Scalable Geospatial Web Services through Efficient, Online and Near Real-Time Processing of Earth Observation Data

摘要

The current generation of space-borne sensors are generating nearly continuous streams of massive earth observation datasets. These huge multi-modal streams increase at astonishing rates, reaching currently several petabytes in many satellite archives. Shortly, high-resolution multispectral images will be available almost once a week and in some regions twice per week. However, it is estimated that most of datasets in existing archives have never been accessed and processed outside high-end supercomputing and data-center environments. To this end, a scalable geospatial platform has been designed, developed and evaluated for the online and real-time harvesting of valuable information from big earth observation data. The core of our platform consists of the Rasdaman Array Database Management System for big raster data storage, and the Open Geospatial Consortium Web Coverage Processing Service for data querying. The WebGIS client is based on the OpenLayers and GeoExt JavaScript libraries, while advanced remote sensing and computer vision libraries like GDAL, Oreo Toolbox and OpenCV have been integrated as well. Currently, the system is fully covering Greece with LANDSAT 8 multispectral data, from the beginning of the satellite's mission. Datasets are stored and pre-processed automatically in our hardware. The developed system has been validated for the efficient and automated processing of high resolution satellite data and in particular for key geospatial, environmental, agriculture and water engineering applications like precision agriculture, water quality monitoring and land cover mapping.