{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T22:45:14Z","timestamp":1770331514992,"version":"3.49.0"},"reference-count":48,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T00:00:00Z","timestamp":1642032000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Utah Division of Water Resources","award":["2019UT258B"],"award-info":[{"award-number":["2019UT258B"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding the spatial variability in highly heterogeneous natural environments such as savannas and river corridors is an important issue in characterizing and modeling energy fluxes, particularly for evapotranspiration (ET) estimates. Currently, remote-sensing-based surface energy balance (SEB) models are applied widely and routinely in agricultural settings to obtain ET information on an operational basis for use in water resources management. However, the application of these models in natural environments is challenging due to spatial heterogeneity in vegetation cover and complexity in the number of vegetation species existing within a biome. In this research effort, small unmanned aerial systems (sUAS) data were used to study the influence of land surface spatial heterogeneity on the modeling of ET using the Two-Source Energy Balance (TSEB) model. The study area is the San Rafael River corridor in Utah, which is a part of the Upper Colorado River Basin that is characterized by arid conditions and variations in soil moisture status and the type and height of vegetation. First, a spatial variability analysis was performed using a discrete wavelet transform (DWT) to identify a representative spatial resolution\/model grid size for adequately solving energy balance components to derive ET. The results indicated a maximum wavelet energy between 6.4 m and 12.8 m for the river corridor area, while the non-river corridor area, which is characterized by different surface types and random vegetation, does not show a peak value. Next, to evaluate the effect of spatial resolution on latent heat flux (LE) estimation using the TSEB model, spatial scales of 6 m and 15 m instead of 6.4 m and 12.8 m, respectively, were used to simplify the derivation of model inputs. The results indicated small differences in the LE values between 6 m and 15 m resolutions, with a slight decrease in detail at 15 m due to losses in spatial variability. Lastly, the instantaneous (hourly) LE was extrapolated\/upscaled to daily ET values using the incoming solar radiation (Rs) method. The results indicated that willow and cottonwood have the highest ET rates, followed by grass\/shrubs and treated tamarisk. Although most of the treated tamarisk vegetation is in dead\/dry condition, the green vegetation growing underneath resulted in a magnitude value of ET.<\/jats:p>","DOI":"10.3390\/rs14020372","type":"journal-article","created":{"date-parts":[[2022,1,14]],"date-time":"2022-01-14T03:14:03Z","timestamp":1642130043000},"page":"372","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Using Remote Sensing to Estimate Scales of Spatial Heterogeneity to Analyze Evapotranspiration Modeling in a Natural Ecosystem"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0878-5861","authenticated-orcid":false,"given":"Ayman","family":"Nassar","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322, USA"},{"name":"Utah Water Research Laboratory, Utah State University, Logan, UT 84322, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2238-9550","authenticated-orcid":false,"given":"Alfonso","family":"Torres-Rua","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322, USA"},{"name":"Utah Water Research Laboratory, Utah State University, Logan, UT 84322, USA"}]},{"given":"Lawrence","family":"Hipps","sequence":"additional","affiliation":[{"name":"Department of Plants, Soils and Climate, Utah State University, Logan, UT 84322, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5727-4350","authenticated-orcid":false,"given":"William","family":"Kustas","sequence":"additional","affiliation":[{"name":"USDA, Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705, USA"}]},{"given":"Mac","family":"McKee","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322, USA"},{"name":"Utah Water Research Laboratory, Utah State University, Logan, UT 84322, USA"}]},{"given":"David","family":"Stevens","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322, USA"},{"name":"Utah Water Research Laboratory, Utah State University, Logan, UT 84322, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4250-6424","authenticated-orcid":false,"given":"H\u00e9ctor","family":"Nieto","sequence":"additional","affiliation":[{"name":"Complutum Tecnolog\u00edas de la Informaci\u00f3n Geogr\u00e1fica S.L. (COMPLUTIG), 28801 Alcala de Henares, Madrid, Spain"}]},{"given":"Daniel","family":"Keller","sequence":"additional","affiliation":[{"name":"Utah Division of Wildlife Resources, Salt Lake City, UT 84116, USA"}]},{"given":"Ian","family":"Gowing","sequence":"additional","affiliation":[{"name":"Utah Water Research Laboratory, Utah State University, Logan, UT 84322, USA"}]},{"given":"Calvin","family":"Coopmans","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Utah State University, Logan, UT 84322, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/07352680701402503","article-title":"Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration","volume":"26","author":"Glenn","year":"2007","journal-title":"Crit. Rev. Plant Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"755","DOI":"10.5194\/hess-25-755-2021","article-title":"Long-Term Water Stress and Drought Monitoring of Mediterranean Oak Savanna Vegetation Using Thermal Remote Sensing","volume":"25","author":"Chen","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Nassar, A., Torres-Rua, A., Kustas, W., Nieto, H., McKee, M., Hipps, L., Stevens, D., Alfieri, J., Prueger, J., and Alsina, M.M. (2020). Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards. Remote Sens., 12.","DOI":"10.3390\/rs12030342"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2187","DOI":"10.5194\/hess-22-2187-2018","article-title":"Assessment of Actual Evapotranspiration over a Semiarid Heterogeneous Land Surface by Means of Coupled Low-Resolution Remote Sensing Data with an Energy Balance Model: Comparison to Extra-Large Aperture Scintillometer Measurements","volume":"22","author":"Saadi","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1029\/97RG01754","article-title":"Representation of Heterogeneity Effects in Earth System Modeling: Experience from Land Surface Modeling","volume":"35","author":"Giorgi","year":"1997","journal-title":"Rev. Geophys."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"eaam8328","DOI":"10.1126\/science.aam8328","article-title":"Climate, Ecosystems, and Planetary Futures: The Challenge to Predict Life in Earth System Models","volume":"359","author":"Bonan","year":"2018","journal-title":"Science"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Krinner, G., Viovy, N., de Noblet-Ducoudr\u00e9, N., Og\u00e9e, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Colin Prentice, I. (2005). A Dynamic Global Vegetation Model for Studies of the Coupled Atmosphere-Biosphere System. Glob. Biogeochem. Cycles, 19.","DOI":"10.1029\/2003GB002199"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.agrformet.2012.09.012","article-title":"Climate Change, Phenology, and Phenological Control of Vegetation Feedbacks to the Climate System","volume":"169","author":"Richardson","year":"2013","journal-title":"Agric. For. Meteorol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.5194\/hess-19-2017-2015","article-title":"Inter-Comparison of Energy Balance and Hydrological Models for Land Surface Energy Flux Estimation over a Whole River Catchment","volume":"19","author":"Guzinski","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0022-1694(99)00195-X","article-title":"Comparing Evapotranspiration Estimates from Satellites, Hydrological Models and Field Data","volume":"229","author":"Kite","year":"2000","journal-title":"J. Hydrol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4028","DOI":"10.1002\/hyp.8394","article-title":"Improved Methods for Estimating Monthly and Growing Season ET Using METRIC Applied to Moderate Resolution Satellite Imagery","volume":"25","author":"Kjaersgaard","year":"2011","journal-title":"Hydrol. Processes"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1175\/1520-0450(1990)029<0704:EOEWAO>2.0.CO;2","article-title":"Estimates of Evapotranspiration with a One- and Two-Layer Model of Heat Transfer over Partial Canopy Cover","volume":"29","author":"Kustas","year":"1990","journal-title":"J. Appl. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Acharya, B., and Sharma, V. (2021). Comparison of Satellite Driven Surface Energy Balance Models in Estimating Crop Evapotranspiration in Semi-Arid to Arid Inter-Mountain Region. Remote Sens., 13.","DOI":"10.3390\/rs13091822"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/0168-1923(95)02265-Y","article-title":"Source Approach for Estimating Soil and Vegetation Energy Fluxes in Observations of Directional Radiometric Surface Temperature","volume":"77","author":"Norman","year":"1995","journal-title":"Agric. For. Meteorol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Gao, R., Torres-Rua, A.F., Nassar, A., Alfieri, J., Aboutalebi, M., Hipps, L., Ortiz, N.B., Mcelrone, A.J., Coopmans, C., and Kustas, W. (2021). Evapotranspiration Partitioning Assessment Using a Machine-Learning-Based Leaf Area Index and the Two-Source Energy Balance Model with sUAV Information. Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI, International Society for Optics and Photonics. (This Conference Conducted in USA).","DOI":"10.1117\/12.2586259"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1016\/j.agrformet.2009.06.012","article-title":"A Comparison of Operational Remote Sensing-Based Models for Estimating Crop Evapotranspiration","volume":"149","author":"Neale","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.rse.2006.11.028","article-title":"An Intercomparison of the Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) Modeling Schemes","volume":"108","author":"Timmermans","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.rse.2006.07.007","article-title":"Regional Evaporation Estimates from Flux Tower and MODIS Satellite Data","volume":"106","author":"Cleugh","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1016\/j.rse.2006.01.020","article-title":"Exploiting Synergies of Global Land Cover Products for Carbon Cycle Modeling","volume":"101","author":"Jung","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1080\/02626669609491522","article-title":"Use of Remote Sensing for Evapotranspiration Monitoring over Land Surfaces","volume":"41","author":"Kustas","year":"1996","journal-title":"Hydrol. Sci. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S0168-1923(03)00064-9","article-title":"Scale Issues in Land\u2013atmosphere Interactions: Implications for Remote Sensing of the Surface Energy Balance","volume":"117","author":"Brunsell","year":"2003","journal-title":"Agric. For. Meteorol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"6457","DOI":"10.1080\/01431161.2010.512929","article-title":"Down-Scaling of SEBAL Derived Evapotranspiration Maps from MODIS (250 M) to Landsat (30 M) Scales","volume":"32","author":"Hong","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1800","DOI":"10.1002\/2015WR017772","article-title":"Impact of Scale\/resolution on Evapotranspiration from Landsat and MODIS Images","volume":"52","author":"Sharma","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1175\/1525-7541(2004)005<0343:AMRSMF>2.0.CO;2","article-title":"A Multiscale Remote Sensing Model for Disaggregating Regional Fluxes to Micrometeorological Scales","volume":"5","author":"Anderson","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2006.11.032","article-title":"Effect of Remote Sensing Spatial Resolution on Interpreting Tower-Based Flux Observations","volume":"112","author":"Li","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/S0034-4257(99)00081-4","article-title":"Evaluating the Effects of Subpixel Heterogeneity on Pixel Average Fluxes","volume":"74","author":"Kustas","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Neale, C.M.U., Geli, H., Taghvaeian, S., Masih, A., Pack, R.T., Simms, R.D., Baker, M., Milliken, J.A., O\u2019Meara, S., and Witherall, A.J. (2011). Estimating Evapotranspiration of Riparian Vegetation Using High Resolution Multispectral, Thermal Infrared and Lidar Data. Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, International Society for Optics and Photonics. (This conference conducted in USA).","DOI":"10.1117\/12.903246"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1007\/s00267-014-0318-7","article-title":"Effects of Flooding and Tamarisk Removal on Habitat for Sensitive Fish Species in the San Rafael River, Utah: Implications for Fish Habitat Enhancement and Future Restoration Efforts","volume":"54","author":"Keller","year":"2014","journal-title":"Environ. Manag."},{"key":"ref_29","unstructured":"Fortney, S.T. (2021, June 25). A Century of Geomorphic Change of the San Rafael River and Implications for River Rehabilitation. Available online: https:\/\/digitalcommons.usu.edu\/etd\/4363."},{"key":"ref_30","unstructured":"Budy, P. (2021, June 25). Habitat Needs, Movement Patterns, and Vital Rates of Endemic Utah Fishes in a Tributary to the Green River, Utah. Available online: https:\/\/digitalcommons.usu.edu\/wats_facpub\/870."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4309","DOI":"10.1080\/0143116042000192358","article-title":"Linking Spatial Patterns of Bird and Butterfly Species Richness with Landsat TM Derived NDVI","volume":"25","author":"Seto","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Morettin, P.A. (1996). From Fourier to Wavelet Analysis of Time Series. COMPSTAT, Physica-Verlag HD.","DOI":"10.1007\/978-3-642-46992-3_10"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1080\/11956860.2002.11682704","article-title":"Wavelets, Boundaries, and the Spatial Analysis of Landscape Pattern","volume":"9","author":"Csillag","year":"2002","journal-title":"\u00c9coscience"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"205","DOI":"10.2307\/2261007","article-title":"Characterizing Canopy Gap Structure in Forests Using Wavelet Analysis","volume":"80","author":"Bradshaw","year":"1992","journal-title":"J. Ecol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"6425","DOI":"10.1080\/01431160903418241","article-title":"Comparing Direct Image and Wavelet Transform-Based Approaches to Analysing Remote Sensing Imagery for Predicting Wildlife Distribution","volume":"31","author":"Murwira","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1007\/s00442-008-0993-2","article-title":"Wavelet Analysis of Ecological Time Series","volume":"156","author":"Cazelles","year":"2008","journal-title":"Oecologia"},{"key":"ref_37","unstructured":"Bruce, A., and Gao, H.-Y. (1996). Applied Wavelet Analysis with S-PLUS, Springer."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1111\/j.1526-100X.1997.00103.x","article-title":"Classification and Mapping of Riparian Systems Using Airborne Multispectral Videography","volume":"5","author":"Neale","year":"2008","journal-title":"Restor. Ecol."},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/S0168-1923(99)00012-X","article-title":"Reply to Comments about the Basic Equations of Dual-Source Vegetation\u2013atmosphere Transfer Models","volume":"94","author":"Kustas","year":"1999","journal-title":"Agric. For. Meteorol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s00271-018-0611-y","article-title":"Impact of Different within-Canopy Wind Attenuation Formulations on Modelling Sensible Heat Flux Using TSEB","volume":"37","author":"Nieto","year":"2019","journal-title":"Irrig. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Campbell, G.S., and Norman, J.M. (1998). An Introduction to Environmental Biophysics, Springer Science and Business Media.","DOI":"10.1007\/978-1-4612-1626-1"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/S0034-4257(00)00119-X","article-title":"Measuring Fractional Cover and Leaf Area Index in Arid Ecosystems","volume":"74","author":"White","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Nassar, A., Torres-Rua, A., Kustas, W., Alfieri, J., Hipps, L., Prueger, J., Nieto, H., Alsina, M.M., White, W., and McKee, L. (2021). Assessing Daily Evapotranspiration Methodologies from One-Time-of-Day sUAS and EC Information in the GRAPEX Project. Remote Sens., 13.","DOI":"10.3390\/rs13152887"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1885","DOI":"10.5194\/hess-18-1885-2014","article-title":"Upscaling of Evapotranspiration Fluxes from Instantaneous to Daytime Scales for Thermal Remote Sensing Applications","volume":"18","author":"Cammalleri","year":"2014","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.rse.2006.03.013","article-title":"Quantifying Spatial Heterogeneity at the Landscape Scale Using Variogram Models","volume":"103","author":"Garrigues","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Wu, L., Qin, Q., Liu, X., Ren, H., Wang, J., Zheng, X., Ye, X., and Sun, Y. (2016). Spatial Up-Scaling Correction for Leaf Area Index Based on the Fractal Theory. Remote Sens., 8.","DOI":"10.3390\/rs8030197"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1006\/jare.2002.0972","article-title":"Seasonal Estimates of Actual Evapo-Transpiration from Tamarix Ramosissima Stands Using Three-Dimensional Eddy Covariance","volume":"52","author":"Cleverly","year":"2002","journal-title":"J. Arid Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/2\/372\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:14:59Z","timestamp":1760364899000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/2\/372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,13]]},"references-count":48,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14020372"],"URL":"https:\/\/doi.org\/10.3390\/rs14020372","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,13]]}}}