@inproceedings{8a016e45f17a4aed825b5c54eae10dee,
title = "Integration of remotely sensed inundation extent and high-precision topographic data for mapping inundation depth",
abstract = "Depth is an essential characteristic of flood inundation in hydro-ecological research. Several studies have tried to estimate inundation depth from remotely sensed image and digital elevation model (DEM) data by applying a series of cross section profiles along the centerline of a river reach. This method requires a large amount of manual work in order to identify the centerlines and cross sections, which makes them both unsuitable for automation and inefficient for mapping. This study presents a methodology of rapidly generating flood inundation depth maps automatically using a combination of remotely sensed inundation extent and a high resolution DEM. The proposed approach is tested in a study area located in the Murray-Darling Basin in Australia, and has been proved to be feasible and reliable.",
keywords = "inundation, Landsat, LiDAR DEM, water level",
author = "Chang Huang and Yun Chen and Jianping Wu and Zuoqi Chen and Linyi Li and Rui Liu and Jia Yu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 ; Conference date: 11-08-2014 Through 14-08-2014",
year = "2014",
month = sep,
day = "25",
doi = "10.1109/Agro-Geoinformatics.2014.6910580",
language = "英语",
series = "2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014",
address = "美国",
}