1. SLM Intervention Impact Assessment Using Remotely Sensed Data: Impact Assessment of the Tana-Beles Integrated Water Resources Development Project
WB Land and Poverty Conference
March 21-23, 2017
Daniel Monchuk, Daniel Ali, Klaus Deininger, and Marguerite Duponchel
The World Bank

2. Tana-Beles Integrated Water Resources Development (TBIWRD) Project 2009-15
Four key components:
Sub-basin Resources Planning and Management
B. Natural Resource Management Investments
Growth-Oriented Investment Facilitation
Project Management

3. 5 critical watersheds - 85,700 ha, 163 micro-watersheds – 526ha average

4. Component B Activities/Interventions
Reported in M&E
Output Soil and water conservation measures undertaken on cultivated lands
Output Gully Treatment and Rehabilitation
Output Degraded land (hillside, grazing and forestry land) treated
Output Existing natural and planted community forests protected and sustainably managed
Output New area planted by community forestry and agro-forestry systems to stabilize landscape and produce fuel wood and timber

5. Soil and water conservation activities/interventions on cultivated land has largest footprint.

6. Impact on the ground? –> Change in Normalized Difference Vegetation Index (NDVI)?

8. Side – Can NDVI (using LS7) pick-up meaningful change?

9. Processing imagery The old way… The new way…
Download 11 years worth of LS7 imagery -> ~2 MONTHS from country office
Batch routines
Filter out clouds, shadows, etc.
Merging raster files
The new way…
Google Earth Engine developer platform -> some javascript -> sit back, relax…
-> 22 images/ year (16 day pass), 4 images span area of interest, 11 years, 250 MB, 4GB/day from country office

10. Sample ~30m pixel resolution Control – 5km buffer
~3 million pixels -> ~99 million obs in panel (11 years, 3seasons/year)
10% sample of pixels
98,182 TBIWRD
201,140 control

11. Remote sensed data NDVI - LS7 imagery used to compute seasonal average
Rainfall - Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS)
Elevation - The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM)
Rainfall - Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) which incorporates 0.05° (~5km) resolution satellite imagery with ground-based weather station data to create gridded rainfall time series
Elevation - The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM)

14. Physical characteristics

15. Identification Panel with pixel fixed-effects
Overall impact of TBIWRD ( )

16. Treatment
the M&E data are used to construct three treatment variables constructed as follows:
Tr1 - an indicator variable identifying micro-watersheds if reporting any activity under any of the outputs listed above (=1) and 0 otherwise;
Tr2 - the ratio of (cumulative) area of cultivated land treated for soil and water conservation (Output 1.2) as a share of total micro-watershed.
Tr3 - the ratio of (cumulative) area of all area treated (Output Output 1.6) to total micro-watershed.

20. Discussion/Conclusions
Strong empirical evidence of positive impact of TBIWRD on NDVI
Magnitude?
Confounding factors/ other considerations
Meaningfully interpreting NDVI (i.e. carbon sequestered) and alternatives (EVI, SAVI, TCT, etc.)
Ex-post evaluation possible
“Easy” to process imagery
Scalable – anywhere, anytime, any size … but need good intervention data (where, what, when)