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DOI10.3390/rs9090955
The Performance of Airborne C-Band PolInSAR Data on Forest Growth Stage Types Classification
Feng, Qi; Zhou, Liangjiang; Chen, Erxue; Liang, Xingdong; Zhao, Lei; Zhou, Yu
发表日期2017
ISSN2072-4292
卷号9期号:9
英文摘要In this paper, we propose a classification scheme for forest growth stage types and other cover types using a support vector machine (SVM) based on the Polarimetric SAR Interferometric (PolInSAR) data acquired by Chinese Multidimensional Space Joint-observation SAR (MSJosSAR) system. Firstly, polarimetric, texture, and coherence features were calculated from the PolInSAR data. Secondly, the capabilities of the polarimetric, texture, and coherence features in land use/cover classification were quantified independently through histograms. Following this, the polarimetric features were used for the classification of land use/cover types, followed by a combination of texture and coherence features. Finally, the three classification results were validated against test samples using the confusion matrix. It was shown that, with the integration of texture and coherence features, the producer's accuracy for afforested land, young forest land, medium forest land, and near-mature forest land improved by 6%, 31%, 11%, and 6%, respectively, compared with the former experiment using solely polarimetric features. Our study indicates that the forest and non-forest lands can be discriminated by the polarimetric features, which also play an important role in the separation between afforested land and other forest types as well as medium forest land and near-mature forest land. The texture features further discriminate afforested land and other forest types, while the coherence features obviously improved the separation of young forest land and medium forest land. This paper provides an effective way of identifying various land use/cover types, especially for distinguishing forest growth stages with SAR data. It would be of great interest in regions with frequent cloud coverage and limited optical data for the monitoring of land use/cover types.
关键词PolInSARforest typespolarimetrictexturecoherence
学科领域Remote Sensing
语种英语
WOS研究方向Remote Sensing
来源期刊REMOTE SENSING
来源机构中国科学院西北生态环境资源研究院
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/111921
作者单位Chinese Acad Sci, Inst Elect, Sci & Technol Microwave Imaging Lab, Beijing 100094, Peoples R China
推荐引用方式
GB/T 7714
Feng, Qi,Zhou, Liangjiang,Chen, Erxue,et al. The Performance of Airborne C-Band PolInSAR Data on Forest Growth Stage Types Classification[J]. 中国科学院西北生态环境资源研究院,2017,9(9).
APA Feng, Qi,Zhou, Liangjiang,Chen, Erxue,Liang, Xingdong,Zhao, Lei,&Zhou, Yu.(2017).The Performance of Airborne C-Band PolInSAR Data on Forest Growth Stage Types Classification.REMOTE SENSING,9(9).
MLA Feng, Qi,et al."The Performance of Airborne C-Band PolInSAR Data on Forest Growth Stage Types Classification".REMOTE SENSING 9.9(2017).
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