摘要
及时准确监测草地植被覆盖度,对草地资源的可持续利用及生态系统的恢复与重建具有重要意义。本研究以荒漠草地植被为研究对象,采用监督分类与植被指数直方图相结合的阈值法,分析了6种RGB植被指数对荒漠草地的识别效果。研究结果表明:归一化绿红差异指数(normalized green-red difference index, NGRDI)对草地覆盖度的提取精度最高,其平均绝对误差和均方根误差分别为2.56%和3.06%。监督分类与可见光植被指数统计直方图相结合的阈值法对荒漠草地植被覆盖度的提取效果较好,可以用于荒漠草地植被覆盖度的提取。
Effective and accurate monitoring of grassland vegetation coverage is important for sustainable utilization of grassland resources and for restoration and reconstruction of ecosystems. In this study, a threshold method combining the supervised classification with the statistical histogram of visible vegetation index was used to identify grassland vegetation. The vegetation extraction accuracies of 6 Red Green Blue(RGB) vegetation indices were evaluated. The results indicated that the Normalized Difference Green/Red Index was the most accurate index for vegetation coverage extraction(mean absolute error 2.56%, root mean square error 3.06%). The proposed method accurately estimates the vegetation coverage of desert grassland.
作者
于惠
吴玉锋
牛莉婷
YU Hui;WU Yufeng;NIU Liting(Gansu Science Institute of Soil and Water Conservation,Lanzhou 730020,Gansu,China)
出处
《草业科学》
CAS
CSCD
北大核心
2021年第8期1432-1438,共7页
Pratacultural Science
基金
甘肃省水利厅水利科研项目(甘水科外[2016]76号-6)
甘肃省自然科学基金(1506RJZA176)
国家自然科学基金(41801191)。
关键词
RGB植被指数
荒漠草地
无人机
阈值法
监督分类
RGB vegetation indices
desert grassland
UAV
threshold method
supervision classification
