Research on key parameters of forest height inversion method based on radar remote sensing images

Haotian Deng; Lingjia Gu; Ruizhi Ren; Shuting Yang

doi:10.1117/12.2566123

20 August 2020 Research on key parameters of forest height inversion method based on radar remote sensing images

Haotian Deng, Lingjia Gu, Ruizhi Ren, Shuting Yang

Proceedings Volume 11501, Earth Observing Systems XXV; 115011C (2020) https://doi.org/10.1117/12.2566123
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Conference Poster

Abstract

The ground measurement of forest height is time-consuming and labor-consuming. In recent years, with the development of satellite remote sensing technology, it is possible to obtain forest height using radar remote sensing data. This paper uses the simulated full polarization radar data as the research object. The PCT inversion method (PCT), RVoG inversion method (RVoG), coherent amplitude inversion method (COH) and DEM difference inversion method (DEM) was used to obtain forest height. Through these four inversion methods, the influence of four parameters (radar incident angle, vegetation density, tree species, actual forest height) on the inversion result was studied. The experimental results show that if the radar incident angle is closer to 45 degrees, the vegetation density is greater than or equal to 300 trees, and the actual forest height is higher than 10 meters, the forest height inversion results have better accuracy. The research’s conclusions can provide a theoretical basis and method for error analysis of forest height inversion from real radar remote sensing data.

Citation Download Citation

Haotian Deng, Lingjia Gu, Ruizhi Ren, and Shuting Yang "Research on key parameters of forest height inversion method based on radar remote sensing images", Proc. SPIE 11501, Earth Observing Systems XXV, 115011C (20 August 2020); https://doi.org/10.1117/12.2566123

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