An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data
An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data
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DOI：
10.1080/01431160110114484
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发表时间：
2002-09-01
影响因子：
3.4
通讯作者：
Mulcahy, KA
中科院分区：
文献类型：
--
作者：
Wang, Y;Colby, JD;Mulcahy, KA
本文介绍了一种经济有效的沿海洪泛区洪泛范围制图方法。该方法是基于一对陆地卫星7号专题成像仪（TM）图像（洪水事件之前和期间）的水与非水目标的反射率特征，以及使用数字高程模型（DEM）数据模拟洪水。通过有限的地面观测，验证了从这一分析得出的大多数洪水和非洪水地区。仅利用TM数据，1999年9月30日北卡罗来纳州皮特县的总淹没面积为237.9 km（2），占该县总面积的14.0%。这个数字可能很低，因为低估了密集植被树冠下的洪水面积。为了进一步调查这种低估，一个子集的面积覆盖四个中央地形四边形，格林维尔地区，在皮特县被选中。通过将DEM数据添加到格林维尔地区的洪水制图分析中，发现总洪水面积为98.6 km（2）（研究面积为593.9 km（2））或16.5%。在格林维尔研究区，受洪水影响最大的三个土地利用和土地覆盖类别是低地森林/硬木沼泽（32.7 km（2））、南部黄松（28.8 km（2））和耕地（19.1 km（2））。它们的总淹没面积为80.6 km（2）或81.7%的总淹没面积在本研究区域内。DEM数据有助于识别发生在森林树冠下的洪水，特别是在低地森林和硬木沼泽。该方法是可靠的，可以迅速应用于其他沿海洪泛区使用的数据，是相对容易获得和分析，并在一个合理的成本。这种方法在地形相对平坦的大空间范围的区域也应该很好地工作。
An efficient and economical method for mapping flooding extent in a coastal floodplain is described. This method was based on the reflectance features of water versus non-water targets on a pair of Landsat 7 Thematic Mapper (TM) images ( before and during the flood event), as well as modelling inundation using Digital Elevation Model (DEM) data. Using limited ground observation, most flooded and non-flooded areas derived from this analysis were verified. Utilizing only TM data, the total flooded areas in Pitt County, North Carolina on 30 September 1999 was 237.9 km(2) or 14.0% of the total county area. This number could be low due to the underestimation of the flooded areas beneath dense vegetation canopies. To further investigate this underestimation, a subset of the area covering the four central topographic quadrangles, the Greenville area, in Pitt County was selected. Through addition of the DEM data into the flood mapping analysis of the Greenville area revealed that the total flooded area was 98.6 km(2) (out of a study area of 593.9 km(2)) or 16.5%. In the Greenville study area, the three landuse and landcover categories most affected by the flood were bottomland forest/hardwood swamps ( 32.7 km(2)), southern yellow pine ( 28.8 km(2)), and cultivated land (19.1 km(2)). Their total flooded areas were 80.6 km(2) or 81.7% of the total flooded area within this study area. The DEM data helped greatly in identifying the flooding that occurred underneath forest canopies, especially within bottomland forest and hardwood swamps. The method was reliable and could be applied quickly in other coastal floodplain regions using data that are relatively easy to obtain and analyse, and at a reasonable cost. This method should also work well in areas of large spatial extent where topography is relative flat.