数字高程模型(Digital Elevation Model,DEM)是提取数字河网的主要数据源。但是,由于在受到带有尺度效应的DEM空间分辨率和数字河网提取过程中,汇流面积阈值等参数的影响,使得河网提取的结果具有很大的主观性,因此,如何优化两者的取值,对于更准确地模拟地表河网具有重要的意义。本文以厦门市作为研究区,以1∶1万的全要素地形图作为原始数据并构建空间分辨率为2.5m的DEM,同时采用最邻近方法将该DEM重采样成网格大小分别为5m,10m,20m,40m,80m,160m和320m等一系列网格相互嵌套的DEM数据,并对重采样后的各DEM数据分别取汇流面积阈值为0.9km2,2.7km2,4.5km2,7.2km2,9km2,13.5km2和18km2,利用D8算法和ArcGIS软件中的Hydrology模块进行数字河网提取,最后,计算河道总长度作为特征指标,定量分析河道总长度、DEM空间分辨率,以及汇流面积阈值三者之间的函数关系,并进一步探讨DEM空间分辨率和汇流面积阈值的优化取值,研究结果表明:(1)河道总长度与阈值、DEM分辨率三者之间的关系满足一复合函数表达式;(2)当阈值保持不变时,河道总长度随DEM分辨率的不断变小而呈减小趋势,反之,当DEM分辨率确定时,河道总长度随阈值的不断变大而减小;(3)根据三者之间函数关系的数学分析结果,研究区提取河网的最适宜分辨率和最适宜阈值分别为40m和7.2km2。经过对比分析,根据最适宜参数所提取的河网数据与分辨率为2.5m的SPOT5厦门遥感影像的水系总体上吻合最好。
Digital Elevation Model (DEM) is the main data source for digital drainage network extraction. But the extracted result would have great subjectivity because of the scale influences by the parameters such as the drainage area threshold and DEM resolution. Therefore, it is of great significance that how to optimize these factors for extracting the drainage networks better. The existing researches are mainly concerned on any two factors qualitatively or quantitatively. It is yet to be answered about how to define the drainage area threshold and the spatial resolution in a given research area. Taking Xiamen City of Fujian Province as the study area and using the Digital Line Graphic (DLG) on the scale of 1:10 000 as the original data to construct the DEM with grid cell size of 2.5m, we re-sampled the DEM into a series of DEMs with nested grid size as 5m, 10m, 20m, 40m, 80m, 160m and 320m using the Nearest Re-sampling method. And then the D8 algorithm and the Hydrology module in ArcGIS software was employed to extract the drainage networks from each DEM mentioned above with 7 drainage area thresholds as 0.9km2, 2.7km2, 4.5km2, 7.2km2, 9km2, 13.5km2 and 18km2. Finally, the length of the drainage networks, as a key factor, was calculated to analyse quantitatively the relationship between the three parameters mentioned above and to further discuss the optimization of these parameters. The research results revealed that:(1)The length of the drainage networks obeys one composite power function;(2)When thresholds keeps constant, drainage network features decreased with DEM grid cell size continuously;(3)According to the mathematical analysis of the composite function, the optimal grid cell size and drainage area threshold are 40m and 7.2km2 respectively. The extracted drainage networks with the optimal parameters met with those extracted from the SPOT5 remote sensing image very well.
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