Landsat MSS图像监督聚类在gis中的应用

Miguel Torres Ruiz, M. Moreno, R. Quintero, G. Guzmán
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引用次数: 3

摘要

在本文中,作者描述并实现了一种对Landsat MSS卫星图像进行监督分类的算法。采用最大似然分类方法,通过监督聚类生成栅格数字专题地图。在墨西哥不同地区的Landsat MSS图像中验证了聚类方法检测与地理环境相关的多个训练数据。该算法已集成到空间分析模块中,以改进决策模型和空间分析在gis应用中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying Supervised Clustering to Landsat MSS Images into GIS-Application
In this paper, the authors describe and implement an algorithm to perform a supervised classification into Landsat MSS satellite images. The Maximum Likelihood Classification method is used to generate raster digital thematic maps by means of a supervised clustering. The clustering method has been proved in Landsat MSS images of different regions of Mexico to detect several training data related to the geographic environment. The algorithm has been integrated into Spatial Analyzer Module to improve the decision making model and the spatial analysis into GIS-applications.
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