{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T15:51:07Z","timestamp":1726501867117},"reference-count":78,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Environmental Modelling & Software"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1016\/j.envsoft.2022.105456","type":"journal-article","created":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T01:30:55Z","timestamp":1656639055000},"page":"105456","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":14,"special_numbering":"C","title":["Towards a combined Landsat-8 and Sentinel-2 for 10-m land surface temperature products: The Google Earth Engine monthly Ten-ST-GEE system"],"prefix":"10.1016","volume":"155","author":[{"given":"Yaser","family":"Abunnasr","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2741-8653","authenticated-orcid":false,"given":"Mario","family":"Mhawej","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.envsoft.2022.105456_bib1","doi-asserted-by":"crossref","DOI":"10.1016\/j.uclim.2020.100733","article-title":"Pervious area change as surrogate to diverse climatic variables trends in the CONUS: a county-scale assessment","volume":"35","author":"Abunnasr","year":"2021","journal-title":"Urban Clim."},{"key":"10.1016\/j.envsoft.2022.105456_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.uclim.2021.100998","article-title":"Downscaled night air temperatures between 2030 and 2070: the case of cities with a complex-and heterogeneous-topography","volume":"40","author":"Abunnasr","year":"2021","journal-title":"Urban Clim."},{"key":"10.1016\/j.envsoft.2022.105456_bib3","article-title":"Fully automated urban land surface temperature downscaling based on RGB high spatial resolution images","author":"Abunnasr","year":"2022","journal-title":"Adv. Space Res."},{"key":"10.1016\/j.envsoft.2022.105456_bib79","doi-asserted-by":"crossref","first-page":"101187","DOI":"10.1016\/j.uclim.2022.101187","article-title":"SEBU: a novel fully automated Google Earth Engine surface energy balance model for urban areas","volume":"44","author":"Abunnasr","year":"2022","journal-title":"Urban Climate"},{"key":"10.1016\/j.envsoft.2022.105456_bib4","series-title":"Optical Spectroscopic Techniques and Instrumentation for Atmospheric and Space Research III","first-page":"354","article-title":"MODTRAN4: multiple scattering and bidirectional reflectance distribution function (BRDF) upgrades to MODTRAN","author":"Acharya","year":"1999"},{"issue":"4","key":"10.1016\/j.envsoft.2022.105456_bib5","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":"10.1016\/j.envsoft.2022.105456_bib6","doi-asserted-by":"crossref","DOI":"10.1016\/j.agwat.2020.106432","article-title":"Monthly 10-m evapotranspiration rates retrieved by SEBALI with Sentinel-2 and MODIS LST data","volume":"243","author":"Allam","year":"2021","journal-title":"Agricultural Water Management"},{"key":"10.1016\/j.envsoft.2022.105456_bib7","doi-asserted-by":"crossref","first-page":"11","DOI":"10.3390\/rs11111319","article-title":"Downscaling land surface temperature from MODIS dataset with random forest approach over alpine vegetated areas","volume":"11","author":"Bartkowiak","year":"2019","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib8","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1016\/j.jqsrt.2017.03.004","article-title":"Validation of MODTRAN\u00ae 6 and its line-by-line algorithm","volume":"203","author":"Berk","year":"2017","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"issue":"3","key":"10.1016\/j.envsoft.2022.105456_bib9","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/S0034-4257(98)00045-5","article-title":"MODTRAN cloud and multiple scattering upgrades with application to AVIRIS","volume":"65","author":"Berk","year":"1998","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib10","series-title":"Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI","first-page":"190","article-title":"Reformulation of the MODTRAN band model for higher spectral resolution","author":"Berk","year":"2000"},{"key":"10.1016\/j.envsoft.2022.105456_bib11","series-title":"2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","first-page":"1","article-title":"MODTRAN\u00ae 6: a major upgrade of the MODTRAN\u00ae radiative transfer code","author":"Berk","year":"2014"},{"key":"10.1016\/j.envsoft.2022.105456_bib12","series-title":"Random Forests. Statistics Department","first-page":"4720","author":"Breiman","year":"2001"},{"key":"10.1016\/j.envsoft.2022.105456_bib13","series-title":"LIBSVM: a Library for Support Vector Machines","author":"Chang","year":"2001"},{"key":"10.1016\/j.envsoft.2022.105456_bib14","first-page":"525","article-title":"Comparison of different methods for spatial downscaling of GPM IMERG V06B satellite precipitation product over a typical arid to semi-arid area","author":"Chen","year":"2020","journal-title":"Front. Earth Sci."},{"key":"10.1016\/j.envsoft.2022.105456_bib15","series-title":"Harmonized Landsat-8 Sentinel-2 (HLS) Product User's Guide","author":"Claverie","year":"2017"},{"key":"10.1016\/j.envsoft.2022.105456_bib16","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2018.09.002","article-title":"The Harmonized Landsat and Sentinel-2 surface reflectance data set","volume":"219","author":"Claverie","year":"2018","journal-title":"Rem. Sens. Environ."},{"issue":"3","key":"10.1016\/j.envsoft.2022.105456_bib17","doi-asserted-by":"crossref","first-page":"431","DOI":"10.3390\/rs10030431","article-title":"An improved single-channel method to retrieve land surface temperature from the Landsat-8 thermal band","volume":"10","author":"Crist\u00f3bal","year":"2018","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib18","first-page":"1843","article-title":"Aspects of robust linear regression","author":"Davies","year":"1993","journal-title":"Ann. Stat."},{"issue":"7","key":"10.1016\/j.envsoft.2022.105456_bib19","doi-asserted-by":"crossref","first-page":"1772","DOI":"10.1016\/j.rse.2011.03.008","article-title":"High-resolution urban thermal sharpener (HUTS)","volume":"115","author":"Dominguez","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib20","first-page":"63","article-title":"Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data","volume":"49","author":"Dong","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.envsoft.2022.105456_bib21","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/0034-4257(81)90021-3","article-title":"A method for satellite identification of surface temperature fields of subpixel resolution","volume":"11","author":"Dozier","year":"1981","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib23","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.cageo.2019.01.004","article-title":"Downscaling MODIS land surface temperature over a heterogeneous area: an investigation of machine learning techniques, feature selection, and impacts of mixed pixels","volume":"124","author":"Ebrahimy","year":"2019","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.envsoft.2022.105456_bib24","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.rse.2016.12.008","article-title":"Darren Ghent, and John Remedios. \"Modelling directional effects on remotely sensed land surface temperature","volume":"190","author":"Ermida","year":"2017","journal-title":"Remote Sens. Environ."},{"issue":"12","key":"10.1016\/j.envsoft.2022.105456_bib25","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.3390\/rs9121243","article-title":"Improved DisTrad for downscaling thermal MODIS imagery over urban areas","volume":"9","author":"Essa","year":"2017","journal-title":"Rem. Sens."},{"issue":"5","key":"10.1016\/j.envsoft.2022.105456_bib26","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. Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib80","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.apgeog.2018.05.020","article-title":"Global trends analysis of the main vegetation types throughout the past four decades","volume":"97","author":"Faour","year":"2018","journal-title":"Appl. Geogr."},{"key":"10.1016\/j.envsoft.2022.105456_bib27","doi-asserted-by":"crossref","DOI":"10.4000\/cybergeo.27620","article-title":"Detecting changes in vegetation trends in the Middle East and North Africa (MENA) region using SPOT vegetation","author":"Faour","year":"2016","journal-title":"Cybergeo"},{"key":"10.1016\/j.envsoft.2022.105456_bib28","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.eja.2019.03.001","article-title":"New approach to determining the surface temperature without thermal band of satellites","volume":"106","author":"Filgueiras","year":"2019","journal-title":"Eur. J. Agron."},{"issue":"11","key":"10.1016\/j.envsoft.2022.105456_bib29","doi-asserted-by":"crossref","first-page":"3287","DOI":"10.3390\/rs4113287","article-title":"A data mining approach for sharpening thermal satellite imagery over land","volume":"4","author":"Gao","year":"2012","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib30","first-page":"137","article-title":"Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems","volume":"80","author":"Garc\u00eda-Llamas","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"3","key":"10.1016\/j.envsoft.2022.105456_bib31","doi-asserted-by":"crossref","first-page":"563","DOI":"10.3390\/cli3030563","article-title":"Regional landsat-based drought monitoring from 1982 to 2014","volume":"3","author":"Ghaleb","year":"2015","journal-title":"Climate"},{"issue":"2\u20133","key":"10.1016\/j.envsoft.2022.105456_bib32","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0034-4257(03)00184-6","article-title":"An enhanced contextual fire detection algorithm for MODIS","volume":"87","author":"Giglio","year":"2003","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib33","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth engine: planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Rem. Sens. Environ."},{"issue":"5","key":"10.1016\/j.envsoft.2022.105456_bib34","doi-asserted-by":"crossref","first-page":"410","DOI":"10.3390\/rs8050410","article-title":"Long term validation of land surface temperature retrieved from MSG\/SEVIRI with continuous in-situ measurements in Africa","volume":"8","author":"G\u00f6ttsche","year":"2016","journal-title":"Rem. Sens."},{"issue":"6","key":"10.1016\/j.envsoft.2022.105456_bib35","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1109\/LGRS.2013.2260319","article-title":"Directional viewing effects on satellite land surface temperature products over sparse vegetation canopies\u2014a multisensor analysis","volume":"10","author":"Guillevic","year":"2013","journal-title":"Geosci. Rem. Sens. Lett. IEEE"},{"key":"10.1016\/j.envsoft.2022.105456_bib36","first-page":"60","article-title":"Land surface temperature product validation best practice protocol. Version 1.1","author":"Guillevic","year":"2018","journal-title":"Best Pract. Satell. Deriv. Land Prod. Validation"},{"key":"10.1016\/j.envsoft.2022.105456_bib37","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.rse.2018.11.019","article-title":"Evaluating the feasibility of using Sentinel-2 and Sentinel-3 satellites for high-resolution evapotranspiration estimations","volume":"221","author":"Guzinski","year":"2019","journal-title":"Rem. Sens. Environ."},{"issue":"5","key":"10.1016\/j.envsoft.2022.105456_bib38","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1007\/s41742-021-00356-8","article-title":"Evaluation of the climate change impact on urban heat island based on land surface temperature and geospatial indicators","volume":"15","author":"Halder","year":"2021","journal-title":"Int. J. Environ. Res."},{"key":"10.1016\/j.envsoft.2022.105456_bib39","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2019.111419","article-title":"Monitoring agricultural drought in Australia using MTSAT-2 land surface temperature retrievals","volume":"236","author":"Hu","year":"2020","journal-title":"Remote Sens. Environ."},{"issue":"19","key":"10.1016\/j.envsoft.2022.105456_bib40","doi-asserted-by":"crossref","first-page":"2304","DOI":"10.3390\/rs11192304","article-title":"Evaluation of TsHARP utility for thermal sharpening of Sentinel-3 satellite images using Sentinel-2 visual imagery","volume":"11","author":"Huryna","year":"2019","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib41","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.rse.2016.03.006","article-title":"Downscaling land surface temperatures at regional scales with random forest regression","volume":"178","author":"Hutengs","year":"2016","journal-title":"Remote Sens. Environ."},{"issue":"4","key":"10.1016\/j.envsoft.2022.105456_bib42","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\u2013radiometric temperature relationship","volume":"85","author":"Kustas","year":"2003","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib43","doi-asserted-by":"crossref","first-page":"18149","DOI":"10.1109\/ACCESS.2018.2818741","article-title":"Land surface temperature retrieval from Landsat-8 data with the generalized split-window algorithm","volume":"6","author":"Li","year":"2018","journal-title":"IEEE Access"},{"issue":"7","key":"10.1016\/j.envsoft.2022.105456_bib44","doi-asserted-by":"crossref","first-page":"2299","DOI":"10.1109\/JSTARS.2019.2896923","article-title":"Evaluation of machine learning algorithms in spatial downscaling of MODIS land surface temperature","volume":"12","author":"Li","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib45","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1016\/j.scitotenv.2018.09.308","article-title":"Using spatio-temporal fusion of Landsat-8 and MODIS data to derive phenology, biomass and yield estimates for corn and soybean","volume":"650","author":"Liao","year":"2019","journal-title":"Sci. Total Environ."},{"issue":"4","key":"10.1016\/j.envsoft.2022.105456_bib46","doi-asserted-by":"crossref","first-page":"2695","DOI":"10.3390\/s8042695","article-title":"Downscaling thermal infrared radiance for subpixel land surface temperature retrieval","volume":"8","author":"Liu","year":"2008","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.envsoft.2022.105456_bib47","doi-asserted-by":"crossref","first-page":"17","DOI":"10.5721\/EuJRS20154802","article-title":"Sensitivity analysis of a bio-optical model for Italian lakes focused on Landsat-8, Sentinel-2 and Sentinel-3","volume":"48","author":"Manzo","year":"2015","journal-title":"Eur. J. Remote Sens."},{"issue":"2","key":"10.1016\/j.envsoft.2022.105456_bib48","doi-asserted-by":"crossref","first-page":"155","DOI":"10.3390\/rs11020155","article-title":"Estimating land surface temperature from Landsat-8 data using the NOAA JPSS enterprise algorithm","volume":"11","author":"Meng","year":"2019","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib49","article-title":"Towards a daily 10-m land surface temperature product: the Google Earth engine daily Ten-ST-GEE system","author":"Mhawej","year":"2022","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.envsoft.2022.105456_bib50","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.ecoinf.2016.02.003","article-title":"Towards an establishment of a wildfire risk system in a Mediterranean country","volume":"32","author":"Mhawej","year":"2016","journal-title":"Ecol. Inf."},{"issue":"14","key":"10.1016\/j.envsoft.2022.105456_bib51","doi-asserted-by":"crossref","first-page":"5321","DOI":"10.1080\/01431161.2020.1739354","article-title":"Evaporation rates in a vital lake: a 34-year assessment for the Karaoun Lake","volume":"41","author":"Mhawej","year":"2020","journal-title":"Int. J. Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib52","doi-asserted-by":"crossref","DOI":"10.1016\/j.agwat.2019.105938","article-title":"Automated evapotranspiration retrieval model with missing soil-related datasets: the proposal of SEBALI","volume":"229","author":"Mhawej","year":"2020","journal-title":"Agric. Water Manag."},{"key":"10.1016\/j.envsoft.2022.105456_bib53","doi-asserted-by":"crossref","DOI":"10.1016\/j.agwat.2019.105955","article-title":"Dynamic calibration for better SEBALI ET estimations: validations and recommendations","volume":"230","author":"Mhawej","year":"2020","journal-title":"Agric. Water Manag."},{"issue":"4","key":"10.1016\/j.envsoft.2022.105456_bib54","doi-asserted-by":"crossref","first-page":"364","DOI":"10.3390\/rs9040364","article-title":"Comprehensive annual ice sheet velocity mapping using Landsat-8, Sentinel-1, and RADARSAT-2 data","volume":"9","author":"Mouginot","year":"2017","journal-title":"Rem. Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2022.105456_bib55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-27905-0","article-title":"Applicability of downscaling land surface temperature by using normalized difference sand index","volume":"8","author":"Pan","year":"2018","journal-title":"Sci. Rep."},{"key":"10.1016\/j.envsoft.2022.105456_bib56","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.rse.2018.06.010","article-title":"Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas","volume":"215","author":"Peng","year":"2018","journal-title":"Rem. Sens. Environ."},{"issue":"3","key":"10.1016\/j.envsoft.2022.105456_bib57","doi-asserted-by":"crossref","DOI":"10.1109\/36.763272","article-title":"Combining multispectral data of differing spatial resolution","volume":"37","author":"Price","year":"1999","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"issue":"24","key":"10.1016\/j.envsoft.2022.105456_bib58","doi-asserted-by":"crossref","first-page":"5044","DOI":"10.3390\/rs13245044","article-title":"Reducing scaling effect on downscaled land surface temperature maps in heterogenous urban environments","volume":"13","author":"Pu","year":"2021","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib59","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2016.12.009","article-title":"Burn severity mapping from landsat MESMA fraction images and land surface temperature","volume":"190","author":"Quintano","year":"2017","journal-title":"Remote Sens. Environ."},{"issue":"10","key":"10.1016\/j.envsoft.2022.105456_bib60","doi-asserted-by":"crossref","first-page":"988","DOI":"10.3390\/rs9100988","article-title":"Sensitivity of Landsat 8 surface temperature estimates to atmospheric profile data: a study using MODTRAN in dryland irrigated systems","volume":"9","author":"Rosas","year":"2017","journal-title":"Rem. Sens."},{"issue":"4","key":"10.1016\/j.envsoft.2022.105456_bib61","doi-asserted-by":"crossref","first-page":"5768","DOI":"10.3390\/s140405768","article-title":"Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm","volume":"14","author":"Rozenstein","year":"2014","journal-title":"Sensors"},{"issue":"2","key":"10.1016\/j.envsoft.2022.105456_bib62","doi-asserted-by":"crossref","first-page":"134","DOI":"10.3390\/rs11020134","article-title":"Analysis of thermal anomalies in volcanic areas using multiscale and multitemporal monitoring: vulcano island test case","volume":"11","author":"Silvestri","year":"2019","journal-title":"Rem. Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2022.105456_bib63","doi-asserted-by":"crossref","first-page":"184","DOI":"10.3390\/rs12010184","article-title":"First comparisons of surface temperature estimations between ECOSTRESS, ASTER and Landsat 8 over Italian volcanic and geothermal areas","volume":"12","author":"Silvestri","year":"2020","journal-title":"Rem. Sens."},{"issue":"12","key":"10.1016\/j.envsoft.2022.105456_bib64","doi-asserted-by":"crossref","first-page":"2592","DOI":"10.1016\/j.rse.2009.07.017","article-title":"Downscaling AVHRR land surface temperatures for improved surface urban heat island intensity estimation","volume":"113","author":"Stathopoulou","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib65","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.rse.2016.08.025","article-title":"A note on the temporary misregistration of landsat-8 operational land imager (OLI) and sentinel-2 multi spectral instrument (MSI) imagery","volume":"186","author":"Storey","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.envsoft.2022.105456_bib66","first-page":"1","article-title":"Relationship between evapotranspiration and land surface temperature under energy-and water-limited conditions in dry and cold climates","volume":"2016","author":"Sun","year":"2016","journal-title":"Adv. Meteorol."},{"key":"10.1016\/j.envsoft.2022.105456_bib67","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2017.01.001","article-title":"Characterizing the relationship between land use land cover change and land surface temperature","volume":"124","author":"Tran","year":"2017","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib68","series-title":"The Nature of Statistical Learning Theory","author":"Vapnik Vladimir","year":"1995"},{"issue":"9","key":"10.1016\/j.envsoft.2022.105456_bib69","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1111\/j.1749-8198.2010.00384.x","article-title":"Cities as net sources of CO2: review of atmospheric CO2 exchange in urban environments measured by eddy covariance technique","volume":"4","author":"Velasco","year":"2010","journal-title":"Geogr. Compass"},{"key":"10.1016\/j.envsoft.2022.105456_bib70","doi-asserted-by":"crossref","DOI":"10.1016\/j.landurbplan.2019.103668","article-title":"Impacts of spatial clustering of urban land cover on land surface temperature across K\u00f6ppen climate zones in the contiguous United States","volume":"192","author":"Wang","year":"2019","journal-title":"Landsc. Urban Plann."},{"key":"10.1016\/j.envsoft.2022.105456_bib71","doi-asserted-by":"crossref","first-page":"21904","DOI":"10.1109\/ACCESS.2019.2896241","article-title":"Downscaling land surface temperatures using a random forest regression model with multitype predictor variables","volume":"7","author":"Wu","year":"2019","journal-title":"IEEE Access"},{"issue":"10","key":"10.1016\/j.envsoft.2022.105456_bib72","doi-asserted-by":"crossref","first-page":"9829","DOI":"10.3390\/rs6109829","article-title":"Land surface temperature retrieval from Landsat 8 TIRS\u2014comparison between radiative transfer equation-based method, split window algorithm and single channel method","volume":"6","author":"Yu","year":"2014","journal-title":"Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib73","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.rse.2011.05.027","article-title":"Downscaling land surface temperature for urban heat island diurnal cycle analysis","volume":"117","author":"Zak\u0161ek","year":"2012","journal-title":"Remote Sens. Environ."},{"issue":"8","key":"10.1016\/j.envsoft.2022.105456_bib74","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1080\/17538947.2019.1593527","article-title":"Downscaling Landsat-8 land surface temperature maps in diverse urban landscapes using multivariate adaptive regression splines and very high resolution auxiliary data","volume":"13","author":"Zawadzka","year":"2020","journal-title":"Int. J. Digit. Earth"},{"key":"10.1016\/j.envsoft.2022.105456_bib75","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.rse.2012.12.014","article-title":"Disaggregation of remotely sensed land surface temperature: literature survey, taxonomy, issues, and caveats","volume":"131","author":"Zhan","year":"2013","journal-title":"Remote Sens. Environ."},{"issue":"5\u20136","key":"10.1016\/j.envsoft.2022.105456_bib76","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1080\/01431161.2018.1489164","article-title":"Spatial downscaling of land surface temperature in combination with TVDI and elevation","volume":"40","author":"Zhang","year":"2019","journal-title":"Int. J. Rem. Sens."},{"key":"10.1016\/j.envsoft.2022.105456_bib77","first-page":"1","article-title":"Mapping paddy rice planting area in rice-wetland coexistent areas through analysis of Landsat 8 OLI and MODIS images","volume":"46","author":"Zhou","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."}],"container-title":["Environmental Modelling & Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815222001621?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815222001621?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T07:45:35Z","timestamp":1680162335000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1364815222001621"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":78,"alternative-id":["S1364815222001621"],"URL":"https:\/\/doi.org\/10.1016\/j.envsoft.2022.105456","relation":{},"ISSN":["1364-8152"],"issn-type":[{"value":"1364-8152","type":"print"}],"subject":[],"published":{"date-parts":[[2022,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Towards a combined Landsat-8 and Sentinel-2 for 10-m land surface temperature products: The Google Earth Engine monthly Ten-ST-GEE system","name":"articletitle","label":"Article Title"},{"value":"Environmental Modelling & Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envsoft.2022.105456","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"105456"}}