多时相双极化SAR影像林地类型分类方法

doi:10.11707/j.1001-7488.20140312

Abstract

Abstract:

Forest plays an important role on global carbon cycle and nature disturbance, so it is of great significance to monitor and map forest resources. Xunke County of Heilongjiang Province was selected as the test site and the coverage of two scenes of ALOS PALSAR images were applied. The sensitivity of multi-temporal PolSAR, InSAR with forest structure variation and time varying characteristics of backscattering coefficients and interferometric coherences were applied for forest land type classification. We developed a forest land type classification method based on SVM using multi-temporal, dual-polarization and interferometric SAR (InSAR) data. The result showed that the average InSAR coherence of multi-temporal could effectively identify forest land, sparse forest land and shrub land. The multi-temporal InSAR coherence, polarization ratios and other effective dimension information selected could effectively highlight the features and structures of objects and classify forest land types in detail.

Key words: multi-temporal, polarization, InSAR, forest land type, classification

CLC Number:

S757

Wang Xinshuang, Chen Erxue, Li Zengyuan, Yao Wanqiang, Zhao Lei. Multi-Temporal and Dual-Polarization SAR for Forest Land Type Classification[J]. Scientia Silvae Sinicae, 2014, 50(3): 83-91.

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Multi-Temporal and Dual-Polarization SAR for Forest Land Type Classification

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