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土壤的波谱反射特性是土壤遥感数据信息处理和计算机自动识别分类的物理学基础。我们曾以云南腾冲光谱试验区的室内外测试资料,应用聚类分析进行了土壤和土地利用分类的尝试。本文拟用同样资料,应用主组元分析进行分类识别,以期为土壤遥感的数据处理,提供一个较为有利的途径。主组元分析已在包括土壤和遥感在内的各个科学技术领域中得到广泛应用。关于主组元分析的原理和计算步骤,本文不另赘述。
The spectral reflectance of soil is the physical basis of information processing of soil remote sensing data and computer automatic identification classification. We used the indoor and outdoor test data of Yunnan Tengchong spectral test area and conducted an attempt to classify soil and land use using cluster analysis. This paper intends to use the same information, the use of principal component analysis to identify the classification, with a view to the remote sensing data processing, provide a more favorable way. Principal component analysis has been widely used in various fields of science and technology, including soil and remote sensing. On the principle of principal component analysis and calculation steps, this article will not repeat them.