{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:26:24Z","timestamp":1762507584653,"version":"build-2065373602"},"reference-count":67,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T00:00:00Z","timestamp":1544140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ERA-NET, Innovation Fund Denmark","award":["125-2013-5"],"award-info":[{"award-number":["125-2013-5"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u2013vegetation 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\u2219m\u22123 to 0.025 m3\u2219m\u22123 when considering temporal dynamics of surface roughness in the approach. The estimated SM correlated better with in-situ root-zone SM (15\u201330 cm) than with surface SM (0\u20135 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.<\/jats:p>","DOI":"10.3390\/rs10121978","type":"journal-article","created":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T03:36:41Z","timestamp":1544413001000},"page":"1978","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Mapping Root-Zone Soil Moisture Using a Temperature\u2013Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3385-3109","authenticated-orcid":false,"given":"Sheng","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark"}]},{"given":"Monica","family":"Garcia","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark"},{"name":"International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, New York, NY 10027, USA"}]},{"given":"Andreas","family":"Ibrom","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark"}]},{"given":"Jakob","family":"Jakobsen","sequence":"additional","affiliation":[{"name":"National Space Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark"}]},{"given":"Christian","family":"Josef K\u00f6ppl","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2735-930X","authenticated-orcid":false,"given":"Kaniska","family":"Mallick","sequence":"additional","affiliation":[{"name":"Department of Environmental Research and Innovation, Unit ENVISION, Luxembourg Institute of Science and Technology, L-4422 Belvaux, Luxembourg"}]},{"given":"Majken C.","family":"Looms","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Natural Resource Management, University of Copenhagen, 1165 Copenhagen, Denmark"}]},{"given":"Peter","family":"Bauer-Gottwein","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating soil moisture-climate interactions in a changing climate: A review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth-Science Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1175\/BAMS-D-12-00124.1","article-title":"A drought monitoring and forecasting system for sub-sahara african water resources and food security","volume":"95","author":"Sheffield","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_3","first-page":"17","article-title":"Comparison of temporal trends from multiple soil moisture data sets and precipitation: The implication of irrigation on regional soil moisture trend","volume":"48","author":"Qiu","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2627","DOI":"10.3390\/rs70302627","article-title":"Assessment of surface soil moisture using high-resolution multi-spectral imagery and artificial neural networks","volume":"7","author":"Jensen","year":"2015","journal-title":"Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Andreasen, M., Jensen, K.H., Desilets, D., Franz, T.E., Zreda, M., Bogena, H.R., and Looms, M.C. (2017). Status and Perspectives on the Cosmic-Ray Neutron Method for Soil Moisture Estimation and Other Environmental Science Applications. Vadose Zo. J., 16.","DOI":"10.2136\/vzj2017.04.0086"},{"key":"ref_6","first-page":"934","article-title":"The potential of multitemporal Aqua and Terra MODIS apparent thermal inertia as a soil moisture indicator","volume":"13","author":"Peters","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1177\/0309133309338997","article-title":"A review of Ts\/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture","volume":"33","author":"Petropoulos","year":"2009","journal-title":"Prog. Phys. Geogr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2605","DOI":"10.5194\/hess-14-2605-2010","article-title":"Error characterisation of global active and passive microwave soil moisture datasets","volume":"14","author":"Dorigo","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.pce.2015.02.009","article-title":"Surface soil moisture retrievals from remote sensing: Current status, products & future trends","volume":"83\u201384","author":"Petropoulos","year":"2015","journal-title":"Phys. Chem. Earth"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/TGRS.2002.808243","article-title":"Soil moisture retrieval from AMSR-E","volume":"41","author":"Njoku","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1016\/j.agrformet.2009.03.004","article-title":"Estimating volumetric surface moisture content for cropped soils using a soil wetness index based on surface temperature and NDVI","volume":"149","author":"Mallick","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1016\/j.agrformet.2017.10.023","article-title":"Incorporating diffuse radiation into a light use efficiency and evapotranspiration model: An 11-year study in a high latitude deciduous forest","volume":"248","author":"Wang","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2529","DOI":"10.3390\/rs3112529","article-title":"Multispectral remote sensing from unmanned aircraft: Image processing workflows and applications for rangeland environments","volume":"3","author":"Laliberte","year":"2011","journal-title":"Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TGRS.2008.2010457","article-title":"Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle","volume":"47","author":"Berni","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.rse.2011.10.007","article-title":"Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera","volume":"117","author":"Berni","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6545","DOI":"10.5194\/bg-13-6545-2016","article-title":"Crop water stress maps for an entire growing season from visible and thermal UAV imagery","volume":"13","author":"Hoffmann","year":"2016","journal-title":"Biogeosciences"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1002\/ird.2098","article-title":"Spatial Root Zone Soil Water Content Estimation in Agricultural Lands Using Bayesian-Based Artificial Neural Networks and High- Resolution Visual, NIR, and Thermal Imagery","volume":"66","author":"Jensen","year":"2017","journal-title":"Irrig. Drain."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/0034-4257(94)90020-5","article-title":"Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index","volume":"49","author":"Moran","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"22207","DOI":"10.1117\/1.JRS.12.022207","article-title":"Soil moisture estimation for spring wheat in a semiarid area based on low-altitude remote-sensing data collected by small-sized unmanned aerial vehicles","volume":"12","author":"Wang","year":"2018","journal-title":"J. Appl. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1175\/1520-0450(1976)015<0811:CFEVIT>2.0.CO;2","article-title":"Compensating for environmental variability in the thermal inertia approach to remote sensing of soil moisture","volume":"15","author":"Idso","year":"1976","journal-title":"J. Appl. Meteorol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0034-4257(01)00274-7","article-title":"A simple interpretation of the surface temperature\/vegetation index space for assessment of surface moisture status","volume":"79","author":"Sandholt","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.rse.2007.02.025","article-title":"Estimation of diurnal air temperature using MSG SEVIRI data in West Africa","volume":"110","author":"Stisen","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.1029\/WR017i004p01133","article-title":"Canopy temperature as a crop water stress indicator","volume":"17","author":"Jackson","year":"1981","journal-title":"Water Resour. Res."},{"key":"ref_24","first-page":"36601","article-title":"Progress in soil moisture estimation from remote sensing data for agricultural drought monitoring - art. no. 636601","volume":"6366","author":"Yan","year":"2006","journal-title":"Remote Sens. Environ. Monit. GIS Appl. Geol. VI"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.rse.2003.09.008","article-title":"Using directional TIR measurements and 3D simulations to assess the limitations and opportunities of water stress indices","volume":"90","author":"Luquet","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1109\/36.58983","article-title":"U sing Spatial Context in Satellite Data to Infer Regional Scale Evapotranspiration","volume":"28","author":"Price","year":"1990","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the relationship between NDVI, fractional vegetation cover, and leaf area index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/0168-1923(95)02261-U","article-title":"An interpretation of methodologies for indirect measurement of soil water content","volume":"77","author":"Carlson","year":"1995","journal-title":"Agric. For. Meteorol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.rse.2014.04.002","article-title":"Accuracy of the Temperature-Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions","volume":"149","author":"Garcia","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S0168-1923(99)00005-2","article-title":"Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover","volume":"94","author":"Kustas","year":"1999","journal-title":"Agric. For. Meteorol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"85","DOI":"10.5194\/hess-6-85-2002","article-title":"The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes","volume":"6","author":"Su","year":"2002","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s10546-015-0090-0","article-title":"Seeing the Fields and Forests: Application of Surface-Layer Theory and Flux-Tower Data to Calculating Vegetation Canopy Height","volume":"158","author":"Pennypacker","year":"2016","journal-title":"Boundary-Layer Meteorol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.5194\/hess-14-2661-2010","article-title":"Aerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in China","volume":"14","author":"Colin","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"\u201cStructure-from-Motion\u201d photogrammetry: A low-cost, effective tool for geoscience applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.eja.2014.01.004","article-title":"Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods","volume":"55","author":"Angileri","year":"2014","journal-title":"Eur. J. Agron."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2017.07.032","article-title":"A time domain solution of the Modified Temperature Vegetation Dryness Index (MTVDI) for continuous soil moisture monitoring","volume":"200","author":"Zhu","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Bandini, F., Lopez-Tamayo, A., Merediz-Alonso, G., Olesen, D., Jakobsen, J., Wang, S., Garcia, M., and Bauer-Gottwein, P. (2018). Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico. Hydrogeol. J., 1\u201316.","DOI":"10.1007\/s10040-018-1755-9"},{"key":"ref_38","unstructured":"Wang, S., Dam-Hansen, C., Zarco Tejada, P.J., Thorseth, A., Malureanu, R., Bandini, F., Jakobsen, J., Ibrom, A., Bauer-Gottwein, P., and Garcia, M. (2017, January 19\u201321). Optimizing sensitivity of Unmanned Aerial System optical sensors for low zenith angles and cloudy conditions. Poster session presented at 10th EARSeL SIG Imaging Spectroscopy Workshop, Zurich, Switzerland. Proceedings of the 10th EARSeL SIG Imaging Spectroscopy Workshop, Zurich, Switzerland."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(94)90090-6","article-title":"Relations between evaporation coefficients and vegetation indices studied by model simulations","volume":"50","author":"Choudhury","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1080\/01431169308904400","article-title":"On the relationship between thermal emissivity\\nand normalized vegetation index for natural surfaces","volume":"14","author":"Owe","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","first-page":"1127","article-title":"A new long-wave formula for estimating downward clear-sky radiation at the surface","volume":"122","author":"Prata","year":"1996","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2062","DOI":"10.1016\/j.rse.2011.04.008","article-title":"Variation and directional anisotropy of reflectance at the crown scale\u2014Implications for tree species classification in digital aerial images","volume":"115","author":"Korpela","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.rse.2010.08.010","article-title":"Air temperature estimation with MSG-SEVIRI data: Calibration and validation of the TVX algorithm for the Iberian Peninsula","volume":"115","author":"Nieto","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Long, D., Singh, V.P., and Scanlon, B.R. (2012). Deriving theoretical boundaries to address scale dependencies of triangle models for evapotranspiration estimation. J. Geophys. Res. Atmos., 117.","DOI":"10.1029\/2011JD017079"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Brutsaert, W. (1982). Evaporation into the Atmosphere. Theory, History, and Applications, D. Reidel Co.","DOI":"10.1007\/978-94-017-1497-6"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1002\/qj.49709942209","article-title":"Momentum, heat and water vapour transfer to and from natural and artificial surfaces","volume":"99","author":"Garratt","year":"1973","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Nishida, K., Nemani, R.R., Running, S.W., and Glassy, J.M. (2003). An operational remote sensing algorithm of land surface evaporation. J. Geophys. Res. Atmos., 108.","DOI":"10.1029\/2002JD002062"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/0168-1923(90)90033-3","article-title":"Estimation of the soil heat flux\/net radiation ratio from spectral data","volume":"49","author":"Kustas","year":"1990","journal-title":"Agric. For. Meteorol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s10546-006-9093-1","article-title":"Utility of radiometric-aerodynamic temperature relations for heat flux estimation","volume":"122","author":"Kustas","year":"2007","journal-title":"Boundary-Layer Meteorol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/0378-3774(95)01182-X","article-title":"Willow stand evapotranspiration simulated for Swedish soils","volume":"28","author":"Persson","year":"1995","journal-title":"Agric. Water Manag."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/S0022-1694(02)00239-1","article-title":"Mapping spatial variation in surface soil water content: comparison of ground-penetrating radar and time domain reflectometry","volume":"269","author":"Huisman","year":"2002","journal-title":"J. Hydrol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.agrformet.2013.10.006","article-title":"Effects of fine-scale soil moisture and canopy heterogeneity on energy and water fluxes in a northern temperate mixed forest","volume":"184","author":"He","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Vivoni, E.R., Moreno, H.A., Mascaro, G., Rodriguez, J.C., Watts, C.J., Garatuza-Payan, J., and Scott, R.L. (2008). Observed relation between evapotranspiration and soil moisture in the North American monsoon region. Geophys. Res. Lett., 35.","DOI":"10.1029\/2008GL036001"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2013.05.010","article-title":"Using radiometric surface temperature for surface energy flux estimation in Mediterranean drylands from a two-source perspective","volume":"136","author":"Morillas","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.rse.2013.05.007","article-title":"Estimation of aerodynamic roughness of a harvested Douglas-fir forest using airborne LiDAR","volume":"136","author":"Christen","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"5320","DOI":"10.1002\/2016WR020111","article-title":"Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships","volume":"53","author":"Haghighi","year":"2017","journal-title":"Water Resour. Res."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1007\/s10546-009-9404-4","article-title":"Exploring the effects of microscale structural heterogeneity of forest canopies using large-eddy simulations","volume":"132","author":"Bohrer","year":"2009","journal-title":"Boundary-Layer Meteorol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/BF00709229","article-title":"Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index","volume":"71","author":"Raupach","year":"1994","journal-title":"Boundary-Layer Meteorol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.jhydrol.2007.05.023","article-title":"Estimation of soil boundary-layer resistance in sparse semiarid stands for evapotranspiration modelling","volume":"342","author":"Were","year":"2007","journal-title":"J. Hydrol."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Wallace, L., Lucieer, A., Malenovsk\u1ef3, Z., Turner, D., and Vop\u011bnka, P. (2016). Assessment of forest structure using two UAV techniques: A comparison of airborne laser scanning and structure from motion (SfM) point clouds. Forests, 7.","DOI":"10.3390\/f7030062"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1612","DOI":"10.3390\/s7081612","article-title":"An overview of the \u201ctriangle method\u201d for estimating surface evapotranspiration and soil moisture from satellite imagery","volume":"7","author":"Carlson","year":"2007","journal-title":"Sensors"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Phillips, C.J., Marden, M., and Suzanne, L.M. (2014). Observations of root growth of young poplar and willow planting types. New Zeal. J. For. Sci., 44.","DOI":"10.1186\/s40490-014-0015-6"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"3114","DOI":"10.3390\/rs70303114","article-title":"Evaluation of the airborne CASI\/TASI Ts-VI space method for estimating near-surface soil moisture","volume":"7","author":"Fan","year":"2015","journal-title":"Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.rse.2011.10.018","article-title":"A method to estimate soil moisture from Airborne Hyperspectral Scanner (AHS) and ASTER data: Application to SEN2FLEX and SEN3EXP campaigns","volume":"117","author":"Sobrino","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JSTARS.2014.2349354","article-title":"Impact of Temporal Autocorrelation Mismatch on the Assimilation of Satellite-Derived Surface Soil Moisture Retrievals","volume":"7","author":"Qiu","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Babaeian, E., Sadeghi, M., Franz, T.E., Jones, S., and Tuller, M. (2018). Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations. Remote Sens. Environ.","DOI":"10.1016\/j.rse.2018.04.029"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Sadeghi, M., Babaeian, E., Tuller, M., and Jones, S.B. (2017). The optical trapezoid model: A novel approach to remote sensing of soil moisture applied to Sentinel-2 and Landsat-8 observations. Remote Sens. Environ.","DOI":"10.1016\/j.rse.2017.05.041"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/1978\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:31:57Z","timestamp":1760196717000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/1978"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,7]]},"references-count":67,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["rs10121978"],"URL":"https:\/\/doi.org\/10.3390\/rs10121978","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,12,7]]}}}