IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2024)

Comparison Between Thermal-Optical and L-Band Passive Microwave Soil Moisture Remote Sensing at Farm Scales: Towards UAV-Based Near-Surface Soil Moisture Mapping

  • Nan Ye,
  • Jeffrey P. Walker,
  • Ying Gao,
  • Ivan PopStefanija,
  • James Hills

DOI
https://doi.org/10.1109/JSTARS.2023.3329015
Journal volume & issue
Vol. 17
pp. 633 – 642

Abstract

Read online

The unmanned aerial vehicle (UAV) based remote sensing has drawn increased attention in precision agriculture. Lightweight optical and thermal sensors have been used widely on UAVs for a range of applications, and have been proposed by some as the best approach to map soil moisture at farm scales. However, passive microwave remote sensing has been widely acknowledged as the most accurate soil moisture mapping technology, and adopted by the soil moisture and ocean salinity and soil moisture active and passive satellite missions. Accordingly, it is postulated that this will also be the best technique for UAV-based near-surface soil moisture remote sensing, overcoming the spatial resolution limitation from low earth orbit altitude. Being so far limited by sensor availability, only a small number of studies have illustrated the potential of UAV-based near-surface soil moisture mapping using L-band microwave radiometers, and there has been no direct comparison with the thermal-optical alternative. To guide the design of future UAV-based soil moisture mapping systems, airborne optical, thermal infrared, and passive microwave observations collected from a scientific aircraft at low altitude over a center-pivot irrigation farm in Tasmania, Australia were used in this study to simulate UAV-based observations, and the performances of the thermal-optical and microwave techniques when compared at 75 m scale. The L-band microwave emission showed a superior sensitivity to near-surface soil moisture, and a higher and more consistent soil moisture retrieval accuracy than thermal-optical, with a root-mean-squared error of 0.05–0.06 m3/m3 and 0.05–0.09 m3/m3, respectively.

Keywords