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Identification and classification of forest landscape pattern: fuzzy modeling and processing of remote sensing image

机译:森林景观模式的识别与分类:遥感图像模糊建模与处理

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摘要

Much information from remote sensing image is fuzzy and uncertain, which greatly influences the recognition and monitoring of landscape pattern. It is more difficult to identify the types of forest landscape, due to its relative homogeneity compared to larger scale landuse type. Moreover, the categories and process of forest landscape classification, in fact, are fuzzy. In this paper, I use a fuzzy modeling approach to deal with the fuzzy phenomena during the process of identification and classification of forest landscape image. This approach also incorporates the knowledge of vegetation ecology and expert experiences into classification model. Using supervised classification of pixel-by-pixel and group-by-group, I classified a tropical forest landscape. The results indicate that the fuzzy modeling approach can effectively deal with fuzzy information from remote sensing image.
机译:来自遥感图像的许多信息是模糊和不确定的,这极大地影响了景观模式的识别和监控。由于其相对均匀性与较大的尺寸型土地使用相比,识别森林景观类型更难以。此外,森林景观分类的类别和过程实际上是模糊的。在本文中,我使用模糊建模方法来处理森林景观图像识别和分类过程中的模糊现象。这种方法还将植被生态和专家经验的知识纳入分类模型中。使用逐个像素和逐个群体的监督分类,我分为热带森林景观。结果表明,模糊建模方法可以有效地处理来自遥感图像的模糊信息。

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