Extraction and monitoring of vegetation coverage based on uncrewed aerial vehicle visible image in a post gold mining area

Abstract

Vegetation coverage reflects the degree of environmental degradation. Timely and effective monitoring of vegetation conditions is the basis for promoting vegetation protection and improving the ecological environment of mining areas. Exploring vegetation coverage extraction methods and selecting the optimal vegetation index in mining areas can provide scientific reference for estimating vegetation coverage based on vegetation index in mining areas. Uncrewed aerial vehicles (UAVs) are widely used because of their fast real-time performance, high spatial resolution, and easy accessibility. In this study, the performances of nine visible vegetation indices and two threshold segmentation methods for extracting vegetation coverage in a post-gold mining area in the Qinling Mountains were comprehensively compared using visible spectrum UAV images. Of the nine indices, the excess green index (EXG) and visible-band difference vegetation index (VDVI) were the most effective in discriminating between vegetation and non-vegetation by visual interpretation. In addition, the accuracy of the bimodal histogram threshold method in extracting vegetation coverage was higher than that of Otsu’s threshold method. The bimodal histogram threshold method combined with EXG yielded optimal extraction results. Based on optimal methods, the total percentages of fractional vegetation coverage in 2019, 2020, and 2021 were 31.47%, 34.08%, and 42.77%, respectively, indicating that the vegetation in the mining area improved. These results provide valuable guidance for extracting vegetation information and evaluating vegetation restoration in mining areas.