Fractional vegetation coverage inversion model based UAV visible light imagery

Zhiyuan Gong; Xuemei Li

doi:10.1117/12.2634507

12 May 2022 Fractional vegetation coverage inversion model based UAV visible light imagery

Zhiyuan Gong, Xuemei Li

Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121730Y (2022) https://doi.org/10.1117/12.2634507
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China

Abstract

Taking Lanzhou Botanical Garden as the study area, the visible light remote sensing images in the study area from March 1, 2021 to June 7, 2021 were gathered by using a drone (Phantom 4 RTK). The Excess green index (ExG) was extracted and the inversion models between this index and fractional vegetation cover (FVC) were analyzed to explore the optimal inversion model in the study area. This index was used to establish the FVC inversion model in the study area. We compared the regression model results of polynomial, exponential, logarithmic and others, and the optimal FVC inversion model in the study area was the model of function of first degree: y=0.37x-1.67. It could estimate the dynamic change of FVC in the study area. Through this study, we can provide a scientific basis for the protection of the ecosystem in Lanzhou and other semi-arid area.

Citation Download Citation

Zhiyuan Gong and Xuemei Li "Fractional vegetation coverage inversion model based UAV visible light imagery", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121730Y (12 May 2022); https://doi.org/10.1117/12.2634507

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