A WCS-based Approach to Integrate Satellite Imagery Data in Wildfire Simulation

Abstract

This paper describes the integration of multi-dimensional data from satellite sensors in a Civil Protection application that simulates fire spread. The approach uses standard Web Coverage Services from OGC to fetch and process land cover and recently burned areas, available in the form of satellite imagery data previously captured by the MODIS sensor, to automatically generate renovated fuel maps. The proposed architecture is based on rasdaman, a domain-independent database management system (DBMS) that offers a suite of WCS services on top of the DBMS. In the current work we extended rasdaman with facilities to: (i) insert and retrieve multi-layer coverages from WCS, (ii) support new formats, such as HDF, adequate for satellite imagery and multi-layer files, and (iii) support Coordinate Reference Systems. We also demonstrate that it is feasible to use MODIS datasets to automatically compute valuable and regularly updated fuel maps, used as input of fire spread simulations. The results also show that in spite of using inexpensive general and low resolution (500m) MODIS maps, we obtained quite acceptable results when compared with the static ones, which are tailored and higher resolution (80m).

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Cite this paper

@inproceedings{Esteves2012AWA, title={A WCS-based Approach to Integrate Satellite Imagery Data in Wildfire Simulation}, author={Ant{\'o}nio Esteves and Ant{\'o}nio Pina}, booktitle={WEBIST}, year={2012} }