黄土丘陵区数字地貌模型与遥感影象分类

黄土丘陵区地形破碎、沟壑纵横，为遥感影象的土地利用自动分类带来了很大困难。仅依靠传统的光谱统计分类方法，难以达到较高的分类精度。本文拟探讨在黄土丘陵区运用大比例尺地形图数据，建立区域数字地貌模型；并在模糊数学理论的指导下，运用数字地貌模型对影象的分层分类结果进行修正和细化。研究表明，此方法能够有效地提高土地利用分类精度和机助制图比例尺。

Study on the Landuse Classification Using DGM Data in Loess Hill Area

With the complicated terrain and low vegetation cover in loess plateau of North China, it is very difficult to get higher accuracy of digital image classification, only depending on the traditional spectral statistical classification method. The spatial resolution of Thematic Mapper(30m /pixel) also limit the accuracy and scale of interpreting landuse maps. In order to improve the accuracy of landuse classification in loess hilly area, a large scale relief map was used to create the digital geomorphic model (DGM). By applying Fuzzy Mathematics theory, the DGM was used to correct the digital image classification result, so as to create the regional landuse model. The study shows that this classification improves the accuracy of landuse classification effectively, and combines the digital image classification with DTM entirely.