Research Papers

Forest and deforestation identification based on multitemporal polarimetric RADARSAT-2 images in Southwestern China

[+] Author Affiliations
Fengli Zhang, Chou Xie, Kun Li

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, #3 Datun Road, Chaoyang District, Beijing 100101, China

Maosong Xu, Xuejun Wang

Academy of Forestry Inventory, Planning and Designing, State Forestry Administration, Beijing 100714, China

Zhongsheng Xia

Forest Resource Management and Conservation Station, Guizhou Province, 550001, China

J. Appl. Remote Sens. 6(1), 063527 (Apr 27, 2012). doi:10.1117/1.JRS.6.063527
History: Received September 25, 2011; Revised February 28, 2012; Accepted March 5, 2012
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Abstract.  In the southwest of China, it is anticipated that synthetic aperture radar (SAR) will become an important tool for forest inventory because of its all-weather capabilities. The Zhazuo area in Guizhou Province of southwest China, with a typical Karst landform, was selected as the test site. Six RADARSAT-2 polarimetric images were acquired in order to analyze polarimetric backscattering behavior and temporal variation of forest and deforested area. Polarimetric decomposition was conducted, and Pauli and Freeman-Durden decomposition were demonstrated to be more suitable for identifying forest and deforestation respectively. Finally, a scheme for multitemporal polarimetric SAR data fusion was proposed, which could greatly improve image quality and make forest identification more efficient. Support vector machine classification showed that the overall accuracy for forest identification was 87.63%, and the accuracy could be enhanced to 91.49% after gamma filtering.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Fengli Zhang ; Maosong Xu ; Chou Xie ; Zhongsheng Xia ; Kun Li, et al.
"Forest and deforestation identification based on multitemporal polarimetric RADARSAT-2 images in Southwestern China", J. Appl. Remote Sens. 6(1), 063527 (Apr 27, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063527


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