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首页> 外文会议>Conference on Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture; Aug 7, 2003; San Diego, California, USA >Land use investigation with remote sensing based on spectral character analysis in Poyang Lake region, China
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Land use investigation with remote sensing based on spectral character analysis in Poyang Lake region, China

机译：基于光谱特征分析的Po阳湖地区遥感土地利用调查

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Based on Landsat TM data combined with practical investigation information obtained using Global Positioning Systems (GPS), we created a training field of land use classification. Using the methods of spectral distance analysis, we analyzed spectral signature value of different training fields in TM3, TM4, TM5 and TM7 band, and compared these with the standard deviation analysis. Based on these results, we selected the best spectral bands for classification and created remote sensing interpretation marks of land use classification. Supervising classification was used with the image classification of TM and the maximum likelihood was used for parametric rule of supervised classification. We applied the method of spectral signature analysis to the individual study of land use classification of Poyang Lake region. The land use was classified into 9 classes: paddy field, non-irrigated farmland, forestland, grassland, water area, lake beach, grass beach, sandy land and residential area. Based on the data of GPS investigation, we assessed the classification accuracy. Result indicated that classification accuracy reached 91.43% and the classification effect was better than the common supervised classifying and unsupervised classifying.
机译：基于Landsat TM数据并结合使用全球定位系统（GPS）获得的实际调查信息，我们创建了土地利用分类的培训领域。使用光谱距离分析的方法，我们分析了TM3，TM4，TM5和TM7频带中不同训练场的光谱特征值，并将其与标准偏差分析进行了比较。基于这些结果，我们选择了最佳光谱带进行分类，并创建了土地利用分类的遥感解释标记。监督分类与TM的图像分类一起使用，最大似然用于监督分类的参数规则。我们将光谱特征分析法应用到Po阳湖地区土地利用分类的个体研究中。土地利用分为9类：水田，非灌溉农田，林地，草原，水域，湖滩，草滩，沙地和居民区。基于GPS调查的数据，我们评估了分类准确性。结果表明，分类准确率达到91.43％，分类效果优于普通监督分类和非监督分类。

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