基于遥感影像的四种植被分析方法的比较与评价

Peijun Du, Yan Luo, W. Cao, Huapeng Zhang
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引用次数: 1

摘要

植被遥感已经发展了一些分析方法并得到了广泛的应用,其中四种比较流行的方法是基于NDVI和其他VIs的植被分析、基于非混合植被丰度的植被分析、基于土地覆盖分类的植被分析和基于K-T变换的绿度分量分析。以徐州市为例,采用4种方法提取Landsat TM影像中的植被信息,并对其性能进行了比较。首先对植被类型、NDVI值、植被丰度和绿度进行关联分析。结果表明,NDVI与植被丰度和绿化度之间的相关性非常明显。基于不同的植被提取方法推导了植被覆盖度,并对其一致性进行了分析。结果表明,该方法在植被覆盖度估算方面优于其他方法。通过比较四种分析方法的性能和有效性,对选择合适的分析方法提出了建议。
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A comparison and evaluation of four vegetation analysis approaches based on remote sensing imagery
Some analytical approaches have been developed and widely used for vegetation remote sensing, among which four popular methods are vegetation analysis via NDVI and other VIs, vegetation analysis using the vegetation abundance derived from unmixing, vegetation analysis by land cover classification, and the greenness component derived from K-T transform. There four approaches are used to extract vegetation information from Landsat TM image taking Xuzhou City as an example, and their performance is compared. Association analysis among vegetation types, NDVI values, vegetation abundance and greenness is conducted at first. It is found that the association among NDVI, vegetation abundance and greenness is quite obvious. Vegetation coverage ratio is derived based on different vegetation extraction approaches, and their consistency is analyzed. It is found that the unmixing-based approach outperforms others in terms of vegetation coverage ration estimation. By comparing the performance and effectiveness of four approaches, some suggestions are given for selecting suitable analytical approaches.
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