摘要
作物长势参数是精细农业遥感监测的重要对象,叶面积指数(LAI)是作物长势最重要的参数之一,利用遥感手段快速获取作物的LAI具有重要的意义。为此,考虑到波段组合方式对LAI的反演效果的不可忽略性,采用4种不同的波段组合,结合PROSPECT和SAIL的模拟数据、地面实测数据和高光谱影像数据,从植被指数的饱和性和模型拟合精度两个角度对6个植被指数展开了评价。结果表明:TVI、MSAVI和MCARI23个植被指数在以上3个方面均表现较优,750～680 nm波段组合更加适合于LAI的反演。
Crop growth parameters play an important role in precision agricultural remote sensing monitoring.Leaf area index(LAI)is one of the most important parameters of crop structure characteristics.It is of great significance to rapidly obtain LAI of crops with remote sensing.Considering the non-negligible effect of the band combination on LAI inversion,four different band combinations are adopted to evaluate six vegetation indices from the saturation and anti-interference of the vegetation index and model fitting accuracy,combined with PROSPECT and SAIL simulation data,ground measurements and hyperspectral image data,performed evaluations on six vegetation indices.The results show that TVI,MSAVI and MCARI2 are superior in the above three aspects,and 750-680 nm band combination is more suitable in LAI inversion.
作者
郑踊谦
董恒
张城芳
黄鹏
Zheng Yongqian;Dong Heng;Zhang Chengfang;Huang Peng(Institute of Remote Sensing and GIS,Peking University,Beijing 100871,China;College of Resource and Environment Engineering,Wuhan University of Technology,Wuhan 430070,China;Department of Architectural Engineering,Wuhan Huaxia University of Technology,Wuhan 430223,China)
出处
《农机化研究》
北大核心
2019年第10期1-6,44,共7页
Journal of Agricultural Mechanization Research
基金
国家自然科学基金项目(41701483)
湖北省教育厅科学研究计划项目(B2015365)
中央高校基本科研业务费专项项目(2018IVB060)
