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Classification of Alpine Wetlands Based on Feature Indices of Remote Sensing Image

机译:基于遥感影像特征指标的高山湿地分类

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摘要

Based on the brightness, greenness, humidity indices after Tasseled Cap transformation, NDWI and DEM. Extracting the alpine wetland information in source regions of three Rivers. Result shows that: the humidity can be used to distinguish wetland types from non-wetland classes, brightness component is effective in grassland extracting, while bare rock and gravel land, sand land etc. could be distinguished through its high value on lightness component. Elevation and slope component could be taken as the threshold variable in distinguishing the marsh and bare rock and gravel land. It shows that RS feature index based classification method used on Alpine wetland could improve the overall accuracy by 10.71% and Kappa index by 0.1250 after comparing with the maximum likelihood method. The result indicates that, the method based on indices got from image band transformation is an effective way of alpine wetlands information remote sensing extracting.
机译:根据流苏帽转换后的亮度,绿色和湿度指数,NDWI和DEM。提取三河源区的高山湿地信息。结果表明:湿度可用于区分湿地类型和非湿地类型,亮度分量在草地提取中是有效的,而裸露的岩石和砾石地,沙地等可以通过对亮度分量的高价值来区分。高程和坡度分量可以作为区分沼泽,裸露的岩石和砾石土地的阈值变量。结果表明,与最大似然法相比,基于RS特征指数的高寒湿地分类方法可将总体精度提高10.71%,将Kappa指数提高0.1250。结果表明,基于图像带变换指标的方法是一种有效的高山湿地信息遥感提取方法。

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