Improved Flood Mapping Based on the Fusion of Multiple Satellite Data Sources and In-Situ Data

Authors

Y.-J. Kwak, R. Pelich, J. Park, and W. Takeuchi

Reference

in 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, SPAIN, 22-27 July, pp. 3521-3523, 2018

Description

For high accuracy flood mapping, an algorithm that integrates multiple satellite data sources is essential to maximize the sensor ability and compensate the limitations of optical and SAR data. The main objective of this study is to propose an algorithm of dynamic flood detection using optical and Synthetic Aperture Radar (SAR) images that compares and combines two different statistical thresholding approaches. To improve the flood detection accuracy, image fusion technique was investigated to maximize the utilization of calibrated and optimized flood maps as the integrated flood detection approach. To showcase the advantages of the proposed methodology, we employ MODIS, Landsat-8 and Sentinel-1A images acquired over a challenging area along the Brahmaputra River where flood events often occur.

Link

doi:10.1109/IGARSS.2018.8517336