Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB

Abstract

Thermal cameras are becoming popular in several applications of precision agriculture, including crop and soil monitoring, for efficient irrigation scheduling, crop maturity, and yield mapping. Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, to deeply understand the variability of crop and soil conditions. However, few commercial software programs, such as PIX4D Mapper, can process thermal images, and their functionalities are very limited. This paper reports on the implementation of a custom MATLAB® R2024a script to extract agronomic information from thermal orthomosaics obtained from images acquired by the DJI Mavic 3T drone. This approach enables us to evaluate the temperature at each point of an orthomosaic, create regions of interest, calculate basic statistics of spatial temperature distribution, and compute the Crop Water Stress Index. In the authors’ opinion, the reported approach can be easily replicated and can serve as a valuable tool for scientists who work with thermal images in the agricultural sector.

Plant phenotyping relevance

UAV熱画像から温度分布とCrop Water Stress Indexを抽出するMATLAB手法を開発・提示しており、植物の水ストレス状態を定量化する方法が中心である。

Code and data availability

The paper's custom MATLAB script is stated to be freely available as an attachment to the manuscript, but no authors' public URL or repository is provided in the supplied blocks. The only GitHub link is a third-party open-source R-JPEG-to-TIFF conversion tool, not the authors' analysis code. No public phenotype dataset

No evidence-backed public reproduction asset is currently recorded.