Field-Based Calibration of Unmanned Aerial Vehicle Thermal Infrared Imagery with Temperature-Controlled References.

Xiongzhe Han,Rahul Raman,Haly Neely,J Alex Thomasson,Jeffrey Siegfried,Tianyi Wang,Vaishali Swaminathan,Nithya Rajan

doi:10.3390/s20247098

Abstract

Accurate and reliable calibration methods are required when applying unmanned aerial vehicle (UAV)-based thermal remote sensing in precision agriculture for crop stress monitoring, irrigation planning, and harvesting. The primary objective of this study was to improve the calibration accuracies of UAV-based thermal images using temperature-controlled ground references. Two temperature-controlled ground references were installed in the field to serve as high- and low-temperature references, approximately spanning the expected range of crop surface temperatures during the growing season. Our results showed that the proposed method using temperature-controlled references was able to reduce errors due to ambient conditions from 9.29 to 1.68 °C, when tested with validation panels. There was a significant improvement in crop temperature estimation from the thermal image mosaic, as the error reduced from 14.0 °C in the un-calibrated image to 1.01 °C in the calibrated image. Furthermore, a multiple linear regression model (R2 = 0.78; p-value < 0.001; relative RMSE = 2.42%) was established to quantify soil moisture content based on canopy surface temperature and soil type, using UAV-based thermal image data and soil electrical conductivity (ECa) data as the predictor variables.

Highlights

Remote sensing of plant temperatures has been used in breeding for the identification of traits related to disease resistance [1,2], water stress tolerance [1,3], and tolerance to other biotic and abiotic stresses [1,2,3,4]
Conclusions the temperature calibration accuracy of unmanned aerial vehicle (UAV)-based thermal images obtained from 40 m above the ground level (AGL)
The closed-loop temperature control method, applied to both the low- and high-temperature temperature calibration accuracy of UAV-based thermal images obtained from 40 m AGL

Summary

Introduction

Remote sensing of plant temperatures has been used in breeding for the identification of traits related to disease resistance [1,2], water stress tolerance [1,3], and tolerance to other biotic and abiotic stresses [1,2,3,4]. Most of the plant canopy and soil temperature measurements currently employed use contact probes or thermometers [7,8,9] and non-contact type hand-held infrared thermometers [10,11,12,13]. Wang et al [13] proposed using an inexpensive infrared optical sensor for reliable and precise canopy temperature measurements in a large rice field; errors due to environmental effects were not considered in the study, and because these non-contact sensors were non-imaging sensors, they had low spatial detail and did not provide much information about variability across the field. It is possible to extract field variability and crop status information via satellite and aerial thermal remote sensing [14,15,16,17] by analyzing the spatial temperature patterns from images. Thermal image data acquired with unmanned aerial vehicles (UAVs) may be more effective for agronomic applications because of their potentially higher temporal and spatial resolutions [18,19,20,21]

Objectives

Methods

Results

Conclusion