黄土高原地形因子间关联性的神经网络分析  

The Relevancy Between Quantitative Terrain Factors and Mean Slope in China′s Loess Plateau

作　　者：张婷[1,2] 汤国安[1] 王春[1,2] 王峥[3] 龙毅[1] 

机构地区：[1]南京师范大学江苏省地理信息科学重点实验室 [2]西北大学城市与资源学系,西安710069 [3]西北大学计算机科学系

出　　处：《地球信息科学》2004年第4期45-50,共6页Geo-information Science

基　　金：国家自然科学基金资助项目(40271089);教育部科研基金重点项目(01111);测绘遥感信息工程国家重点实验室高级访问学者基金

摘　　要：不同的地形因子从不同侧面反映地面的起伏特征或空间变异,各因子之间所存在的相互关联、相互制约、相互影响的特征,在很大程度上揭示了地形发育与空间变异的内在本质。本文以黄土高原丘陵沟壑区的1∶10000和1∶50000两种比例尺的15个实验样区为样本,应用BP神经网络模型,探讨不同比例尺的地形定量因子与地面坡度之间的关联特征及其变化规律。实验结果表明:①利用神经网络分析方法可以有效定量评价地形因子间的关联性;②该研究方法有助于地学分析中DEM尺度的选择,地形因子的确定及其相关关系的量化。Different terrain factors express the undulating characteristics and spatial variations of the true surface from different aspects. The relationships among them can play a key role in revealing the mechanism and development of the terrain and geomorphologic situation to a great extent. The relationships and their variance discipline between the terrain factors and mean slope are discussed in this paper via the Back Propagation model of Neural Network. Fifteen loess gully-hilly areas are selected as the test areas for experiment, and the relevant 1∶10 000 and 1∶50 000 map scale DEMs of high resolution and high precision are also selected as the basic data. The results show this method can effectively evaluate the relevancy of terrain factors on the mean slope extracted from DEMs at the two scales. It is hoped that this result can be helpful in evaluating the availability of the DEM scale applied, determining the relevancies among multiple topographical factors as well as selecting suitable terrain variables for different applications.

关 键 词：地形因子 坡度 关联性 神经网络 DEM 

分 类 号：P231.5[天文地球—摄影测量与遥感]