PROCESSING BIG REMOTE SENSING DATA FOR FAST FLOOD DETECTION IN A DISTRIBUTED COMPUTING ENVIRONMENT

Olasz, A.; Kristóf, D.; Nguyen Thai, B.; Belényesi, M.; Giachetta, R.

The Earth observation (EO) missions of the space agencies and space industry (ESA, NASA, national and commercial companies) are evolving as never before. These missions aim to develop and launch next-generation series of satellites and sensors and often provide huge amounts of data, even free of charge, to enable novel monitoring services. The wide geospatial sector is targeted to handle new challenges to store, process and visualize these geospatial data, reaching the level of Big Data by their volume, variety, velocity, along with the need of multi-source spatio-temporal geospatial data processing. Handling and analysis of remote sensing data has always been a cumbersome task due to the ever-increasing size and frequency of collected information. This paper presents the achievements of the IQmulus EU FP7 research and development project with respect to processing and analysis of geospatial big data in the context of flood and waterlogging detection.

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Olasz, A. / Kristóf, D. / Nguyen Thai, B. / et al: PROCESSING BIG REMOTE SENSING DATA FOR FAST FLOOD DETECTION IN A DISTRIBUTED COMPUTING ENVIRONMENT. 2017. Copernicus Publications.

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