addresses non-linear, differential NIR and red radiant transfer through a canopy, and C1, C2 are the coefficients of the aerosol resistance term, which uses the blue band to correct for aerosol influences in the red band. The coefficients adopted in the MODIS-EVI algorithm are; L=1, C1 = 6, C2 = 7.5, and G (gain factor) = 2.5.
accessibility and shows how likely farming households are to be physically integrated with or isolated from markets. Travel time is influenced not only by distance but also by infrastructure quality and road conditions. ▪ Accessibility was determined using a cost-distance function to measure the “cost” in hours to the nearest market center for each location. Travel time was adjusted based on a number of input variables, including road location, road type, elevation, slope, country boundaries, bodies of water, coastline, and land cover.
of the measurement are based on ~2000. (e.g. land cover, settlements/cities, road networks) ▪ Resolution could be coarser for contain country or regional studies. ▪ Not fully harmonized with potential spatial datasets (new roads, different road attributes). ▪ Some parameters of the model need to be improved and refined. ▪ crowdsourcing
networks are updating to for Mali, Kenya, Malawi, Senegal, Uganda, Nigeria, Tanzania, Burundi, Ethiopia, Ghana, ) • Land cover (2009 data with more details land cover classes following LCCS systems and higher spatial resolution) • Human settlements ( 2010 and harmonize across different sources) • Fine tune model parameters
o relaxation of suitability constraints o control of slacks o parameter trail to reproduce results ▪ Additional sub-national crop statistics around 2005 ▪ Improved agricultural_land surface (Fritz et al, IIASA) ▪ Include refined crop distribution maps ▪ Coordinate irrigation information with IMPACT project ▪ Adjustment/correction of cropping systems shares ▪ Generation of 336 global maps – MARIA COMANESCU ( = 42 crops x 2 cropping systems x 4 parameters) ▪ Data query user interface for web-download – MARIA COMANESCU (in trial phase) Slide is provided by Wood-Sichra, Ulrike; and Comanescu,
Design Principles MSExcel revisions no more! Grow organically based on evolving M&E needs and partners’ feedback and capacity – do not overbuild Flexible, adapted to most M&E designs Simple to deploy in the field, no strong dependence on high-speed Internet connectivity Leverage existing CGIAR tools and repositories Openness (to and from 3rd party applications and databases) Powerful Spatial Visualization M&E site stratification & selection. Powerful spatial visualization features to provide rich contextual information, and overlays of local biophysical characteristics with socio-economic data in support of action/control site selection process. Simplified Project Performance Monitoring Streamlined indicator data entry and reporting Slide is provided by Azzarri, Carlo; and Haile, Beliyou
site navigation and filtering Bottom pane: map tools, rendering options (layer legend, base layers, administrative boundaries) Left pane: data toolbar (contextual overlays) Map: Africa RISING megasites and community clusters. Slide is prepared by Azzarri, Carlo; and Haile, Beliyou
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