Sentinel-1 decorrelation assessment based on vegetation index

doi:10.13474/j.cnki.11-2246.2023.0132

Abstract

Abstract: Sentinel-1 data has been widely used in synthetic aperture radar interferometry technology and related application fields since it is opened for free in the world, but its short wavelength characteristics make it easy to generate decorrelation in some low coherence areas, especially in vegetation coverage areas. However, the current mainstream post-interference incoherence evaluation strategy may cause data waste and increase research costs, taking into account the polarization mode, this paper establishes the quantitative models of Sentinel-1 coherence and optical remote sensing vegetation index NDVI at VV and VH polarization, and verifies the accuracy of the models in the adjacent validation area, indicating the reliability of the model. Based on the established models, the decorrelation can be quantitatively evaluated before the interference of Sentinel-1 data, in order to overcome the shortcomings of the above post-interference evaluation strategy, improve the efficiency of interferometry and reduce the research costs.

Key words: Sentinel-1A decorrelation, NDVI, interferometric coherence, vegetation index

CLC Number:

P237

PAN Jianping, ZHAO Ruiqi, CAI Zhuoyan, YUAN Yuxin, LI Pengxia. Sentinel-1 decorrelation assessment based on vegetation index[J]. Bulletin of Surveying and Mapping, 2023, 0(5): 32-37,50.

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