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Remote Sens. 2018, 10(12), 1978; https://doi.org/10.3390/rs10121978

Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion

1
Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
2
International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, New York, NY 10027, USA
3
National Space Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
4
Department of Environmental Research and Innovation, Unit ENVISION, Luxembourg Institute of Science and Technology, L-4422 Belvaux, Luxembourg
5
Department of Geosciences and Natural Resource Management, University of Copenhagen, 1165 Copenhagen, Denmark
*
Authors to whom correspondence should be addressed.
Received: 8 October 2018 / Revised: 27 November 2018 / Accepted: 29 November 2018 / Published: 7 December 2018
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
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Abstract

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, when addressing the links between surface temperature and SM patterns via surface energy balances. Our methodology can be applied to operationally monitor VHR root-zone SM from UAS in agricultural and natural ecosystems. View Full-Text
Keywords: Thermal and optical remote sensing; Tree height; Very high spatial resolution; Surface energy balance; Unmanned Arial Systems (UAS) Thermal and optical remote sensing; Tree height; Very high spatial resolution; Surface energy balance; Unmanned Arial Systems (UAS)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wang, S.; Garcia, M.; Ibrom, A.; Jakobsen, J.; Josef Köppl, C.; Mallick, K.; Looms, M.C.; Bauer-Gottwein, P. Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion. Remote Sens. 2018, 10, 1978.

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