Sep 16, 2014 by Carlo Azzarri

HarvestChoice researchers explore the assumption that owning livestock leads to better nutrition and health outcomes for children and other household members in rural Uganda.

Sep 17, 2010 by Jawoo Koo

Many of HarvestChoice spatial datasets are organized and released on 10-km grids. To make spatial analyses easier for researchers (even without having access to GIS platform), we put data layers from multiple themes together in one denormalized big table. This post describes the methodology and presents a prototype.

Layered information on a grid cell

Aug 17, 2010 by Zhe Guo

This surface divides sub-Saharan Africa into market sheds by measuring the nearest city or ‘market’ with a population of 20,000; 50,000; 100,000; 250,000; and 500,000 respectively. Nearness is determined by measuring the least accumulated ‘cost’ or travel time to each market center. The market shed is the total area surrounding each market for which that market has the lowest cost in terms of travel time. Travel time was estimated based on the combination of different spatial data layers, or variables, which affect the time required to travel across to the given points (i.e. cities). Market shed data can be used to determine the number of people or households that are more than likely dependent on a given market center (assuming that most people would travel to the closest market for their needs).