耕地暴雨灾情动态信息的遥感提取  

Remote Sensing Extraction of Rainstorm Disaster Dynamic Information of Cultivated Land

作　　者：郭旭东[1] 苏亚丽 吴长江 陈瑜琦[1] 雷莉萍 廖静娟 汪晓帆[1] 张衍毓[1] 

机构地区：[1]中国土地勘测规划院国土资源部土地利用重点实验室,北京100035 [2]中国科学院遥感与数字地球研究所数字地球重点实验室,北京100094 [3]西安科技大学研究生院,陕西西安710054

出　　处：《地理空间信息》2018年第3期57-60,共4页Geospatial Information

基　　金：国家重点研发计划资助项目(2016YFB0501505);国土资源部土地利用重点实验室开放基金资助项目(KLLU201604)

摘　　要：根据暴雨降水天气引起的灾害信息特征,利用基于卫星遥感观测的植被指数NDVI时序数据变化检测方法,在空间和时间上提取了暴雨灾害受灾动态信息。不同于常规的仅提取受灾空间信息的方法,该方法还能提取灾害开始和灾害影响过程中的时间信息。以2016年7月发生暴雨灾害的安徽省巢湖地区为实验区,利用NDVI时序数据进行了应用实验验证。结果表明,利用该方法可有效提取常规受淹、受灾强度的空间信息;结合对应年降水的时间变化特征发现,该方法提取的受灾开始时间数据揭示了持续强降水导致的土壤水分饱和对作物生长的影响,能为国家灾害救助和灾后耕地恢复提供决策依据。Aiming to know how long and how much the farmland inundated due to the rainstorm disaster, a feasible approach for detecting dynamic situation of rainstorm disaster was proposed using time-series NDVI obtained by MODIS in this paper. Using difference of multi-temporal NDVI values between the disaster year and normal year in the past, the disaster information including the starting period, length, and recovery situation of the inundated farmland suffered rainstorm were detected in the research area located at Chaohu District, Anhui Province. As a result, the proposed approach using time-series NDVI is facilitate and operative, and can provide the information which reveals dynamic process of disaster caused by continuous heavy rain or rainstorm through crop growing and soil moisture saturation in farmland. This information is significant to support the decision for recovery of farmland and governmental subsidies for crop loss.

关 键 词：暴雨 灾情动态 遥感 多时相 

分 类 号：P237[天文地球—摄影测量与遥感]