栅格DEM坡体因子融合方法北大核心CSCD

坡体是自然地形实体的基本组成单元,利用综合性坡体因子分析和挖掘地形隐含信息,有助于区域地形地貌分析及规划利用。本文针对当前坡体综合表达因子(LS)未顾及坡宽因子的缺陷,采用归一化几何运算法将坡长(L)、坡度(S)、坡宽(W)进行融合,获取了一种新的坡体融合因子LSW。以DEM为数据源、黄土高原某小流域局部范围为典型研究区,在提取L、S、W及LS因子的基础上,分别以L×S×W、L+S+W、LS×W及LS+W共4种方式进行融合试验。结果表明,L+S+W融合方式获取的坡体LSW因子标准差矩阵均值最小,为0.234 4,有效平衡了各单地形因子对融合坡体因子LSW的贡献度,信息熵值计算分析也实证了L+S+W融合方式具有最优性。

Slope body factor fusion of grid DEM

Slope body is the basic unit of natural terrain entity. It is beneficial for regional landform analysis and planning to use comprehensive slope factor analysis and excavation of terrain implied information. Because of the current defect that the slope width factor has not been considered in the slope comprehensive expression factor(LS), a new slope fusion factor(LSW) is acquired by integrating the slope length (L), slope (S) and slope width (W) with the normalized geometric operation method. Using DEM by intercepting a local area of a small watershed in the Loess Plateau as a typical study area, four patterns L×S×W, L+S+W, LS×W and LS+W are adopted for the fusion experiment based on the extraction of L, S, W and LS. The experimental results show that the L+S+W fusion pattern has the lowest mean value 0.2344 in the LSW factor variance matrix, effectively balances the contribution of each single terrain factor in LSW to the fusion slope factor LSW, and the L+S+W fusion pattern is demonstrated to be optimal by information entropy calculation.