遥感
计算机科学
大洪水
数据处理
链条(单位)
环境科学
地质学
数据库
地理
考古
物理
天文
作者
André Twele,Wenxi Cao,Simon Plank,Sandro Martinis
标识
DOI:10.1080/01431161.2016.1192304
摘要
This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-realtime (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows derivinging time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0% and 96.1% and Cohen’s kappa coefficients (κ) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.
科研通智能强力驱动
Strongly Powered by AbleSci AI