Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB.
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| Title: | Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB. |
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| Authors: | Paciolla, Francesco1 (AUTHOR), Popeo, Giovanni1 (AUTHOR), Farella, Alessia1 (AUTHOR), Pascuzzi, Simone1 (AUTHOR) simone.pascuzzi@uniba.it |
| Source: | Remote Sensing. Aug2025, Vol. 17 Issue 15, p2746. 17p. |
| Subjects: | Agronomy, Agricultural drones, Thermography, MatLab (Computer software), Irrigation efficiency, Precision farming, Irrigation scheduling |
| 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs17152746 |
