Retrieving the chlorophyll content of individual apple trees by reducing canopy shadow impact via a 3D radiative transfer model and UAV multispectral imagery
文献类型： 外文期刊
作者： Zhang, Chengjian 1 ; Chen, Zhibo 1 ; Chen, Riqiang 1 ; Zhang, Wenjie 1 ; Zhao, Dan 2 ; Yang, Guijun 2 ; Xu, Bo 2 ; Feng, Haikuan 2 ; Yang, Hao 2 ;
作者机构： 1.Beijing Forestry Univ, Sch Informat Sci & Technol, Beijing 100083, Peoples R China
2.Beijing Acad Agr & Forestry Sci, Minist Agr & Rural Affairs, Informat Technol Res Ctr, Key Lab Quantitat Remote Sensing Agr, Beijing 100097, Peoples R China
关键词： Chlorophyll content; Shadows; Vegetation index (VI); Radiative transfer models (RTMs); Hybrid inversion model; Individual apple tree crown
期刊名称：PLANT PHENOMICS （ 影响因子：6.4； 五年影响因子：7.1 ）
ISSN： 2643-6515
年卷期： 2025 年 7 卷 1 期
页码：
收录情况： SCI
摘要： Accurate monitoring and spatial distribution of the leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC) of individual apple trees are highly important for the effective management of individual plants and the promotion of the construction of modern smart orchards. However, the estimation of LCC and CCC is affected by shadows caused by canopy structure and observation geometry. In this study, we resolved the response relationship between individual apple tree crown spectra and shadows through a three-dimensional radiative transfer model (3D RTM) and unmanned aerial vehicle (UAV) multispectral images, assessed the resistance of a series of vegetation indices (VIs) to shadows and developed a hybrid inversion model that is resistant to shadow interference. The results revealed that (1) the proportion of individual tree canopy shadows exhibited a parabolic trend with time, with a minimum occurring at noon. Correspondingly, the reflectance in the visible band decreased with increasing canopy shadow ratio and reached a maximum value at noon, whereas the pattern of change in the reflectance in the near-infrared band was opposite that in the visible band. (2) The accuracy of chlorophyll content estimation varies among different VIs at different canopy shadow ratios. The top five VIs that are most resistant to changes in canopy shadow ratios are the NDVI-RE, Cire, Cigreen, TVI, and GNDVI. (3) For the constructed 3D RTM + GPR hybrid inversion model, only four VIs, namely, NDVI-RE, Cire, Cigreen, and TVI, need to be input to achieve the best inversion accuracy. (4) Both the LCC and the CCC of individual trees had good validation accuracy (LCC: R2 = 0.775, RMSE = 6.86 mu g/cm2, nRMSE = 12.24%; CCC: R2 = 0.784, RMSE = 32.33 mu g/cm2, and nRMSE = 14.49 %), and their distributions at orchard scales were characterized by considerable spatial heterogeneity. This study provides ideas for investigating the response between individual tree canopy shadows and spectra and offers a new strategy for minimizing the influence of shadow effects on the accurate estimation of chlorophyll content in individual apple trees.
- 相关文献
作者其他论文 更多>>
-
UssNet: a spatial self-awareness algorithm for wheat lodging area detection
作者：Zhang, Jun;Wu, Qiang;Duan, Fenghui;Liu, Cuiping;Xiong, Shuping;Ma, Xinming;Cheng, Jinpeng;Feng, Mingzheng;Dai, Li;Wang, Xiaochun;Yang, Hao;Yang, Guijun;Chang, Shenglong
关键词：Unmanned aerial vehicle; State space models; Wheat lodging area identification; Semantic segmentation
-
A Comprehensive Evaluation of Monocular Depth Estimation Methods in Low-Altitude Forest Environment
作者：Jia, Jiwen;Kang, Junhua;Gao, Xiang;Zhang, Borui;Yang, Guijun;Chen, Lin;Yang, Guijun
关键词：monocular depth estimation; CNN; vision transformer; forest environment; comparative study
-
Genotyping Identification of Maize Based on Three-Dimensional Structural Phenotyping and Gaussian Fuzzy Clustering
作者：Xu, Bo;Zhao, Chunjiang;Xu, Bo;Zhao, Chunjiang;Yang, Guijun;Zhang, Yuan;Liu, Changbin;Feng, Haikuan;Yang, Xiaodong;Yang, Hao;Xu, Bo;Zhao, Chunjiang;Yang, Guijun;Zhang, Yuan;Liu, Changbin;Feng, Haikuan;Yang, Xiaodong;Yang, Hao
关键词：tassel; 3D phenotyping; TreeQSM; genotyping; clustering
-
Sensitivity Analysis of AquaCrop Model Parameters for Winter Wheat under Different Meteorological Conditions Based on the EFAST Method
作者：Xing, Huimin;Sun, Qi;Li, Zhiguo;Wang, Zhen;Xing, Huimin;Wang, Zhen;Xing, Huimin;Sun, Qi;Wang, Zhen;Li, Zhiguo;Feng, Haikuan
关键词：winter wheat; biomass; sensitivity analysis; AquaCrop model
-
Estimation of Leaf Chlorophyll Content of Maize from Hyperspectral Data Using E2D-COS Feature Selection, Deep Neural Network, and Transfer Learning
作者：Chen, Riqiang;Feng, Haikuan;Hu, Haitang;Chen, Riqiang;Ren, Lipeng;Yang, Guijun;Cheng, Zhida;Zhao, Dan;Zhang, Chengjian;Feng, Haikuan;Hu, Haitang;Yang, Hao;Chen, Riqiang;Zhang, Chengjian;Ren, Lipeng;Feng, Haikuan
关键词：maize; chlorophyll; radiative transfer model; feature selection; transfer learning
-
Field-scale irrigated winter wheat mapping using a novel cross-region slope length index in 3D canopy hydrothermal and spectral feature space
作者：Zhang, Youming;Yang, Guijun;Li, Zhenhong;Liu, Miao;Zhang, Jing;Gao, Meiling;Zhu, Wu;Zhang, Youming;Yang, Guijun;Yang, Xiaodong;Song, Xiaoyu;Long, Huiling;Liu, Miao;Meng, Yang;Thenkabail, Prasad S.;Wu, Wenbin;Zuo, Lijun;Meng, Yang
关键词：Winter wheat; Irrigation mapping; Hydrothermal and spectral feature; Cross-region; Rainfed line; Slope Length Index
-
Combining UAV Remote Sensing with Ensemble Learning to Monitor Leaf Nitrogen Content in Custard Apple (Annona squamosa L.)
作者：Jiang, Xiangtai;Xu, Xingang;Wu, Wenbiao;Yang, Guijun;Meng, Yang;Feng, Haikuan;Li, Yafeng;Xue, Hanyu;Chen, Tianen;Jiang, Xiangtai;Xu, Xingang;Gao, Lutao
关键词：canopy nitrogen content; UAV remote sensing; ensemble learning; Lasso model
