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SIMLEZA Site Characterization for Eastern Province of Zambia. Zhe Guo, Carlo Azzarri, Beliyou Haile SIMLEZA - Africa RISING Meeting 28-29 May 2013, Lilongwe, Malawi. Objectives. Understand the spatial pattern and heterogeneity Choose appropriate data layers for stratification
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SIMLEZA Site Characterization for Eastern Province of Zambia Zhe Guo, Carlo Azzarri, Beliyou Haile SIMLEZA - Africa RISING Meeting 28-29 May 2013, Lilongwe, Malawi
Objectives • 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
Data Source: Naomi Kamanga and Walter Mupangwa (N=225) Lundazi Chipata Katete
Source: Munyaradzi Mutenje, MenaleKassie, and KindieFantaye Includes farmers in innovation networks?
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
Little within spatial heterogeneity (based on Land scan but result is the same based on Afripop)
Spatial heterogeneity in rainfall and elevation • Correlation b/n spatial distribution of temperature elevation • Two data layers (9 classes) to stratify SIMLEZA districts
Final Layer 1. Rainfall 772 -850mm 851-950mm 951-1050mm 1051-1241mm
Final Layer 2. Elevation 369-700 m 701-900m 901-1100m 1101-2237m Excluded area - No farmers in this range based on available farmer location
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
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
Source: Munyaradzi Mutenje, MenaleKassie, and KindieFantaye