Blog entries filtered by: Demographics, Farming
The June 2012 issue of Insights, IFPRI’s quarterly magazine, talks up HarvestChoice’s increasingly popular online tool: MAPPR. So friendly to use that a writer and a graphics designer combined wits to create the MAPPR-generated visuals for the article.
Mapping the global extent of soil constraints to crop growth plays an important role in developing strategies for agricultural production, environmental protection, and sustainable development at regional and global scales. The most widely used dataset is the Soil Fertility Capability Classification System (FCC) developed by Center for International Earth Science Information Network (CIESIN) and the Tropical Agriculture Program of the Earth Institute at Columbia University.
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.
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).
HarvestChoice AgMarketFinder is a web-based geoprocessing GIS application that provides a quick-and-easy access to the spatially-explicit agricultural statistics databases, including crop, livestock, and rural/urban human population. No GIS skill necessary!
HarvestChoice relies heavily on large sets of household survey data to evaluate the economic impact of biophysical productivity responses at the farm level and on target populations.
HarvestChoice Labs uses ESRI ArcGIS Server as a web-based spatial data sharing/exploration platform. This post presents a quick example application using Port Sheds dataset.
Many of HarvestChoice’s spatial analyses are done using raster datasets at various spatial resolutions (e.g., 1 km, 10 km, or 50 km grids).
To facilitate the exchange of HarvestChoice-developed datasets and analysis results with broader geospatial community, a standard/systematic global grid database was developed for multiple spatial resolutions (from 1 degree to 30 arc-second). The new grid database, called HCID, can be used as a key identifier that links and harmonizes various themes of raster datasets as well as aggregates them even at multiple resolutions. This can be helpful not only for GIS analysts but also for researchers who would need to handle the datasets in relational database management systems.