{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T07:13:22Z","timestamp":1768461202672,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,9,13]],"date-time":"2017-09-13T00:00:00Z","timestamp":1505260800000},"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>Estimation of latent heat flux at the agricultural field scale is required for proper water management. The current generation thermal sensors except Landsat-8 provide data on the order of 1000 m. The aim of this study is to test three approaches based on contextual models using only remote sensing datasets for the disaggregation of latent heat flux over India. The first two approaches are, respectively, based on the estimation of the evaporative fraction (EF) and solar radiation ratio at coarser resolution and disaggregating them to yield the latent heat flux at a finer resolution. The third approach is based on disaggregation of the thermal data and estimating a finer resolution latent heat flux. The three approaches were tested using MODIS datasets and the validation was done using the Bowen Ratio energy balance observations at five sites across India. From the validation, it was observed that the first two approaches performed similarly and better than the third approach at all five sites. The third approach, based on the disaggregation of the thermal data, yielded larger errors. In addition to better performance, the second approach based on the disaggregation of solar radiation ratio was simpler and required lesser data processing than the other approaches. In addition, the first two approaches captured the spatial pattern of latent heat flux without introducing any artefacts in the final output.<\/jats:p>","DOI":"10.3390\/rs9090949","type":"journal-article","created":{"date-parts":[[2017,9,13]],"date-time":"2017-09-13T10:17:32Z","timestamp":1505297852000},"page":"949","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Spatial Disaggregation of Latent Heat Flux Using Contextual Models over India"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6227-4873","authenticated-orcid":false,"given":"Rajasekaran","family":"Eswar","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muddu","family":"Sekhar","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India"},{"name":"Interdisciplinary Centre for Water Research, Indian Institute of Science, Bangalore 560012, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bimal","family":"Bhattacharya","sequence":"additional","affiliation":[{"name":"Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380015, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soumya","family":"Bandyopadhyay","sequence":"additional","affiliation":[{"name":"Indian Space Research Organisation, Bangalore 560231, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/S0022-1694(98)00253-4","article-title":"A remote sensing surface energy balance algorithm for land (SEBAL). 1: Formulation","volume":"213","author":"Bastiaanssen","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1061\/(ASCE)0733-9437(2007)133:4(380)","article-title":"Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)\u2014Model","volume":"133","author":"Allen","year":"2007","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_3","first-page":"161","article-title":"Evapotranspiration from a Satellite-Based Surface Energy Balance for the Snake Plain Aquifer in Idaho","volume":"4","author":"Allen","year":"2005","journal-title":"California Water Plan"},{"key":"ref_4","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_5","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/S0034-4257(03)00036-1","article-title":"Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship","volume":"85","author":"Kustas","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1016\/j.rse.2006.10.006","article-title":"A vegetation index based technique for spatial sharpening of thermal imagery","volume":"107","author":"Agam","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"L02402","DOI":"10.1029\/2007GL032195","article-title":"Utility of thermal image sharpening for monitoring field-scale evapotranspiration over rainfed and irrigated agricultural regions","volume":"35","author":"Agam","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.rse.2013.03.023","article-title":"Development and verification of a non-linear disaggregation method (NL-DisTrad) to downscale MODIS land surface temperature to the spatial scale of Landsat thermal data to estimate evapotranspiration","volume":"135","author":"Bindhu","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"12,029","DOI":"10.1002\/2013JD020813","article-title":"A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India","volume":"118","author":"Eswar","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"1646","DOI":"10.1016\/j.agrformet.2009.05.006","article-title":"Latent heat flux estimation in clear sky days over Indian agroecosystems using noon-time satellite remote sensing data","volume":"149","author":"Mallick","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.jhydrol.2010.03.030","article-title":"Regional clear sky evapotranspiration over agricultural land using remote sensing data from Indian geostationary meteorological satellite","volume":"387","author":"Bhattacharya","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Eswar, R., Sekhar, M., and Bhattacharya, B.K. (2017). Comparison of three remote sensing based models for the estimation of latent heat flux over India. Hydrol. Sci., accepted.","DOI":"10.1080\/02626667.2017.1404067"},{"key":"ref_14","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_15","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.rse.2013.07.001","article-title":"Temporal upscaling of instantaneous evapotranspiration: An intercomparison of four methods using eddy covariance measurements and MODIS data","volume":"138","author":"Tang","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_16","first-page":"35","article-title":"Upscaling latent heat flux for thermal remote sensing studies: Comparison of alternative approaches and correction of bias","volume":"468\u2013469","author":"McVicar","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1080\/01431161.2016.1145363","article-title":"Disaggregation of LST over India: Comparative analysis of different vegetation indices","volume":"37","author":"Eswar","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2773","DOI":"10.1029\/1999GL006049","article-title":"A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations","volume":"26","author":"Jiang","year":"1999","journal-title":"Geophys. Res. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.rse.2004.06.020","article-title":"Comparison of evaporative fractions estimated from AVHRR and MODIS sensors over South Florida","volume":"93","author":"Venturini","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2006.02.019","article-title":"Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains","volume":"103","author":"Batra","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.rse.2009.10.012","article-title":"An application of the Ts\u2013VI triangle method with enhanced edges determination for evapotranspiration estimation from MODIS data in arid and semi-arid regions: Implementation and validation","volume":"114","author":"Tang","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"D04106","DOI":"10.1029\/2010JD014543","article-title":"Validating MODIS\u2014Derived land surface evapotranspiration with in situ measurements at two AmeriFlux sites in a semiarid region","volume":"116","author":"Tang","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1080\/2150704X.2014.984083","article-title":"Latent heat flux estimation using trapezoidal relationship between MODIS land surface temperature and fraction of vegetation\u2013application and validation in a humid tropical region","volume":"5","author":"Laxmi","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez P\u00e9rez, J.\u00c1., Garc\u00eda-Galiano, S.G., Martin-Gorriz, B., and Baille, A. (2017). Satellite-Based Method for Estimating the Spatial Distribution of Crop Evapotranspiration: Sensitivity to the Priestley-Taylor Coefficient. Remote Sens., 9.","DOI":"10.3390\/rs9060611"},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0034-4257(00)00205-4","article-title":"Narrowband to broadband conversions of land surface albedo: I. Algorithms","volume":"76","author":"Liang","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2867","DOI":"10.1175\/JCLI3720.1","article-title":"An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations","volume":"19","author":"Jin","year":"2006","journal-title":"J. Clim."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Campbell, G.S., and Norman, J.M. (1998). An Introduction to Environmental Biophysics, Springer. [2nd ed.].","DOI":"10.1007\/978-1-4612-1626-1"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.rse.2005.03.014","article-title":"Estimation of net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days","volume":"97","author":"Bisht","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/0034-4257(96)00039-9","article-title":"Mapping land surface emissivity from NDVI: application to European, African and South American areas","volume":"57","author":"Valor","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/S0168-1923(99)00080-5","article-title":"Assessment of reliability of Bowen ratio method for partitioning fluxes","volume":"97","author":"Perez","year":"1999","journal-title":"Agric. For. Meteorol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/9\/949\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:44:48Z","timestamp":1760208288000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/9\/949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,13]]},"references-count":31,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["rs9090949"],"URL":"https:\/\/doi.org\/10.3390\/rs9090949","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,9,13]]}}}