{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T23:03:09Z","timestamp":1772233389265,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,23]],"date-time":"2021-10-23T00:00:00Z","timestamp":1634947200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Evapotranspiration (ET) plays an important role in coupling the global energy, water, and biogeochemical cycles and explains ecosystem responses to global environmental change. However, quantifying and mapping the spatiotemporal distribution of ET across a large area is still a challenge, which limits our understanding of how a given ecosystem functions under a changing climate. This also poses a challenge to water managers, farmers, and ranchers who often rely on accurate estimates of ET to make important irrigation and management decisions. Over the last three decades, remote sensing-based ET modeling tools have played a significant role in managing water resources and understanding land-atmosphere interactions. However, several challenges, including limited applicability under all conditions, scarcity of calibration and validation datasets, and spectral and spatiotemporal constraints of available satellite sensors, exist in the current state-of-the-art remote sensing-based ET models and products. The special issue on \u201cRemote Sensing of Evapotranspiration II\u201d was launched to attract studies focusing on recent advances in remote sensing-based ET models to help address some of these challenges and find novel ways of applying and\/or integrating remotely sensed ET products with other datasets to answer key questions related to water and environmental sustainability. The 13 articles published in this special issue cover a wide range of topics ranging from field- to global-scale analysis, individual model to multi-model evaluation, single sensor to multi-sensor fusion, and highlight recent advances and applications of remote sensing-based ET modeling tools and products.<\/jats:p>","DOI":"10.3390\/rs13214260","type":"journal-article","created":{"date-parts":[[2021,10,24]],"date-time":"2021-10-24T22:07:11Z","timestamp":1635113231000},"page":"4260","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Recent Advances in Remote Sensing of Evapotranspiration"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2749-3549","authenticated-orcid":false,"given":"Nishan","family":"Bhattarai","sequence":"first","affiliation":[{"name":"School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7444-0461","authenticated-orcid":false,"given":"Pradeep","family":"Wagle","sequence":"additional","affiliation":[{"name":"Grazinglands Research Laboratory, US Department of Agriculture-Agricultural Research Service, El Reno, OK 73036, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.rse.2011.08.025","article-title":"Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources","volume":"122","author":"Anderson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2071","DOI":"10.1016\/j.agrformet.2009.05.016","article-title":"Advances in thermal infrared remote sensing for land surface modeling","volume":"149","author":"Kustas","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1002\/wat2.1168","article-title":"A review of remote sensing based actual evapotranspiration estimation","volume":"3","author":"Zhang","year":"2016","journal-title":"Wiley Interdiscip. Rev. Water"},{"key":"ref_4","first-page":"75","article-title":"Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate","volume":"49","author":"Bhattarai","year":"2016","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"112602","DOI":"10.1016\/j.rse.2021.112602","article-title":"The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models","volume":"264","author":"Trebs","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Allies, A., Demarty, J., Olioso, A., Bouzou Moussa, I., Issoufou, H.B.-A., Velluet, C., Bahir, M., Ma\u00efnassara, I., O\u00ef, M., and Chazarin, J.-P. (2020). Evapotranspiration Estimation in the Sahel Using a New Ensemble-Contextual Method. Remote Sens., 12.","DOI":"10.3390\/rs12030380"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wu, J., Lakshmi, V., Wang, D., Lin, P., Pan, M., Cai, X., Wood, E.F., and Zeng, Z. (2020). The Reliability of Global Remote Sensing Evapotranspiration Products over Amazon. Remote Sens., 12.","DOI":"10.3390\/rs12142211"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1126\/science.1099192","article-title":"GRACE measurements of mass variability in the Earth system","volume":"305","author":"Tapley","year":"2004","journal-title":"Science"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Javadian, M., Behrangi, A., Smith, W.K., and Fisher, J.B. (2020). Global Trends in Evapotranspiration Dominated by Increases across Large Cropland Regions. Remote Sens., 12.","DOI":"10.3390\/rs12071221"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"S Ha, W., R Diak, G., and F Krajewski, W. (2020). Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa. Remote Sens., 12.","DOI":"10.3390\/rs12142337"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Cha, M., Li, M., and Wang, X. (2020). Estimation of Seasonal Evapotranspiration for Crops in Arid Regions Using Multisource Remote Sensing Images. Remote Sens., 12.","DOI":"10.3390\/rs12152398"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Acharya, B., Sharma, V., Heitholt, J., Tekiela, D., and Nippgen, F. (2020). Quantification and Mapping of Satellite Driven Surface Energy Balance Fluxes in Semi-Arid to Arid Inter-Mountain Region. Remote Sens., 12.","DOI":"10.3390\/rs12244019"},{"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":"192","DOI":"10.1016\/j.isprsjprs.2017.03.022","article-title":"Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum","volume":"128","author":"Wagle","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2311","DOI":"10.5194\/hess-22-2311-2018","article-title":"Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US","volume":"22","author":"Bhattarai","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mallick, K., Wandera, L., Bhattarai, N., Hostache, R., Kleniewska, M., and Chormanski, J. (2018). A Critical Evaluation on the Role of Aerodynamic and Canopy\u2013Surface Conductance Parameterization in SEB and SVAT Models for Simulating Evapotranspiration: A Case Study in the Upper Biebrza National Park Wetland in Poland. Water, 10.","DOI":"10.3390\/w10121753"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.rse.2012.02.003","article-title":"Integration of soil moisture in SEBS for improving evapotranspiration estimation under water stress conditions","volume":"121","author":"Gokmen","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Li, Y., Huang, C., Kustas, W.P., Nieto, H., Sun, L., and Hou, J. (2020). Evapotranspiration Partitioning at Field Scales Using TSEB and Multi-Satellite Data Fusion in The Middle Reaches of Heihe River Basin, Northwest China. Remote Sens., 12.","DOI":"10.3390\/rs12193223"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bellvert, J., Jofre-\u0108ekalovi\u0107, C., Pelech\u00e1, A., Mata, M., and Nieto, H. (2020). Feasibility of Using the Two-Source Energy Balance Model (TSEB) with Sentinel-2 and Sentinel-3 Images to Analyze the Spatio-Temporal Variability of Vine Water Status in a Vineyard. Remote Sens., 12.","DOI":"10.3390\/rs12142299"},{"key":"ref_20","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_21","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_22","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Guti\u00e9rrez, V., St\u00f6ckle, C., Gil, P.M., and Meza, F.J. (2021). Evaluation of Penman-Monteith Model Based on Sentinel-2 Data for the Estimation of Actual Evapotranspiration in Vineyards. Remote Sens., 13.","DOI":"10.3390\/rs13030478"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Nagler, P.L., Barreto-Mu\u00f1oz, A., Chavoshi Borujeni, S., Nouri, H., Jarchow, C.J., and Didan, K. (2021). Riparian Area Changes in Greenness and Water Use on the Lower Colorado River in the USA from 2000 to 2020. Remote Sens., 13.","DOI":"10.5194\/egusphere-egu21-138"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Bajgain, R., Xiao, X., Wagle, P., Kimball, J.S., Brust, C., Basara, J.B., Gowda, P., Starks, P.J., and Neel, J.P.S. (2021). Comparing Evapotranspiration Products of Different Temporal and Spatial Scales in Native and Managed Prairie Pastures. Remote Sens., 13.","DOI":"10.3390\/rs13010082"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ahmed, K.R., Paul-Limoges, E., Rascher, U., and Damm, A. (2021). A First Assessment of the 2018 European Drought Impact on Ecosystem Evapotranspiration. Remote Sens., 13.","DOI":"10.3390\/rs13010016"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4260\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:21:54Z","timestamp":1760167314000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4260"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,23]]},"references-count":25,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214260"],"URL":"https:\/\/doi.org\/10.3390\/rs13214260","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,23]]}}}