The document discusses assessments of soil health at large scales for evidence-based decision making. It describes the Land Degradation Surveillance Framework (LDSF), which uses spatially stratified random sampling and a hierarchical structure to assess soil health across a global network of sentinel sites. Earth observation data from satellites can provide information on soil properties and sensitivity to degradation. Assessments need quantifiable metrics that allow for hypothesis testing and be at scales relevant to farmers. They should also integrate social and ecological indicators to understand interactions between systems and resilience.

1. ASSESSMENTS OF SOIL HEALTH AT SCALE FOR
E
V I
D
E N C E
BASED DECISION MAKING
Tor-G. Vågen
World Agroforestry Centre (ICRAF)
Nairobi, KENYA

2. • Indicators of soil health need to be consistent
• Need to be supported by analytical frameworks for modeling and
mapping with high levels of rigour
• Should integrate biophysical and socio-economic indicators across
scales (i.e. in landscapes)
• Diagnostics to assess interactions between social and ecological
systems, including their resilience and socioeconomic drivers of
changes in soil health
To assess soil health at scale

3. The Land Degradation Surveillance Framework (LDSF)
• Spatially stratified random sampling
• Hierarchical structure

4. Global network of LDSF sentinel sites
• > 200 sentinel sites in ~40 countries
• > 30,000 reference plots
• Archive of more than 200,000 soil samples

5. 5
In the LDSF we utilize and build applications
around new EO platforms from the European Space
Agency and established EO platforms from NASA
Open
Data
aws
Earth observation (EO) has significant potential
for assessments of soil health at scale
Open
Data
Open
Data

6. Understanding how the soil properties
and their spatial distribution determine
sensitivity to land degradation – i.e.
the inherent resilience of the system.
Source: Google Maps
For a paper describing the modeling approach:
Vågen, T.-G., Winowiecki, L.A., Abegaz, A., Hadgu, K.M., 2013.
Landsat-based approaches for mapping of land degradation prevalence
and soil functional properties in Ethiopia. Remote Sens. Environ. 134,
266–275. doi:10.1016/j.rse.2013.03.006
Soil pH is high à soil is prone to
degradation even under moderate
levels of disturbance/stress
Example: Soil pH or acidity

7. Source: Google Maps
For a paper describing the modeling approach:
Vågen, T.-G., Winowiecki, L.A., Abegaz, A., Hadgu, K.M., 2013.
Landsat-based approaches for mapping of land degradation prevalence
and soil functional properties in Ethiopia. Remote Sens. Environ. 134,
266–275. doi:10.1016/j.rse.2013.03.006
Soil pH is high à soil is prone to soil
erosion even under moderate levels
of disturbance/degradation
Example: Soil organic carbon (SOC)
Soil organic carbon content is
moderate to high à inherent
resilience is high.
Understanding how the soil properties
and their spatial distribution determine
sensitivity to land degradation – i.e.
the inherent resilience of the system.

8. Land cover and land use
- SATVI based on Landsat 8
• land cover does not necessarily reflect
land degradation status or processes
that drive it
• has implications for both data
requirements and modeling approaches
to create outputs that can be used in a
meaningful way to support decision
making
For a paper describing the modeling approach:
Vågen, T.-G., Winowiecki, L.A., Abegaz, A., Hadgu, K.M., 2013.
Landsat-based approaches for mapping of land degradation prevalence
and soil functional properties in Ethiopia. Remote Sens. Environ. 134,
266–275. doi:10.1016/j.rse.2013.03.006

10. Social
Systems
Ecological
Systems
assessments need to be based on quantifiable metrics
that provide opportunities for hypotheses testing

11. Assessments need to be
spatially explicit and at scales
relevant to farmers or land
managers
Soil erosion based on Landsat 8.
Example from Tigray region, Ethiopia
Source: Google Maps

12. The SHARED approach uses comprehensive facilitation to support interaction with evidence and
co-learning, building long-term relationships to ensure that evidence can be critically evaluated
and interpreted to inform decision-making.
Challenges:
• To make information (evidence) about land
degradation and land-/ecosystem health available to
decision makers and farmers/pastoralists
• To ensure that decision makers use evidence in their
planning and decision making
StakeHolder Approach to Risk-informed and Evidence-based Decision-making

13. Soil organic carbon (SOC) and
soil erosion prevalence.
Laikipia County, Kenya

14. Thank you!
Email: t.vagen@cgiar.org
Asante!