Exploring the depth of the maize canopy LAI detected by spectroscopy based on simulations and in situ measurements

作者：Jinpeng Cheng, Jiao Wang, Dan Zhao, Fenghui Duan, Qiang Wu, Yahao Lai, Jianbo Qi, Shuping Xiong, Hongbo Qiao, Xinming Ma, Hao Yang, Guijun Yang · 发表于：Plant Phenomics · 年份：2025 · DOI：10.1016/j.plaphe.2025.100100 · 被引用次数：6 · 研究领域：Remote Sensing in Agriculture、Spectroscopy and Chemometric Analyses、Remote Sensing and LiDAR Applications

The vertical distribution of leaves plays a crucial role in the growth process of maize. Understanding the vertical spectral characteristics of maize leaves is crucial for monitoring their growth. However, accurate estimation of the vertical distribution of leaf area remains a significant challenge in practical investigations. To address this, we used a 3D RTM to simulate the layered canopy spectra of maize, revealing the impact of canopy structure on remote sensing penetration depth across different growth stages and planting densities. The results of this study revealed differences in detection depth across growth stages. During the early growth stage, the depth was concentrated in the bottom 1 to 3 leaves of the canopy, reaching 1 to 4 leaves at the ear stage and 1 to 7 leaves during the grain-filling stage. The planting density had a notable effect on the detection depth at the bottom of the canopy. Moreover, compared with the other spectral bands, the near-infrared spectral range exhibited greater sensitivity to density variations. In terms of LAI inversion, a FuseBell-Hybrid model was constructed. We analyzed VIs across different planting density and canopy structural scenarios and found that compared with lower layers, increased density reduced the relative change rate in the upper leaf layers. The sensitivity patterns differed between plant architectures: VIred exhibited density-dependent sensitivity, with distinct responses between plant types, and MTVI2 demonstrated...