Abstract：Flood disasters are the most important of the types of natural disasters with high frequency and wide impact, posing a serious threat to social and economic development and the safety of people’s lives and property. The experiment selected Fugou County of Zhoukou City, which was heavy hit by the "7.20" exceptionally heavy rainstorm event in Henan Province as the research area, selected the sentinel-1 and Sentinel-2 images before and after the flood disaster as the main data sources, used the SVM to classify the land use of the sentinel-2 image before the disaster and quickly extracted the water body area during and after the disaster on the Sentinel-1 image based on the SDWI dual polarization water index method, and combined with the GIS to evaluate the disaster situation in the research area. The results show that: ① The overall accuracy of the land use classification map extracted based on the SVM is 95.85%. ② The results of the water body range extracted using the SDWI water body index method show that the water body area during and after the disaster is 36.468 km2 and 18.770 km2,and the overall accuracy is 97.6% and 95.4%. ③ The extraction results show that Caoli Township was the most seriously affected with the maximum water body change area of 12.63 km2.
姜晗兵, 邓文彬. 基于Sentinel-1和Sentinel-2影像的河南扶沟县洪涝灾害遥感监测评估研究[J]. 中国防汛抗旱, 2024, 34(2): 50-55.
JIANG Hanbing, DENG Wenbin. Remote sensing monitoring and evaluation of flood disaster in Fugou County of Henan Province based on Sentinel-1 and Sentinel-2 images. journal1, 2024, 34(2): 50-55.
[1] 周晗. 基于 Sentinel1/2 的斯里兰卡洪涝淹没范围提取研究[D]. 北京:中国科学院大学(中国科学院遥感与数字地球研究所),2018.[2] 郑伟,刘诚.FY-3 卫星洪涝灾害监测应用[J]. 上海航天,2017,34(4):73-78.[3] 宋文龙,杨昆,路京选,等. 水利遥感技术及应用学科研究进展与展 望[J]. 中国防汛抗旱,2022,32(1):34-40.[4] 汤玲英,刘雯,杨东,等. 基于面向对象方法的 Sentinel-1A SAR 在洪 水监测中的应用[J]. 地球信息科学学报,2018,20(3):377-384.[5] 刘宏洁,宋文龙,杨昆,等". 2022.6"珠江流域洪涝灾害应急遥感监 测[J]. 中国防汛抗旱,2023,33(2):20-25.[6] 李加林,曹罗丹,浦瑞良. 洪涝灾害遥感监测评估研究综述[J]. 水利 学报,2014,45(3):253-260.[7] Zhang M M,Li Z,Tian B S,et al.The backscattering characteristics of wetland vegetation and water-level changes detection using multi-mode Sar:a case study[J]. International Journal of Applied Earth Observation and Geoinformation,2016,45(3):1-13.[8] Rahman M R,Thakur P K. Detecting, mapping and analysing of flood water propagation using Synthetic Aperture Radar(SAR)satellite data and Gis:a case study from the Kendrapara District of Orissa State of India[J]. The Egyptian Journal of Remote Sensing and Space Sciences,2018,21(S1):S37-S41.[9] Shu L,Zhou G,Liu D,et al.On-board wavelet based change detection implementation of Sar flood image[C]//Igarss 2019-2019 Ieee In- ternational Geoscience and Remote Sensing Symposium,2019:1502-1505.[10]李景刚,黄诗峰,李纪人.ENVISAT 卫星先进合成孔径雷达数据水体提 取研究——改进的最大类间方差阈值法[J]. 自然灾害学报,2010,19 (3):139-145.[11]孙书腾,刘培,王光彦. 基于多时相主被动遥感协同处理的洪涝灾害 应急监测[J].水利水电技术(中英文),2022,53(9):25-35.[12]孙亚勇,黄诗峰,李纪人,等.Sentinel-1A SAR 数据在缅甸伊洛瓦底 江下游区洪水监测中的应用[J]. 遥感技术与应用,2017,32(2):282-288.[13]田颖,陈卓奇,惠凤鸣,等. 欧空局哨兵卫星 Sentinel-2A/B 数据特征 及应用前景分析[J]. 北京师范大学学报(自然科学版),2019,5(1):57-65.[14]马丽云,李建刚,李帅. 基于 FY-3/MERSI 数据的新疆融雪性洪水灾害 监测[J].国土资源遥感,2015,27(4):73-78.[15]Vapnik V N. An overview of statistical learning theory[J]. IEEE Transactions on Neural Networks,1999,10(5):988-999.[16]国家质量监督检验检疫总局,中国国家标准化管理委员会.土地利用 现状分类:GB/T 21010-2017[S].2017.[17]Mason D C,Giustarini L,García-pintado J,et al. Detection of flooded urban areas in high resolution synthetic aperture radar images using double scattering[J]. International Journal of Ap- plied Earth Observation and Geoinformation,2014,28(3):150-159.[18]贾诗超,薛东剑,李成绕,等. 基于 Sentinel-1 数据的水体信息提取 方法研究[J].人民长江,2019,50(2):213-217.
2024, Vol. 34 
