Characterizing land cover change has become a major goal for Earth observation science, with the World Meteorological Organization Global Climate Observing System Implementation Plan calling for repeated observations of global land cover at 30-meter resolution every five years. Although we now have over 30 years of Landsat-class observations, the land science community still lacks the analysis infrastructure to meet the GCOS goal. In response, this project proposes to create the infrastructure for a distributed Land Cover Change Community-based Processing and Analysis System (LC-ComPS).
The LC-ComPS environment is envisioned as a distributed network of processing centers, linked with data archives via Data Grid technology, to allow regional and continental-scale analysis land cover at high resolution.
We will develop and distribute (i) software modules to generate consistent surface reflectance datasets from Landsat-type observations; (ii) software modules to support generalized change detection applications; and (iii) data grid implementation to allow access to multiple satellite data archives. Participants (Goddard, UMD) have already developed most of the components during previous projects; this effort will concentrate on assembling these pieces into a "user-friendly" processing environment that can be replicated a data centers worldwide.
Deployed at UMD Global Change Research Institute.