About
This site was inspired by blog posts like this one, and associated discussions regarding land use. Our original goal was to provide some generic tools that let users summarize land types within any arbitrary area of interest, and our map interface makes this easy for any user to do. In addition, our API allows users to programmatically query land use datasets using a simple interface.Since our beta launch last year, we've also begun adding a variety of additional datasets and a series of tools that take advantage of our ability to query large raster datasets in an automated manner. A set of these tools geared towards clients who run EPA air modeling analyses, or who need access to large elevation datasets, are outlined in our Services.
Land Cover Data Sources
- National Land Cover Dataset, 1992
- National Land Cover Dataset, 2001
- Coastal Change Analysis Program, 2006
- The NLCD datasets were merged using GDAL into a single TIFF that covers the continental US.
- The python GDAL library is used to read raster data into Numpy array. A mask array by polygon is created using Matplotlib, and the NLCD is summarized by class.
- The map interface and polygon editing tools are built with OpenLayers. The NLCD overlay is served up by Mapserver and Tilecache. Base layers from Google Maps and Open Street Map are provided for context.
- The website back-end is built on Django. Some queries take advantage of GeoDjango
- The site is hosted on Amazon EC2 virtual servers, with PostGIS and other large datasets on an EBS
- Our clients can access our API programmatically, and take advantage of additional features such as the ability to upload shapefiles for batch-calculating polygons, and access summary results with a private login. Additional analyses (e.g. albedo, bowen ratio, or surface roughness) and datasets (e.g. topography, weather stations) can be integrated into a customized interface, as required.