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Ningxiao Sun, Yuejin Zhao, Lin Sun, Qiongzhi Wu. Forest Mapping and Classification with Compact PolInSAR Data[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2018, 27(3): 391-398. doi: 10.15918/j.jbit1004-0579.17084
Citation: Ningxiao Sun, Yuejin Zhao, Lin Sun, Qiongzhi Wu. Forest Mapping and Classification with Compact PolInSAR Data[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2018, 27(3): 391-398.doi:10.15918/j.jbit1004-0579.17084
shu

Forest Mapping and Classification with Compact PolInSAR Data

doi:10.15918/j.jbit1004-0579.17084
  • 1.

    School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China

  • 2.

    School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

  • Received Date:2017-07-25
    Abstract
  • An unsupervised classification method was applied to compact polarimetric-interferometric SAR(C-PolInSAR) data to investigate its potential for forest mapping and classification. Unsupervised classification requires an initial class as a training set. In this paper, the compact polarimetric entropy Hand the optimal coherence spectrum Awere computed, and their capabilities for initial classification were analyzed. Based on the Hand A, a partition method was proposed to subdivide the H-Aplane, and initial classes were hence obtained. Next, unsupervised C-PolInSAR segmentation procedures based on H-Aand the complex coherence matrix J 4were investigated. The effectiveness of the unsupervised classification of C-PolInSAR data was demonstrated by using an E-SAR L-band PolInSAR dataset of the Traunstein test site.
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