High resolution root-zone soil moisture (SM) maps are important for understanding the spatial variability of water availability in agriculture, ecosystems research and water resources management. Unmanned Aerial Systems (UAS) can ﬂexibly monitor land surfaces with thermal and optical imagery at very high spatial resolution (meter level, VHR) for most weather conditions. We modiﬁed the temperature–vegetation triangle approach to transfer it from satellite to UAS remote sensing. To consider the effects of the limited coverage of UAS mapping, theoretical dry/wet edges were introduced. The new method was tested on a bioenergy willow short rotation coppice site during growing seasons of 2016 and 2017. We demonstrated that by incorporating surface roughness parameters from the structure-from-motion in the interpretation of the measured land surface-atmosphere temperature gradients, the estimates of SM signiﬁcantly improved. The correlation coefﬁcient between estimated and measured SM increased from not signiﬁcant to 0.69 and the root mean square deviation decreased from 0.045 m3·m−3 to 0.025 m3·m−3 when considering temporal dynamics of surface roughness in the approach. The estimated SM correlated better with in-situ root-zone SM (15–30 cm) than with surface SM (0–5 cm) which is an important advantage over alternative remote sensing methods to estimate SM. The optimal spatial resolution of the triangle approach was found to be around 1.5 m, i.e. similar to the length scale of tree-crowns. This study highlights the importance of considering the 3-D ﬁne scale canopy structure,whenaddressingthelinksbetweensurfacetemperatureandSMpatternsviasurfaceenergy balances. Our methodology can be applied to operationally monitor VHR root-zone SM from UAS in agricultural and natural ecosystems.
- Thermal and optical remote sensing
- Tree height
- very high spatial resolution
- Surface energy balance
- Unmanned Arial Systems (UAS)
Wang, S., Garcia, M., Ibrom, A., Jakobsen, J., Köppl, C. J., Mallick, K., Looms, M. C., & Bauer-Gottwein, P. (2018). Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion. Remote Sensing, 10, . https://doi.org/10.3390/rs10121978