Remote Sensing Monitoring and Analysis on Heavy Rainstorm Flood in Yongji County, Jilin Province
- DOI
- 10.2991/978-94-6463-194-4_16How to use a DOI?
- Keywords
- flood monitoring; remote sensing; GF-1; SVM; Yongji County
- ABSTRACT
With the continuous development of remote sensing technology, increasingly it is applied in natural disaster monitoring and management, especially, in the field of flood monitoring and warning, flood risk and loss assessment. The three phase Gaofen-1 satellite images before and after the flood in Yongji County were comparatively analyzed, surface conditions before and after floods were extracted by SVM algorithm. And on this basis, the flood damages and impacts were assessed. The results indicated that, affected by the torrential rain and floods on July 13, the affected area was about 138.54km2, residential land and dry land were severely flooded. The process of flood routing can be monitored quickly, accurately and comprehensively by remote sensing technology, which provides scientific basis for flood control and disaster reduction.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiaoyu Liao AU - Walian Du AU - Rina Su PY - 2023 DA - 2023/07/21 TI - Remote Sensing Monitoring and Analysis on Heavy Rainstorm Flood in Yongji County, Jilin Province BT - Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022) PB - Atlantis Press SP - 116 EP - 121 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-194-4_16 DO - 10.2991/978-94-6463-194-4_16 ID - Liao2023 ER -