. Lindeque

17. Effectiveness trend of conservation measures last 10 years
L. Lindeque

18. Reason for an increase in effectiveness trend of conservation measures
(last 10 years)
L. Lindeque

19. Identifying priority areas for intervention
L. Lindeque

20. Where are the hotspots or priority areas for intervention?
High DI values
Low CI values
L. Lindeque

21. What need to be done in land degradation priority areas?
• LADA-WOCAT Assessment methodology is all
about understanding the current LD problems
and analyzing the current responses to LD
problems
• This knowledge and understanding on a
‘lessons learned’ approach will then help to
design suitable, sustainable future options to
address LD problems
L. Lindeque

22. Rwanda Land use database
The LUS database include biophysical, socio-economical,
and livestock and crop use data. Most inputs were provided by NELSAP
M. Petri

23. Comparison Degradation vs conservation
Burundi – chemical degradation
Effectiveness of Land
existing SLM degradation severity
SLM have low effectiveness and Weighted (Extent * degree * rate[normalized])
are not present in certain severely
degraded areas
M. Petri

24. Lessons learned / Improvements
• harmonized LUS/QM database developed through capacity building and
participatory knowledge sharing
• formulate the project intervention strategy, to identify best practices
for SLM in the region for scaling
• inform policy making, planning and budgetary allocations
• use the method for monitoring project impacts
• be used for justifying and developing proposals for catchment's level
interventions.
M. Petri

25. National Desertification Monitoring System NDMS Mongolia
NDMS – Desertification assessment
e.g. Change of Vegetation cover (2001-2011)
 Using MODIS data  degradation & improvements
MSc Thesis Elias Hodel, 2012 1

26. National Desertification Monitoring System NDMS Mongolia
NDMS – Tools for cross-scale applications
MSc Thesis Elias Hodel, 2012

27. National Desertification Monitoring System NDMS Mongolia
NDMS – Monitoring vegetation cover trend (2)
MSc Thesis Elias Hodel, 2012 31

28. National Desertifikation Monitoring System NDMS Mongolia
Khovt
WOCAT-LADA mapping  comparing with Remote Sensing
Soum governor Chandmana
 Support for Pasture User Groups
32

29. What is the potential?
 Defining state of DLD
 Protected areas: fenced, National parks, railway…
Foto: H.P. Liniger
14. April 2013 33

30. National Desertification Monitoring System NDMS Mongolia
Landscape approach
Identifying the potential?
>
>  Depends on where in landscape
Khovt 1
34

31. National Desertification Monitoring System NDMS Mongolia
Model to assess LD / Desertification (Pilot phase)
Include 13 landscape units (LSU) for assessment
Mountains / hilltops (+ Aspect E,N,W,S). >30%
Footslopes (E,S,W,N): 8-30%
Lower gentle slopes (E,S,W,N):
2-8%
Valley floors,
Criteria: Depressions <2 %
•Slope (e.g. 4 categories) / rouhgness
•Aspect
•Altitude
•Surface roughness
Basic assumption:
•Each of the different landscape unit has a different potential
•Trends & state of LD should be analyzed for each LSU separately
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3

32. National Desertification Monitoring System NDMS Mongolia
Model to assess LD / Desertification (Pilot phase)
Landscape Units: 13 1
36

33. National Desertification Monitoring System NDMS Mongolia
14. April 2013
1
37

34. National Desertification Monitoring System NDMS Mongolia
NDMS – Land degradation: forest cover change
Imagery source:
Landsat TM5 2000/2010
(single coverages)
TerraMODIS 2000-2010
(daily coverage)
CDE@SDC/UNCCD December 14, 2012 1

35. Defining state of LD
 Verification in the field (NW of Ulaanbator)
Forest destruction example
MSc Thesis Elias Hodel, 2012 39

36. Mapping Land Use, Degradation Conservation/SLM
Conclusions:
-Value of spatial overview of LD and SLM and its impacts!
-Scale independent method!
-Importance of participatory mapping
-Combination of available data, maps, expert assessment 
user-friendly interactive tool for local & regional mapping
-Role of RS growing yet…
 ground truthing being neglected!
-Value and use of mapping still not sufficiently recognized
-Partnership is Commitment & joy
needed & welcome!
-www.wocat.net
-http://www.fao.org/
nr/lada/
Leverage: 1 … +7!

37. Lessons learned / Improvements
• An multi-country harmonized LUS/QM database has been
developed through capacity building and participatory knowledge
sharing
• Resulting data and maps can now be used to formulate the
project intervention strategy, to identify best practices for
SLM in the region for scaling up and to guide effective and
responsive interventions at various scales
• Data will inform policy making, planning and budgetary
allocations by the concerned technical sectors at district and
transboundary levels and serve as a baseline for more integrated
landscape management approaches
• A potential outcome is the use of the method for monitoring
project impacts
• The process can also be used for justifying and developing
proposals for catchment's level interventions by concerned
communities and districts and for developing more substantive
M. Petri