1. Land-use characterization at continental scales: A methodological framework for GLADA stratification
LADA Stratification Task Force - FAO
(AGLL, SDRN, AGAL, ESAE, ..)
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS

2. -an integral part of the LADA assessment process
Work Plan - LADA
« Stratification »
-an integral part of the LADA assessment process
global
national
8 months
10 months
3 months

3. GLADA « stratification »: Why?
Cost-effective collection and analysis of data
selection of representative sites for the evaluation of LD assessment methodologies
extrapolation of LD status and recommendations of remedial actions (local >> national >> global)
Insights on the causative factors for land-degradation “hot” & “bright” spots observed using GLADA regional-scale assessment methodologies
NDVI trends analysis (ISRIC)
Rational spatial allocation of remedial measures as a function of local conditions

4. Existing schemes HOLRIDGE Main criteria: climate & vegetation
Source: USGS 0.5 °, 1989
Main criteria: climate & vegetation
Limited value for LADA purposes

5. Existing schemes Holdridge (Leemans) Ecoregion (Bailey)
Main criteria:
temperature
vegetation
Limited value for LADA purposes
Holdridge (Leemans)
Ecoregion
(Bailey)
World ecosystems
(Olson)
Biomes
(WWF)
Ecological Zones
(FAO-FORM)

6. ‘Regional’ farming system map
Regional study; generalized boundaries
Lengthy iterative process: expert knowledge & use of selected biophysical data for guidance
Criteria
resource base
enterprise (land-use) patterns
household livelihoods & constraints
Farming systems & Poverty- 2001
FAO initiative to improve detail
Task Force on subnational land use - SPAT

7. GLADA « stratification »: How ?
Divide an area into regions which have similar characteristics of direct relevance to LADA
susceptibility to land degradation
inherent biophysical characteristics of the resources base supporting livelihoods
land-use purpose and management practices
human influences on the resources base
socio-economic context
major factors influencing the choice of land-use management practices
NOTE
Regions are tailored to LADA requirements; different from existing “ecological” maps

8. landscape assessment methodologies
1- LD susceptibility
Stratify using biophysical characteristics which strongly influence the range of possible land uses. E.g.
climate
landform/ geology/ soils
vegetation
access to groundwater
.....
Process and simplify existing data in order to highlight
inherent susceptibility to LD (natural & human-induced processes)
thresholds in the above characteristics which often characterize major differences in land uses
(e.g. from previous studies Farming systems; GAEZ, TERRASTAT, ..)
REVIEW
available data
landscape assessment methodologies

9. Length of growing period, LGP
Moisture, Temperature & Heat strongly influence plant growth & development (crop production),
Spatially correlated with livestock distribution
T (mean)>5deg; P > 0.5 PET
<60 days: irrigation necessary
Source: IIASA FAO;
0.5° spatial resolution
Intervals after TERRASTAT

10. Thermal regime Reclassify
to account for differences in the thermal requirements of crops
Reclassify
Thermal climates
Tropics
Subtropics, summer rainfall
Subtropics, winter rainfall
Tropics: 12m T>18ºC
Sub-tropics: >1m 5< T>18º
Temperate: >1m T>18º; >4m T <10º
Boreal: >1m T<5º; >1 to <4m T>10º
Polar Arctic: 12m T <10º
Source: IIASA – FAO
0.5° resolution

11. Moisture, Temp., Thermal regime
Class 1
Sub-humid areas
SubTropics 2
Moist semi-arid areas 3
Dry semi-arid areas 4
Arid areas 5
Hyper Arid areas 6
Tropics 7 8 9 10 11
Humid areas 12
Perhumid areas 13 14
LGP
Thermal climate
0.5° resolution

12. Landform: Slope and relief
strong influences on erosion potential;
limits to mechanized agriculture
Reclassification
Level land
Sloping land
Source: AGLL, FAO
Original scale : 1:5,000,000
(map under review)

13. Landform: Elevation
strong correlations to climate, and potential land uses m m
> 1500 m
Intervals based on regional farming systems classification - after Dixon et al., 2001
Source: SRTM
Original resolution 90m

14. Slope, relief, elevation
Slope & elevation
Level land, m
Level land, m
Level land, >1500 m
Sloping and steep land, m
Sloping and steep land, m
Sloping and steep land, >1500 m
5’ resolution

15. Land cover
Reclassify GLC2000 into limited number of land-cover classes that strongly influence or reflect major types of land uses
Global land cover
Forest
Regularly flooded
Agriculture and mixed agriculture
Shrub and Herbaceous & sparse shrub
Bare & artificial areas
0.5° resolution

16. Resources base: spatial analysis
Input Data
Reclassification
Intermediate outputs
Final Output
LGP IIASA-FAO
Thermal climate IIASA-FAO
Resources base
SRTM DEM (GLCN)
Landform
Vegetation
GLC2000

17. Extracts from regional map
Resources base
climate (14)
LGP
thermal regime
landform (6)
slope
elevation
land cover (5)
14 x 6 x 5 = 420 possible classes
LADA relevant properties highlighted
Each RB unit possibly associated with different land uses
NEXT: Differentiate units on the basis of land uses (i.e. sub classification)
Are RB strata sufficiently detailed for national LADA purposes?

18. Resources base vs. regional FS
‘Resources base’ units

19. hierarchical classification
Resources Base
Generalized small scale map
(multiple levels of aggregation possible)
visual communication
original data retained for subsequent analyses
hierarchical classification

20. Processing of data on Land use purpose and practices
Objective: Sub classify ‘Resources Base’ units taking into consideration differences in land uses
Land use:
Socio-economic purpose(s) of human activities and the land management required to obtain desired goods and services

21. Crop production & management
Spatial reallocation of subnational crop statistics (IFPRI)
Reallocation Criteria
statistics (AGROMAPS; FAOSTAT)
land cover
crop suitability
...
Reporting units
other crops
5690 admin2 subdivisions
metric tons per pixel
5’ resolution

22. Crop groups Oil crops Cereals Root crops Sugar crops Pulses
soybean,
groundnuts, other oil crops
wheat, rice,
maize, barley,
millet, sorghum
potato, cassava
sweet potato and yams
Sugar crops
Pulses
sugar cane, sugar beets
dry beans,
other pulses
Variable threshold applied based on data distribution

23. Crop production & management
Major crop groups
No significant crops
cereals
cereals,oil crops
cereals,oil crops,pulses
cereals,oil crops,pulses,root crops
cereals,oil crops,pulses,root crops,stimulant crops
cereals,oil crops,pulses,root crops,stimulant crops,sugar crops
cereals,oil crops,pulses,root crops,sugar crops
cereals,oil crops,pulses,stimulant crops
cereals,oil crops,pulses,stimulant crops,sugar crops
cereals,oil crops,pulses,sugar crops
cereals,oil crops,root crops
cereals,oil crops,root crops,stimulant crops
cereals,oil crops,root crops,stimulant crops,sugar crops
cereals,oil crops,root crops,sugar crops
cereals,oil crops,stimulant crops
cereals,oil crops,stimulant crops,sugar crops
cereals,oil crops,sugar crops
cereals,pulses
cereals,pulses,root crops
cereals,pulses,root crops,stimulant crops
cereals,pulses,root crops,stimulant crops,sugar crops
cereals,pulses,root crops,sugar crops
cereals,pulses,stimulant crops
cereals,pulses,stimulant crops,sugar crops
cereals,pulses,sugar crops
cereals,root crops
cereals,root crops,stimulant crops
cereals,root crops,stimulant crops,sugar crops
cereals,root crops,sugar crops
cereals,stimulant crops
cereals,stimulant crops,sugar crops
cereals,sugar crops
oil crops
oil crops,pulses
oil crops,pulses,root crops
oil crops,pulses,root crops,stimulant crops
oil crops,pulses,root crops,stimulant crops,sugar crops
oil crops,pulses,root crops,sugar crops
oil crops,pulses,stimulant crops
oil crops,pulses,stimulant crops,sugar crops
oil crops,pulses,sugar crops
oil crops,root crops
oil crops,root crops,stimulant crops
oil crops,root crops,stimulant crops,sugar crops
oil crops,root crops,sugar crops
oil crops,stimulant crops
oil crops,stimulant crops,sugar crops
oil crops,sugar crops
pulses
pulses,root crops
pulses,root crops,stimulant crops,
pulses,root crops,stimulant crops,sugar crops
pulses,root crops,sugar crops
pulses,stimulant crops
pulses,stimulant crops,sugar crops
pulses,sugar crops
root crops
root crops,stimulant crops
root crops,stimulant crops,sugar crops
root crops,sugar crops
stimulant crops
stimulant crops,sugar crops
sugar crops
(work in progress)

24. Major crop groups - TUNISIA

25. Major crop groups - Senegal

26. Number of cattle per pixel
Livestock production
Number of cattle per pixel
source GLIPHA - FAO
0.5° resolution (~ 55km)
Modeling criteria
statistics (FAOSTAT)
climate
...
Other data available:
sheep
pigs
small ruminants

27. Livestock production cattle Calculation:
inputs: livestock systems map, population, cattle number
cattle density per livestock systems / population density per livestock system

28. Crop & livestock production zones
Cropland and livestock
Cropland
Cropland with high livestock presence
Cropland with some livestock
High livestock presence
No cropland and livestock presence
Some livestock

29. Resources base & land use
Resources base (thermal climate, LGP, elevation, land cover, landform)
land use (crop & livestock production)
Further sub classification possible
land management (irrigation, protected areas, ..)
socio-economic factors
(population density, access to land/ markets, ...)
actual land uses influenced by many different local factors

30. Crop production & management
Irrigation: a land management factor
Area equipped for irrigation (%)
source AQUASTAT (2006)
5’ resolution

31. Protected Areas a land management factor regional protected areas
international protected areas
national protected areas
World Commission on Protected Areas (IUCN-UNEP)

32. Concluding remarks Study in progress; Guided by an Internal Task Force
Potential useful where suitable national stratification schemes for LADA purposes do not already exist
Methodological refinements to be based on feedback
Feedback: LADA countries & institutions (network)
Assessment of validity of GLADA stratification
Harmonization with national level data
Proposals for improvement of GLADA stratification
Participation in methodological development
On-going evaluation of a national stratification framework (CSE)
involve other institutions (e.g CGIAR – ILRI, IFPRI, CIAT..)
participative assessment of GLADA methodologies

33. Concluding remarks Global vs national stratification
Global level approach: multiple simplifications appropriate for continental scale map
Potentially significant variations at national level could be masked.
Use appropriately detailed data for national stratification and planning of LADA activities
However, the stratification framework (methodological approach) remains the same in both cases
General agreement between national & global-level strata

34. National stratification Case study - Senegal
Towards a methodological framework
National stratification Case study - Senegal
Approach and results currently under local evaluation by CSE

35. GLADA « stratification »: How ?
Divide an area into regions which have similar characteristics of direct relevance to LADA
biophysical characteristics
- inherent biophysical characteristics of the resources base supporting livelihoods
land-use purpose and management practices
human influences on the resources base
socio-economic context
major factors influencing the choice of land-use management practices
NOTE
Regions are tailored to LADA requirements; different from existing “ecological” maps

36. ‘Regional’ farming system map
Regional study; generalized boundaries
Lengthy iterative process: expert knowledge & use of selected biophysical data for guidance
Criteria
resource base
enterprise (land-use) patterns
household livelihoods & constraints
Farming systems & Poverty- 2001
FAO initiative to improve detail
Task Force on subnational land use - SPAT

37. Caractérisation des zones:
LUT/FS parameters
select key data sets for local conditions
data availability – a possible constraint

38. Procédure d’intégration spatiale

39. Base des ressources
Derived from Land cover, LGP, DEM

40. key distinguishing characteristics of regional farming systems - SSA

41. key distinguishing characteristics of regional farming systems - SSA

42. Arbre de décision
Hauts plateaux pérennes O N
Mixte maïs
Mixte Tempéré des hauts plateaux
Systèmes des hauts plateaux
Cultures arboricoles
industrielles pérennes
Présence
significative
de bovin
Maïs
Tempéré des hauts plateaux
Hauts plateaux >800 m
Présence de
bétail
Départ
Dominance maïs
Dominance
petits grains
céréales à
Autres hauts plateaux
Clairsemé
Faible densité
de population rurale + Aride
Pastoral
des cultures
> T1 (bétail en grande quantité)
≥ C1 (élevée)
Agro-pastoral
< C1 (faible)
Bétail dominant
Riz arbre
Axé sur la foret
Bétail & cultures
Axé sur les arbres
d’arbres
Riz dominant
≤ T 1 (un peu de bétail)
Présence de terres
en culture
Importance du
Présence significative
de tubercules
de céréales et
tubercules
Tubercules
Céréales & tubercules
Autres terres cultivées
des tubercules
Mixtes tubercules
Mixtes céréales & tubercules
< T2 (non significative)
≥ T2 (significative)
Pastoral (faible intensité)
non significative
Tubercules-céréales
Autres terres cultivées mixtes
Mixtes céréales-tubercules
Zones
marécageuses
Terres marécageuses avec un peu de culture du riz
Terres marécageuses
Axé sur les terres marécageuses
Culture
dominante
riz
Systèmes régionaux de production agricole – Afrique sub-saharienne

43. Systèmes de production agricole
validate!

44. Systèmes de production agricole

45. Pourquoi une « stratification »
Zones homogènes d’utilisation des terres
Adapté aux besoins en information de LADA
Zone D P S I R
Niayes
Vallée
.....
participative
multi disciplinary
multi stakeholder
Planification
Répartition rationnelle des mesures de redressement en fonction des conditions locales
Évaluation de la dégradation des terres
Faciliter un échantillonnage rentable de la collecte/analyse des données
Choix de sites ‘représentatifs’ pour l’évaluation des méthodologies
Extrapolation des résultats (local >>> national >>> mondial)
Pour « expliquer » les origines des variations spatiales de la dégradation des terres observées à différentes échelles (locale >>> nationale >>> mondiale)

46. Concluding remarks Study in progress; Guided by an Internal Task Force
Potential useful where suitable national stratification schemes for LADA purposes do not already exist
Methodological refinements to be based on feedback
Feedback: LADA countries & institutions (network)
Assessment of validity of GLADA stratification
Harmonization with national level data
Proposals for improvement of GLADA stratification
Participation in methodological development
On-going evaluation of a national stratification framework (CSE)
involve other institutions (e.g CGIAR – ILRI, IFPRI, CIAT..)
participative assessment of GLADA methodologies

47. Concluding remarks Global vs national stratification
Global level approach: multiple simplifications appropriate for continental scale map
Potentially significant variations at national level could be masked.
Use appropriately detailed data for national stratification and planning of LADA activities
availability of suitable data??
However, the stratification framework (methodological approach) remains the same in both cases
General agreement between national & global-level strata