Multi-Spectral Point Cloud Constructed with Advanced UAV Technique for Anisotropic Reflectance Analysis of Maize Leaves

Abstract

Reflectance anisotropy in remote sensing images can complicate the interpretation of spectral signature, and extracting precise structural information under these pixels is a promising approach. Low-altitude unmanned aerial vehicle (UAV) systems can capture high-resolution imagery even to centimeter-level detail, potentially simplifying the characterization of leaf anisotropic reflectance. We proposed a novel maize point cloud generation method that combines an advanced UAV cross-circling oblique (CCO) photography route with the Structure from the Motion-Multi-View Stereo (SfM-MVS) algorithm. A multi-spectral point cloud was then generated by fusing multi-spectral imagery with the point cloud using a DSM-based approach. The Rahman–Pinty–Verstraete (RPV) model was finally applied to establish maize leaf-level anisotropic reflectance models. Our results indicated a high degree of similarity between measured and estimated maize structural parameters (R2 = 0.89 for leaf length and 0.96 for plant height) based on accurate point cloud data obtained from the CCO route. Most data points clustered around the principal plane due to a constant angle between the sun and view vectors, resulting in a limited range of view azimuths. Leaf reflectance anisotropy was characterized by the RPV model with R2 ranging from 0.38 to 0.75 for five wavelength bands. These findings hold significant promise for promoting the decoupling of plant structural information and leaf optical characteristics within remote sensing data.

Plant phenotyping relevance

UAVマルチスペクトル画像とSfM-MVSを用いてトウモロコシの点群・葉レベル反射特性を生成・推定する手法が中心で、葉長や草丈などの植物形質を検証している。

Code and data availability

The paper's maize point clouds, UAV multi-spectral imagery, manual structural measurements, and RPV analysis outputs are not publicly deposited. The Data Availability Statement only offers the data upon inquiry to the corresponding author, so any paper-specific asset requires contacting the authors.

No evidence-backed public reproduction asset is currently recorded.