1. SIMLEZA Site Characterization for Eastern Province of Zambia Zhe Guo, Carlo Azzarri, Beliyou Haile SIMLEZA - Africa RISING Meeting 28-29 May 2013, Lilongwe, Malawi 1

2. Understand the spatial pattern and heterogeneity Choose appropriate data layers for stratification Thus help Better target interventions Identify representative or otherwise appropriate action and control sites Guide scaling-up/scaling-out efforts within, across, and beyond 2 Objectives

3. Data Source: Naomi Kamanga and Walter Mupangwa (N=225) 3 Lundazi Chipata Katete

4. Source: Munyaradzi Mutenje, Menale Kassie, and Kindie Fantaye 4 Includes farmers in innovation networks?

5. Review of Spatial Biophysical and Socio-economic Data Layers ; Afripop Candidate data layers mapped to visualize their spatial distribution Final layers aggregated by classes Results will need refining 5

6. Little within spatial heterogeneity (based on Land scan but result is the same based on Afripop) 6

7. Spatial heterogeneity 7

8. Little within spatial heterogeneity 8

9. 9

10. 10

11. Spatial heterogeneity 11

12. 12 Spatial heterogeneity

13. Spatial heterogeneity in rainfall and elevation Correlation b/n spatial distribution of temperature elevation Two data layers (9 classes) to stratify SIMLEZA districts 13

14. 772 -850mm 851-950mm 951-1050mm 1051-1241mm 14 Final Layer 1. Rainfall

15. 369-700 m 701-900m 901-1100m 1101-2237m 15 Final Layer 2. Elevation Excluded area - No farmers in this range based on available farmer location

16. 16 Final Classification

17. Conclusion and Caveats Candidate layers – population, market access, temperature, LGP, slope, elevation and rainfall Maps based on GIS location of 225 farmers from 7 camps in 3 districts Final layers for stratification - elevation and rainfall; 9 classes Site/Camp stratification:  Ludanzi (Hoya and Vuu): Low R - High E  Chipata (Kapara, Mtaya, and Chanje ): Low R and Medium E; Medium R and Medium E; Medium R and Low E  Katete (Kawalala and Kafumbwe): High R and Medium E Coarse resolution metadata more suitable to global analysis 17

18. Next Steps Update maps based on Feedback from Zambia team Higher-resolution/better data layers from Zambia team Data for all farmers (e.g., could there more than 1 class in Ludanzi: low-low), including from Mesekra Identification of target and control sites Data collection efforts Review of existing data SIMLEZA baseline survey tool 18

19. Thank you!

20. Source: Munyaradzi Mutenje, Menale Kassie, and Kindie Fantaye 20