Abstract
Earth Observation has proven to be a synoptic and objective source of information to derive crisis and damage maps. In case of flood events, often characterized by weather conditions which prevent the possibility of exploiting data acquired by optical sensors, synthetic aperture radar (SAR) sensors become the only space-born source of information due to their all-weather capability. In order to assure the delivery of damage maps as soon as possible after a disaster, the access and the exploitation of SAR data must be accelerated and simplified with respect to the current procedures. In this context, two issues needed to be addressed: fast access to large data archives, and provision of near real-time on demand processing services. This paper presents a near real-time SAR processing service to support the mapping of flooded areas. The service exploits Grid technology to manage large volumes of data and to provide the computational resources to cope with SAR processing demanding tasks. The algorithm for the implemented orthorectification of the final products is presented. The validation of the derived products shows a reliable accuracy for co-registration of half a pixel. The geolocation accuracy resulted below 100 m. The service makes a significant contribution to accelerating the access and exploitation of ESA SAR data.
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Notes
According to CEOS definition, Level 3 products are data or retrieved geophysical parameters which have been spatially and/or temporally re-sampled (i.e. derived from Level 1 or 2 products), usually with some completeness and consistency. Such re-sampling may include averaging and compositing.
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Acknowledgments
We are grateful to Giovanna Trianni for her guidance in gathering and understanding the requirements of users of GSE RESPOND and “International Charter Space and Major Disasters”. We thank Olivier Colin and his team, as responsible for the operations of ESA G-POD.
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Cossu, R., Schoepfer, E., Bally, P. et al. Near real-time SAR-based processing to support flood monitoring. J Real-Time Image Proc 4, 205–218 (2009). https://doi.org/10.1007/s11554-009-0114-4
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DOI: https://doi.org/10.1007/s11554-009-0114-4