The High Performance Database Research Center at Florida International University is leveraging the Hadoop framework, which implements Google's computational paradigm MapReduce and provides distributed file system services, for serving geospatial imagery and to execute spatial queries with heterogeneous predicates. This work is laying the foundation for high-performance geospatial querying. For instance, queries such as "the percentage of Florida state's land-mass that has vegetation" can be computed using basic image processing (map operation) at each image tile, followed by a simple summation (reduce operation) across tiles that comprise the aerial imagery of the Florida land-mass. A potentially infinite number of such semantic queries can thus be computed using the MapReduce paradigm and a large-scale raster imagery dataset. This exploratory work is providing a bridge between geospatial Web services and the MapReduce platform which has demonstrated success in other data-intensive applications.This work is expected to produce a major impact on the field of geospatial data management and especially decision support based on geospatial data, by enabling decision support queries which were not previously practical. This will provide a foundation to enable critical decision support applications in fields such as disaster mitigation and environmental protection.This work is also providing a uniquely comprehensive collection of geospatial data to a broad research community.