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]
基于无人机遥感的植被覆盖与管理因子计算
- Title:
- Calculation of Vegetation Cover and Management Factor Based on Remote Sensing Image of Unmanned Aerial Vehicle
- 文章编号:
- 1005-3409(2024)06-0103-06
- Keywords:
- soil erosion; vegetation cover and management factor; universal soil loss equation; UAV remote sensing; object-oriented classification
- 分类号:
- S157.4; Q948
- 文献标志码:
- A
- 摘要:
- [目的]研究传统遥感的混合像元分解法在无人机遥感中的应用,提出小区域尺度的植被覆盖与管理因子(C因子)快速估算方法。[方法]借助无人机航拍获取南京江宁谷里地区土地利用情况的遥感影像,采用面向对象分类法提取各类型用地的地物盖度,基于混合像元分解的C因子模型计算了研究区C值,通过与已有研究成果的分析比较,评价该方法的准确性。[结果]对象分类结果(植被、裸地和非光合地物)总正确率都在95%以上,基于混合像元分解的C因子模型估算南京江宁谷里地区的林地、耕地和草地的C值分别为0.057,0.176,0.043,结果与已有研究成果接近。[结论]利用无人机遥感进行C因子估算是可行的,且相较于传统的径流小区实测法,更为高效便捷。
- 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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备注/Memo
收稿日期:2023-09-04 修回日期:2023-12-29
资助项目:国家自然科学基金(41907049); 安徽省自然科学基金(2308085US04); 南京水利科学研究院中央级公益性科研院所基本科研业务费专项资金(Y919021,Y923005,Y922001); 南京市水务科技项目(202303)
第一作者:卞雪(1991—),女,江苏溧阳人,硕士,工程师,主要从事水土保持研究。E-mail:xbian@nhri.cn
通信作者:耿韧(1990—),男,安徽阜阳人,博士,高级工程师,主要从事土壤侵蚀与水土保持研究。E-mail:rgeng@nhri.cn