A practical method for visualizing flood area and evaluating damage is presented, which consists of two technical approaches: self\|programming and adapting commercial GIS platforms. The low\|cost and easy\|to\|use GI...A practical method for visualizing flood area and evaluating damage is presented, which consists of two technical approaches: self\|programming and adapting commercial GIS platforms. The low\|cost and easy\|to\|use GIS\|Based model developed by self\|programming can meet current requirements of most local authorities, especially in developing countries. In this model, two cases, non\|source flood and source flood, are distinguished and the Seed\|spread algorithm suitable for source\|flood is discussed; The flood damage is assessed by overlaying the flood area range with thematic maps and other related social and economic data. and all thematic maps are converted to raster format before overlay analysis. Two measures are taken to improve the operation efficiency of speed seed\|spread algorithm. The accuracy of the model mainly depends on the resolution and precision of the DEM data, and the accuracy of registering all raster layers and the quality of attribute data.展开更多
文摘A practical method for visualizing flood area and evaluating damage is presented, which consists of two technical approaches: self\|programming and adapting commercial GIS platforms. The low\|cost and easy\|to\|use GIS\|Based model developed by self\|programming can meet current requirements of most local authorities, especially in developing countries. In this model, two cases, non\|source flood and source flood, are distinguished and the Seed\|spread algorithm suitable for source\|flood is discussed; The flood damage is assessed by overlaying the flood area range with thematic maps and other related social and economic data. and all thematic maps are converted to raster format before overlay analysis. Two measures are taken to improve the operation efficiency of speed seed\|spread algorithm. The accuracy of the model mainly depends on the resolution and precision of the DEM data, and the accuracy of registering all raster layers and the quality of attribute data.
