Remote sensing approaches to improving aid targeting and understanding aid effectiveness
This project aims to develop and test remote-sensing based approaches to gathering two typesof aid-relevant data: data on agricultural productivity and data on household assets, with a focus on Sub-Saharan Africa. The work will combine new high-resolution satellite imagery with household survey data to develop algorithms to measure crop yields and key household assets remotely (i.e. from space), with the household survey data providing the “ground truth” with which to train the algorithms. The team's proposed work builds on existing field data collection on-going in Western Kenya, on collaborative data-collection efforts with the World Bank’s DIME and LSMS teams in Uganda and Rwanda, and on an excellent working relationship with Skybox, a high-resolution satellite company recently acquired by Google who has committed to bi-weekly imaging of the project's field sites in Kenya, Uganda, and Rwanda over the next year.