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[1]Bian Xue,Lu Huizhong,Geng Ren,et al.Calculation of Vegetation Cover and Management Factor Based on Remote Sensing Image of Unmanned Aerial Vehicle[J].Research of Soil and Water Conservation,2024,31(06):103-108.[doi:10.13869/j.cnki.rswc.2024.06.012]

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Calculation of Vegetation Cover and Management Factor Based on Remote Sensing Image of Unmanned Aerial Vehicle

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 31 Number of periods: 2024 06 Page number: 103-108 Column: Public date: 2024-12-10

Title:: Calculation of Vegetation Cover and Management Factor Based on Remote Sensing Image of Unmanned Aerial Vehicle

Author(s):: Bian Xue¹, Lu Huizhong¹, Geng Ren¹, Shi Yu², Jin Qiu¹, Zhao Guangju¹; (1.The National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210029, China; 2.Monitoring Center for Soil and Water Conservation, Ministry of Water Resources, Beijing 100055, China)

Keywords:: soil erosion; vegetation cover and management factor; universal soil loss equation; UAV remote sensing; object-oriented classification

CLC:: S157.4; Q948

DOI:: 10.13869/j.cnki.rswc.2024.06.012

Abstract:: [Objective]This study aims to explore the application of traditional mixed pixel decomposition method in drone remote sensing technology, and to propose a fast estimation method for vegetation cover and management factor(C factor)at a small scale. [Methods]Drone aerial photography was used to capture remote sensing imagery of land use in the Guli area of Jiangning, Nanjing. An object-oriented classification method was utilized to extract the coverage of various land types. The C value of the research area was computed based on the mixed pixel decomposition C factor model, and the method's accuracy was evaluated by comparing it with previous research results. [Results]The object classification results(vegetation, bare land, and non-photosynthetic land)have an overall accuracy of over 95%. Based on the mixed pixel decomposition C factor model, the estimated C values for forestland, cultivated land, and grassland in the Guli area are 0.057, 0.176, and 0.043, respectively, which are close to existing research results. [Conclusion]Estimating C factor based on UAV remote sensing is feasible and more efficient compared to the traditional method of runoff plot observation.

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Last Update: 2024-12-10