基于DEM的四川盆地地形形态纹理统计分析

Q1 Social Sciences HumanMachine Communication Journal Pub Date : 2010-04-24 DOI:10.1109/MVHI.2010.169
Yonghong Zhou, Mingliang Luo
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引用次数: 2

摘要

地形分析是复杂地形环境下进行地形分类和地貌制图的重要工作。当航天飞机雷达地形图任务出现时,大量的SRTM数字高程模型(简称SRTM DEM)数据被传回地球。然后自动化数据的分析和解释是一个具有挑战性的重大利益的考验。在本研究中,我们提出结合纹理统计和分类对四川盆地地形资料和地貌周围进行解释,识别四川盆地景观的组成地貌。我们的方法使用无监督图像分割将地形划分为许多空间扩展但地形均匀的物体。这些物体被划分为预先确定的地貌类别。我们已经将我们的技术应用到中国四川省的四川盆地和山区。80%的平均准确率表明我们的算法是有效和可接受的。
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Texture Statistics for Sichuan Basin Terrain Morphology Analysis DEM Based
Terrain analysis is an important job for terrain classification and geomorphologic mapping in complex terrain context. When Shuttle Radar Topography Mission appeared, enormous account of data, SRTM Digital Elevation Model (abbreviated SRTM DEM), has been sent back to earth. Then automating the analysis of this data and its interpretation represents a challenging test of significant benefit. In this study, we propose combing texture statistics and classification to interpret topography data of Sichuan Basin and landform surround and to identify constituent land-forms of the Sichuan Basin landscape. Our approach used unsupervised image segmentation to divide a landform into a number of spatially extended but topographically homogeneous objects. The objects are classified into predetermined landform classes. We have applied our technique to the Sichuan Basin and mountain surround in Sichuan Province, China. The 80% mean accuracy as a result has shown our algorithm being efficiency and acceptable.
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CiteScore
10.00
自引率
0.00%
发文量
10
审稿时长
8 weeks
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