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Automatic determination of imperviousness in urban areas from digital orthophotos

机译:通过数字正射影像自动确定城市地区的不渗透性

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Determination of impervious areas in urban regions is the most labour-intensive part of data acquisition for rainfall-runoff modelling in urban hydrology. This paper presents an automatic determination method of imperviousness from aerial photographs. The colour, CIR (colour infrared) aerial photographs and orthophotos used have a ground resolution of 25 to 75 centimetres. A maximum likelihood classification algorithm was applied to assign each pixel to a surface category. Classification results were then overlaid with the subcatchments to determine the imperviousness of each subcatchment. Classification and overlay were carried out with the raster-based GIS IDRISI. The method was tested on various catchment areas, and the results compared with data obtained from manually digitised surfaces. Accuracy of the estimated imperviousness for the entire catchment areas was within 10%. The deviations for individual subcatchments were much higher. Equivalent results were obtained for colour and CIR photographs. A combination of both spectral ranges resulted only in a slight improvement. Consequently, this does not justify the additional costs of the second image. The developed method is an interesting alternative for use on large catchment areas where manual digitisation is very time-consuming and, thus, expensive.
机译:在城市水文降雨径流模拟数据采集中,确定城市区域的不透水区域是最费力的部分。本文提出了一种自动确定航空摄影不透水的方法。所使用的彩色CIR(彩色红外)航空照片和正射照片的地面分辨率为25至75厘米。应用最大似然分类算法将每个像素分配给一个表面类别。然后将分类结果覆盖在子汇水面积上,以确定每个子汇水面积的不渗透性。分类和叠加是使用基于栅格的GIS IDRISI进行的。该方法在各个集水区进行了测试,并将结果与​​从手动数字化表面获得的数据进行了比较。整个集水区的估计防渗精度在10%以内。单个子汇水面积的偏差要大得多。彩色和CIR照片获得了等效的结果。两个光谱范围的组合仅导致轻微改善。因此,这不能证明第二张图像的额外费用是合理的。所开发的方法是用于大型集水区的一种有趣的替代方法,在该区域中,手动数字化非常耗时,因此价格昂贵。

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