Assessing the accuracy of multi-model approaches for downscaling land surface temperature across diverse agroclimatic zones

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cg.contributor.affiliationIndian Agricultural Research Institute
cg.contributor.affiliationCentral Coastal Agricultural Research Institute
cg.contributor.affiliationUniversity of California
cg.contributor.affiliationCentral Arid Zone Research Institute
cg.contributor.affiliationUttar Banga Krishi Viswavidyalaya
cg.contributor.affiliationSpace Applications Centre
cg.contributor.affiliationInternational Center for Agricultural Research in the Dry Areas
cg.contributor.affiliationMississippi State University
cg.contributor.affiliationIndia Meteorological Department
cg.contributor.affiliationKansas State University
cg.contributor.affiliationInternational Maize and Wheat Improvement Center
cg.contributor.donorIndian Council of Agricultural Research
cg.contributor.initiativeFragility to Resilience in Central and West Asia and North Africa
cg.creator.identifiervksehgal: 0000-0002-3473-9722
cg.creator.identifierSHESHAKUMAR GOROSHI: 0000-0003-3840-023X
cg.creator.identifierP.V. Vara Prasad: 0000-0001-6632-3361
cg.creator.identifierDebashis Chakraborty: 0000-0001-9664-8095
cg.howPublishedFormally Published
cg.identifier.doihttps://doi.org/10.1038/s41598-025-92135-0
cg.identifier.urlhttps://hdl.handle.net/10883/35623
cg.isijournalISI Journal
cg.issn2045-2322
cg.journalScientific Reports
cg.reviewStatusPeer Review
dc.contributor.authorRoy, Debasish
dc.contributor.authorDas, Bappa
dc.contributor.authorSingh, Pooja
dc.contributor.authorSantra, Priyabrata
dc.contributor.authorDeb, Shovik
dc.contributor.authorBhattacharya, Bimal Kumar
dc.contributor.authorGovind, Ajit
dc.contributor.authorJatav, Raghuveer
dc.contributor.authorSethi, Deepak
dc.contributor.authorGhosh, Tridiv
dc.contributor.authorMukherjee, Joydeep
dc.contributor.authorSehgal, Vinay Kumar
dc.contributor.authorPrakash Kumar Jha
dc.contributor.authorGoroshi, Sheshakumar
dc.contributor.authorPrasad, P. V. Vara
dc.contributor.authorChakraborty, Debashis
dc.date.accessioned2025-05-30T22:39:52Z
dc.date.available2025-05-30T22:39:52Z
dc.identifier.urihttps://hdl.handle.net/10568/174892
dc.titleAssessing the accuracy of multi-model approaches for downscaling land surface temperature across diverse agroclimatic zones
dcterms.abstractLand surface temperature (LST) is a critical parameter for land surface and atmospheric interactions. However, the applicability of current LST estimates for field-level hydrological, agricultural, and ecological operations is challenging due to their coarse spatiotemporal resolution. In the current article, we compared three different models, namely 1) Thermal Sharpening (TsHARP), 2) Thin Plate Spline (TPS), and 3) Random Forest (RF) for downscaling LST from 100 to 10 m by using high-resolution Sentinel-1,2 optical-microwave data. TsHARP, TPS, and RF are commonly used methods for improving the spatial resolution of large-scale environmental or climate data to finer scales for field-level applications. The analysis was performed at agricultural farms in the semi-arid, arid, and per-humid regions of India during the winter and summer seasons of 2020-21 and 2021-22. The calibration accuracy of the RF model was in better agreement with the coefficient of determination (R2), root mean square error (RMSE), and normalized RMSE (nRMSE) values ranging between 0.961-0.997, 0.103-0.439 K, and 0.034-0.143%, respectively, and lower values of standard errors for all three locations. Though the validation accuracy of models varied between the regions, RF and TPS consistently outperformed the TsHARP model. Further the impact of individual features on LST downscaling was analyzed using Accumulated Local Effects (ALE) plot. The study concluded that RF is an effective and adaptable strategy that can be used in various agroclimatic zones and land cover types, suggesting its broader applicability in agricultural and ecological operations. Finer resolution LST data with enhanced precision can support tailored field-level decision-making and interventions in agriculture and environmental monitoring.
dcterms.accessRightsOpen Access
dcterms.available2025-03-28
dcterms.bibliographicCitationRoy, D., Das, B., Singh, P., Santra, P., Deb, S., Bhattacharya, B. K., Govind, A., Jatav, R., Sethi, D., Ghosh, T., Mukherjee, J., Sehgal, V. K., Jha, P. K., Goroshi, S., Prasad, P. V. V., & Chakraborty, D. (2025). Assessing the accuracy of multi-model approaches for downscaling land surface temperature across diverse agroclimatic zones. Scientific Reports, 15(1), 10824. https://doi.org/10.1038/s41598-025-92135-0
dcterms.issued2025
dcterms.languageen
dcterms.licenseCC-BY-NC-ND-4.0
dcterms.publisherNature Publishing Group
dcterms.subjectforecasting
dcterms.subjectfarms
dcterms.subjectagroclimatic zones
dcterms.typeJournal Article

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