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中文摘要：
针对ALOS PALSAR全极化数据提取了多种极化特征,分析其对人工地物、裸地、农田、林地、水体5种典型地物的提取能力。实验结果表明,利用全极化SAR影像提取的极化特征可以较好地区分城市典型地物类型,并且全极化数据的地物区分能力优于双极化数据。对于单一时相的数据分类结果而言,人工地物与其他非人工地物的极化特征差别最大,水体与林地也较容易区分,而裸地和农田容易混淆。
英文摘要：
Several polarimetric characteristics are extracted from ALOS PALSAR data,containing coherent and non-coherental characteristics.Then,through qualitative and quantitative indicators,their abilities to distinguish five typical urban land covers including artificial features,bare land,farmland,woodland and water are analyzed and compared.The experimental results show that circular polarization correlation coefficient,linear polarization correlation coefficient,total power and XPI are the best set of polarization characteristics to classify these land covers.Classification using such a group of characteristics can achieve an overall accuracy of 75.5% with Kappa being 0.651 1.In addition,we find that artificial features are easier to be distinguished from other land cover types,while bare land and farmland are prone to be mixed up.
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