基于洪水过程的农业洪灾变化遥感快速评估模型及其应用  

FAST ASSESSMET MODEL OF FLOOD HAZARDS BASED ON FLOODING PROCESS AND REMOTE SENSING DATA:A CASE STUDY IN POYANG LAKE REGION

作　　者：汪权方[1,2] 孙佩 王新生[1,2] 汪倩倩[1] 王渊 袁琳 王亚彭[1] 徐慧[1] 陈志杰 魏立飞[1,2] 李中元[1,2] 

机构地区：[1]湖北大学资源环境学院,湖北武汉430062 [2]农业部遥感应用中心武汉分中心,湖北武汉430062

出　　处：《长江流域资源与环境》2017年第11期1831-1842,共12页Resources and Environment in the Yangtze Basin

基　　金：国家自然科学基金项目(41371344;40601003);农业部-农业农村资源监测统计项目(06162130111242026);安徽省智慧城市与地理国情监测重点实验室开放基金(2016-K-02Z)~~

摘　　要：洪涝灾情的准确测度需要同时兼顾淹没区的面积大小和淹水时长信息。利用淹没区内由水和作物等多种地物所组成的"复合水体"不同于水体的波谱时间变化特性,将不同洪灾时期的水体指数和植被指数进行信息复合,以有效凸显水体和洪涝淹没区之间的影像差异,据此进行了灾初期、峰期和中后期等3个时次受淹范围的有效识别。在此基础上,根据洪涝灾情随着淹没时长而加重以及灾区内淹水时长非均匀分布的特性,建立基于淹没时长的受淹面积不等权参与的洪灾扩展动态度指数(Variation Index of Flood,VIF)和区域灾情比较指数(Comparison Index of Flood Disaster,CIFD)两种模型,并将模型应用于鄱阳湖区2016年夏季农业洪涝灾害的时空变化遥感监测。结果显示,应用上述两种模型不仅可以准确获取鄱阳湖区本次农业洪涝灾情的演变趋势,而且能够方便地对比分析区域内不同地方的受灾程度。鄱阳湖区在2016年6月23日~7月25日期间的洪涝灾情具有由弱增强再趋弱的特征,其VIF指数由初始阶段(6月23日~7月9日)的3.75降至后续阶段(7月9日~7月23日)的1.29;鄱阳县是研究区内受灾最严重的区域,其CIFD指数值居于研究区内各受灾县市之首,该县受灾总面积以及多次被淹的灾区面积均高于其他县市。Extent of inundation is a key factor in flood damage assessment. In the previous research on flood damage assessment,flooded regions were often assigned weight coefficients corresponding to the submerged acreage,which actually implied that equal weighting of flooded acreage factor was used in flood damage assessment. However,extent of inundation usually changed during a flood event. For example,one spot may be submerged at the beginning of flooding and then may become non-flooded soon afterwards,while other areas may be submerged for the whole period of a flooding event. Therefore,these areas should be assigned time-weighted inundated acreage to take into account of their differences in inundation duration. Based on this fact,Variation Index of Flood（ VIF） and Comparison Index of Flood Disaster（ CIFD） were proposed to monitor the spatiotemporal characteristics of 2016 summer flood in the Poyang Lake regions. In order to acquire the actual acreage factor,the extent of inundation from 23^rd to June 25^th of July was mapped using GPS-based field investigation and remote sensing data before and after the flooding,including multi-temporal Landsat 8 OLI,GF-1 WFV and Google earth imagery. To resolve the difficulty in remote sensing distinction between water body and the flooded area,image fusion was applied to integrate information from Normalized Difference Vegetation Index,Modified Normalized Difference Water Index（ MNDWI） of the Landsat 8 OLI in the early stage of the flood event and Normalized Difference Water Index（ NDVI） in the latter stage. By doing so,the color differences between water body and the flooded area in the satellite images can be enlarged to have an effective discrimination of these areas.This study revealed that： 1） A total area of 33 329. 28 hm^2 was covered by flood excluding the original extent of the water in the study area. And 81% of flooded land area occurred in counties of Poyang,Yongxiu,Yugan,Duchang,Xinjian,Xingzi and Jinxian,located in the lake region; 2） VIF tnder

关 键 词：洪涝过程 时序遥感影像 特征指数信息复合 洪灾扩展动态度指数 区域灾情比较指数 鄱阳湖区 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]