天蓬
高光谱成像
多光谱图像
叶面积指数
遥感
决定系数
数学
植被(病理学)
叶绿素
氮气
内容(测量理论)
反照率(炼金术)
环境科学
化学
农学
园艺
植物
统计
地理
生物
数学分析
病理
医学
有机化学
艺术史
表演艺术
艺术
作者
Yuanyuan Pan,Wenxuan Wu,Jiawen Zhang,Yuejiao Zhao,Jiayi Zhang,Yangyang Gu,Xia Yao,Tao Cheng,Yan Zhu,Weixing Cao,Yongchao Tian
标识
DOI:10.1016/j.compag.2023.107769
摘要
Canopy scattering coefficient (CSC) is the ratio of bidirectional reflectance factor (BRF) to directional area scattering coefficient (DASF), and has been successfully applied to correct the effect of canopy structure. The key to calculate CSC is to calculate DASF, which is determined by the intercept b and slope k of the linear relationship between BRF and BRFλΩωλ (the ratio of hyperspectral BRF in certain view direction to leaf albedo (ωλ). However, due to the limitation of multispectral bands, how to accurately calculate crop DASF during the whole growth period using multispectral UAV data is still an urgent problem to be solved. In this study, wheat canopy multi-angular (0°, −30°, −45°) datasets including near-ground hyperspectral data, UAV multispectral data, and PROSAIL simulation data were obtained for three consecutive years. The DASFk-b model was proposed to estimate b and k based on multispectral sensors by relative accumulated growing degree days (RAGDD) and BRF. The previously developed DASFg-NIR model and vegetation index (VI) model were compared with DASFk-b model under different view angles (VZAs), to evaluate their performances in correcting canopy structural effect, estimating leaf nitrogen content (LNC) and leaf chlorophyll content (LCC) based on generalized additive model (GAM). The results showed that the hyperspectral band range suitable for estimating wheat DASF was 710–760 nm. Parameter b decreased with increased N application rates, and activated first and then inhibited with increased RAGDD; the tendency of k, DASFHy were opposite. Compared with CSCg-NIR (calculated from DASFg-NIR model) and VIs, CSCk-b (calculated from DASFk-b model) had the best correction effect on canopy structure under different VZAs. The estimation accuracy of LNC and LCC using CSCk-b was improved compared with CSCg-NIR and VIs, with RRMSE values of 9.2% and 7.0%, respectively, and the recommended VZA was −45° for both models.
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