Optimizing UAV-based uncooled thermal cameras in field conditions for precision agriculture

Unoccupied aerial vehicles (UAVs) equipped with thermal cameras show great promise for precision agriculture, but challenges persist in analyzing land surface temperature (LST). This study explores the influence of ambient environmental conditions and intrinsic characteristics of uncooled thermal cameras on the accuracy of temperature measurements obtained through UAV-based thermal cameras. The research utilized DJI Matrice 210 quad-rotor UAVs equipped with FLIR Tau 2 and WIRIS 2 nd Gen thermal cameras. The experimental design involved strategically selected temperature reference materials of diverse compositions. UAV flights were conducted at varying altitudes, capturing thermal images correlated with ground-based thermocouple measurements. Results indicate that increasing flight altitude resulted in underestimated temperatures measured by UAVs for objects with higher kinematic temperatures, while objects with lower temperatures displayed higher measurements. The study integrates multiple environmental metrics, illustrating the complex influence of air temperature, humidity, net radiation, and wind speed on temperature measurements, with variations observed between FLIR Tau 2 and WIRIS 2 nd Gen camera models. Linear regression models highlight the diverse impact of these metrics on UAV-based temperature observations. Furthermore, an analysis of uncooled thermal sensor characteristics reveals a correlation between UAV-measured temperatures and the focal plane array (FPA) temperature, emphasizing the importance of considering intrinsic sensor dynamics. These findings provide valuable insights for enhancing the reliability of UAV-based thermal measurements in agricultural and environmental monitoring. The research underscores the necessity for a comprehensive understanding of both ambient conditions and camera-model-specific dynamics to optimize thermal imaging accuracy for precision agriculture applications. Accordingly, the recommended procedures have been described to reduce the effect of identified sources of influence. • Field practice standardization benefits from the strategic selection of reference materials. • Optimizing thermal flight altitudes balances accuracy, resolution, and battery. • FPA temperature fluctuations during thermal flights result in increased signal variations. • Calibrating environmental factors is only possible with complete on-site ancillary data. • User tests for each camera model are recommended before miniaturizing cooled sensors.

Authors

Institutions

Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2024-10-31
DOI
https://doi.org/10.1016/j.jag.2024.104184
Citations
3
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
0.62

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing UAV-based uncooled thermal cameras in field conditions for precision agriculture

Magdalena Śmigaj, Quanxing Wan, Lammert Kooistra, Benjamin Brede
3 citations
International Journal of Applied Earth Observation and Geoinformation
Urban Heat Island Mitigation
0.62
article

Optimizing UAV-based uncooled thermal cameras in field conditions for precision agriculture

Magdalena Śmigaj, Quanxing Wan, Lammert Kooistra, Benjamin Brede
article en
3 citations

Abstract

Unoccupied aerial vehicles (UAVs) equipped with thermal cameras show great promise for precision agriculture, but challenges persist in analyzing land surface temperature (LST). This study explores the influence of ambient environmental conditions and intrinsic characteristics of uncooled thermal cameras on the accuracy of temperature measurements obtained through UAV-based thermal cameras. The research utilized DJI Matrice 210 quad-rotor UAVs equipped with FLIR Tau 2 and WIRIS 2 nd Gen thermal cameras. The experimental design involved strategically selected temperature reference materials of diverse compositions. UAV flights were conducted at varying altitudes, capturing thermal images correlated with ground-based thermocouple measurements. Results indicate that increasing flight altitude resulted in underestimated temperatures measured by UAVs for objects with higher kinematic temperatures, while objects with lower temperatures displayed higher measurements. The study integrates multiple environmental metrics, illustrating the complex influence of air temperature, humidity, net radiation, and wind speed on temperature measurements, with variations observed between FLIR Tau 2 and WIRIS 2 nd Gen camera models. Linear regression models highlight the diverse impact of these metrics on UAV-based temperature observations. Furthermore, an analysis of uncooled thermal sensor characteristics reveals a correlation between UAV-measured temperatures and the focal plane array (FPA) temperature, emphasizing the importance of considering intrinsic sensor dynamics. These findings provide valuable insights for enhancing the reliability of UAV-based thermal measurements in agricultural and environmental monitoring. The research underscores the necessity for a comprehensive understanding of both ambient conditions and camera-model-specific dynamics to optimize thermal imaging accuracy for precision agriculture applications. Accordingly, the recommended procedures have been described to reduce the effect of identified sources of influence. • Field practice standardization benefits from the strategic selection of reference materials. • Optimizing thermal flight altitudes balances accuracy, resolution, and battery. • FPA temperature fluctuations during thermal flights result in increased signal variations. • Calibrating environmental factors is only possible with complete on-site ancillary data. • User tests for each camera model are recommended before miniaturizing cooled sensors.

International Journal of Applied Earth Observation and GeoinformationVol. 134
GFZ Helmholtz Centre for Geosciences (DE), Wageningen University & Research (NL)
China Scholarship Council, Wageningen University and Research
Zero hunger
Openalex Percentile: Top 35%
Urban Heat Island Mitigation
0.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.