基于遥感影像与地理国情数据的城市内涝灾害评估分析

Assessment of Urban Waterlogging Disaster Based on Remote Sensing Image and Geographical Conditions Data

2016年7月6日,武汉市遭遇罕见特大暴雨,全城渍水严重。本文利用7月8号的高分一号影像数据提取了研究区的渍水区域,结合武汉市第一次地理国情普查数据,对渍水区域内淹没的地类、村庄和街道的数量、面积进行估算,以便为政府部门的灾后补偿和灾后重建工作提供数据支撑;同时,还利用数字高程模型(DEM)数据,对研究区内的渍水高度进行分析,以估算此次暴雨期间水位上涨的高度。研究表明,本次暴雨期间研究区受灾范围最大的地类是坑塘,占受灾总面积的50%;其次为种植土地。渍水区域平均上涨水位为970 mm,重点分布在梁子湖、豹澥湖、牛山湖等大型湖泊周围。

Wuhan suffered a huge rain storm on July 6,2016. It caused a serious waterlogging. To provide decision support for policy makers,this paper proposes an automatic approach for waterlogging area extraction from GF-1 and disaster assessment using geographical conditions data. The results include the area and types of land use affected,as well as the amount of streets with waterlogging. This paper also leverages DEM and geographical conditions data to explore how much the water level risen because of the storm. Our study shows that the largest affected land use is pond,accounting for50 percent of the total damaged area. Planting land came the second. The water level of waterlogging in study area averagely risen 970 mm,and the large lakes,such as Liangzi Lake,Baoxie Lake and Niushan Lake,contributed the most.