{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T05:40:13Z","timestamp":1782366013723,"version":"3.54.5"},"reference-count":73,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T00:00:00Z","timestamp":1588723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["PTDC\/CTA-MET\/28946\/2017"],"award-info":[{"award-number":["PTDC\/CTA-MET\/28946\/2017"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land Surface Temperature (LST) is increasingly important for various studies assessing land surface conditions, e.g., studies of urban climate, evapotranspiration, and vegetation stress. The Landsat series of satellites have the potential to provide LST estimates at a high spatial resolution, which is particularly appropriate for local or small-scale studies. Numerous studies have proposed LST retrieval algorithms for the Landsat series, and some datasets are available online. However, those datasets generally require the users to be able to handle large volumes of data. Google Earth Engine (GEE) is an online platform created to allow remote sensing users to easily perform big data analyses without increasing the demand for local computing resources. However, high spatial resolution LST datasets are currently not available in GEE. Here we provide a code repository that allows computing LSTs from Landsat 4, 5, 7, and 8 within GEE. The code may be used freely by users for computing Landsat LST as part of any analysis within GEE.<\/jats:p>","DOI":"10.3390\/rs12091471","type":"journal-article","created":{"date-parts":[[2020,5,7]],"date-time":"2020-05-07T03:10:38Z","timestamp":1588821038000},"page":"1471","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":625,"title":["Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0737-0824","authenticated-orcid":false,"given":"Sofia L.","family":"Ermida","sequence":"first","affiliation":[{"name":"Instituto Portugu\u00eas do Mar e da Atmosfera (IPMA), 1749-077 Lisbon, Portugal"},{"name":"Instituto Dom Luiz (IDL), Faculdade de Ci\u00eancias, Universidade de Lisboa, 1749-016 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patr\u00edcia","family":"Soares","sequence":"additional","affiliation":[{"name":"Department of Earth Sciences, Universidade de Coimbra, 3030-790 Coimbra, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasco","family":"Mantas","sequence":"additional","affiliation":[{"name":"Department of Earth Sciences, Universidade de Coimbra, 3030-790 Coimbra, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5836-5430","authenticated-orcid":false,"given":"Frank-M.","family":"G\u00f6ttsche","sequence":"additional","affiliation":[{"name":"Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology (KIT), 76021 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8640-9170","authenticated-orcid":false,"given":"Isabel F.","family":"Trigo","sequence":"additional","affiliation":[{"name":"Instituto Portugu\u00eas do Mar e da Atmosfera (IPMA), 1749-077 Lisbon, Portugal"},{"name":"Instituto Dom Luiz (IDL), Faculdade de Ci\u00eancias, Universidade de Lisboa, 1749-016 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.isprsjprs.2019.06.011","article-title":"Calculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2","volume":"154","author":"Mokhtari","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","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":"Remote Sens. Environ."},{"key":"ref_3","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. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.isprsjprs.2017.09.008","article-title":"Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987\u20132015)","volume":"133","author":"Estoque","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.rse.2015.12.040","article-title":"A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery","volume":"175","author":"Fu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.isprsjprs.2013.12.010","article-title":"Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation","volume":"89","author":"Maimaitiyiming","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6136","DOI":"10.3390\/rs6076136","article-title":"Analysis of the Relationship between Land Surface Temperature and Wildfire Severity in a Series of Landsat Images","volume":"6","author":"Vlassova","year":"2014","journal-title":"Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.apgeog.2013.07.004","article-title":"The impact of tree cover loss on land surface temperature: A case study of central Massachusetts using Landsat Thematic Mapper thermal data","volume":"45","author":"Rogan","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1080\/01431161.2012.712227","article-title":"Assessment of land surface temperature in relation to landscape metrics and fractional vegetation cover in an urban\/peri-urban region using Landsat data","volume":"34","author":"Zhang","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","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_11","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_12","doi-asserted-by":"crossref","first-page":"2606","DOI":"10.1016\/j.rse.2009.07.021","article-title":"Spatial\u2013temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use\/cover in the Tabriz urban area, Iran","volume":"113","author":"Amiri","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.jenvman.2006.07.016","article-title":"The impact of land use and land cover changes on land surface temperature in a karst area of China","volume":"85","author":"Xiao","year":"2007","journal-title":"J. Environ. Manage."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/S1001-0742(07)60041-2","article-title":"Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China","volume":"19","author":"XIAO","year":"2007","journal-title":"J. Environ. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.rse.2005.09.023","article-title":"An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data","volume":"104","author":"Xian","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4345","DOI":"10.3390\/rs6054345","article-title":"Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling","volume":"6","author":"Vlassova","year":"2014","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4268","DOI":"10.3390\/rs70404268","article-title":"An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data","volume":"7","author":"Wang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_18","first-page":"D08103","article-title":"Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapor and air temperature","volume":"114","author":"Sobrino","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1080\/01431160010006971","article-title":"A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region","volume":"22","author":"Qin","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7369","DOI":"10.1080\/01431161.2013.820368","article-title":"Generation of Landsat surface temperature product for China, 2000\u20132010","volume":"34","author":"Zhang","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.rse.2004.02.018","article-title":"Deriving land surface temperature from Landsat 5 and 7 during SMEX02\/SMACEX","volume":"92","author":"Li","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2004.02.003","article-title":"Land surface temperature retrieval from LANDSAT TM 5","volume":"90","author":"Sobrino","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Crist\u00f3bal, J., Jim\u00e9nez-Mu\u00f1oz, J., Prakash, A., Mattar, C., Skokovi\u0107, D., and Sobrino, J. (2018). An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band. Remote Sens., 10.","DOI":"10.3390\/rs10030431"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2582","DOI":"10.1080\/01431161.2011.617396","article-title":"Intercomparison of methods for estimating land surface temperature from a Landsat-5 TM image in an arid region with low water vapour in the atmosphere","volume":"33","author":"Zhou","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5717","DOI":"10.1109\/TGRS.2018.2824828","article-title":"An Operational Land Surface Temperature Product for Landsat Thermal Data: Methodology and Validation","volume":"56","author":"Malakar","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Parastatidis, D., Mitraka, Z., Chrysoulakis, N., and Abrams, M. (2017). Online Global Land Surface Temperature Estimation from Landsat. Remote Sens., 9.","DOI":"10.3390\/rs9121208"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1109\/TGRS.2008.2007125","article-title":"Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data","volume":"47","author":"Cristobal","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Meng, X., Cheng, J., Zhao, S., Liu, S., and Yao, Y. (2019). Estimating Land Surface Temperature from Landsat-8 Data using the NOAA JPSS Enterprise Algorithm. Remote Sens., 11.","DOI":"10.3390\/rs11020155"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.1080\/01431161.2018.1460513","article-title":"Land-surface temperature retrieval from Landsat 8 single-channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product","volume":"40","author":"Duan","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","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"},{"key":"ref_31","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":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zheng, S., Cao, C., Wang, M., Xu, M., and Lu, S. (2013, January 21\u201326). Land surface temperature retrieval using HJ-1B\/IRS data and analysis of its effect. Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, Melbourne, Australia.","DOI":"10.1109\/IGARSS.2013.6723274"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Sun, L., Yu, H., Gao, T., Tian, X., Li, X., and Sun, L. (2013, January 12\u201316). Land surface temperature retrieval from HJ-1B IRS supported by MODIS. Proceedings of the 2013 Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Fairfax, VA, USA.","DOI":"10.1109\/Argo-Geoinformatics.2013.6621929"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hulley, G., Shivers, S., Wetherley, E., and Cudd, R. (2019). New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California. Remote Sens., 11.","DOI":"10.3390\/rs11182136"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"13139","DOI":"10.3390\/rs71013139","article-title":"Meteosat land surface temperature climate data record: Achievable accuracy and potential uncertainties","volume":"7","author":"Bento","year":"2015","journal-title":"Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1175\/1520-0477(1996)077<0437:TNYRP>2.0.CO;2","article-title":"The NCEP\/NCAR 40-Year Reanalysis Project","volume":"77","author":"Kalnay","year":"1996","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Hulley, G.C., Hook, S.J., Abbott, E., Malakar, N., Islam, T., and Abrams, M. (2015). The ASTER Global Emissivity Dataset (ASTER GED): Mapping Earth\u2019s emissivity at 100 m spatial scale. Geophys. Res. Lett., 42.","DOI":"10.1002\/2015GL065564"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1175\/JTECH1806.1","article-title":"An Update on SURFRAD\u2014The GCOS Surface Radiation Budget Network for the Continental United States","volume":"22","author":"Augustine","year":"2005","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.5194\/essd-10-1491-2018","article-title":"Baseline Surface Radiation Network (BSRN): structure and data description (1992\u20132017)","volume":"10","author":"Driemel","year":"2018","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"G\u00f6ttsche, F.-M., Olesen, F.-S., Trigo, I.F., Bork-Unkelbach, A., and Martin, M.A. (2016). Long term validation of land surface temperature retrieved from MSG\/SEVIRI with continuous in-situ measurements in Africa. Remote Sens., 8.","DOI":"10.3390\/rs8050410"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1016\/j.rse.2009.01.007","article-title":"Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors","volume":"113","author":"Chander","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_42","unstructured":"USGS (2019). Landsat Collection 1 Level 1 Product Definition, USGS. LSDS-1656 version 2.0."},{"key":"ref_43","unstructured":"USGS (2019). Landsat 7 (L7) Data Users Handbook, USGS. LSDS-1927 version 2.0."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2016.04.008","article-title":"Preliminary analysis of the performance of the Landsat 8\/OLI land surface reflectance product","volume":"185","author":"Vermote","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2224","DOI":"10.1016\/j.rse.2009.06.005","article-title":"Validation of the North American ASTER Land Surface Emissivity Database (NAALSED) version 2.0 using pseudo-invariant sand dune sites","volume":"113","author":"Hulley","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the relation between NDVI, fractional vegetation cover, and leaf area index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"6764","DOI":"10.1002\/2017JD026910","article-title":"Mapping finer-resolution land surface emissivity using Landsat images in China","volume":"122","author":"Ren","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/S0034-4257(96)00216-7","article-title":"Estimation of air temperature from remotely sensed surface observations","volume":"60","author":"Prihodko","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_49","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_50","doi-asserted-by":"crossref","first-page":"768","DOI":"10.3390\/s90200768","article-title":"Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA\/CHRIS Data Over an Agricultural Area","volume":"9","author":"Sobrino","year":"2009","journal-title":"Sensors"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/S0034-4257(96)00123-X","article-title":"Emissivity measurements of several soils and vegetation types in the 8\u201314, \u03bcm Wave band: Analysis of two field methods","volume":"59","author":"Rubio","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"11145","DOI":"10.1029\/97JD00344","article-title":"Thermal band selection for the PRISM instrument: 1. Analysis of emissivity-temperature separation algorithms","volume":"102","author":"Caselles","year":"1997","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1834","DOI":"10.1109\/TGRS.2005.851172","article-title":"Emissivity maps to retrieve land-surface temperature from MSG\/SEVIRI","volume":"43","author":"Peres","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1175\/1520-0450(2004)043<0363:LSTEFT>2.0.CO;2","article-title":"Land Surface Temperature Estimation from the Next Generation of Geostationary Operational Environmental Satellites: GOES M\u2013Q","volume":"43","author":"Sun","year":"2004","journal-title":"J. Appl. Meteorol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"3051","DOI":"10.1080\/01431161.2012.716925","article-title":"Land surface temperature from multiple geostationary satellites","volume":"1161","author":"Freitas","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2012.12.008","article-title":"a Satellite-derived land surface temperature: Current status and perspectives","volume":"131","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Martins, J., Trigo, I., Bento, V., and da Camara, C. (2016). A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms. Remote Sens., 8.","DOI":"10.20944\/preprints201608.0073.v2"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2717","DOI":"10.5194\/gmd-11-2717-2018","article-title":"An update on the RTTOV fast radiative transfer model (currently at version 12)","volume":"11","author":"Saunders","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.rse.2014.08.013","article-title":"Validation of Land Surface Temperature products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) using ground-based and heritage satellite measurements","volume":"154","author":"Guillevic","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1080\/01431161.2013.873149","article-title":"Evaluation of 10 year AQUA\/MODIS land surface temperature with SURFRAD observations","volume":"35","author":"Li","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"12215","DOI":"10.3390\/rs70912215","article-title":"Quality Assessment of S-NPP VIIRS Land Surface Temperature Product","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Martin, M., Ghent, D., Pires, A., G\u00f6ttsche, F.-M., Cermak, J., and Remedios, J. (2019). Comprehensive In Situ Validation of Five Satellite Land Surface Temperature Data Sets over Multiple Stations and Years. Remote Sens., 11.","DOI":"10.3390\/rs11050479"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2013.2260319","article-title":"Directional Viewing Effects on Satellite Land Surface Temperature Products Over Sparse Vegetation Canopies \u2014 A Multisensor Analysis","volume":"10","author":"Guillevic","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.rse.2014.03.016","article-title":"Validation of remotely sensed surface temperature over an oak woodland landscape \u2014 The problem of viewing and illumination geometries","volume":"148","author":"Ermida","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.rse.2012.05.010","article-title":"Validation of six satellite-retrieved land surface emissivity products over two land cover types in a hyper-arid region","volume":"124","author":"Hulley","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_66","unstructured":"Guillevic, P., G\u00f6ttsche, F., Nickeson, J., and Rom\u00e1n, M. (2020, April 01). Land Surface Temperature Product Validation Best Practice Protocol, Best Practice for Satellite-Derived Land Product Validation, Available online: https:\/\/lpvs.gsfc.nasa.gov\/PDF\/CEOS_LST_PROTOCOL_Feb2018_v1.1.0_light.pdf."},{"key":"ref_67","first-page":"33","article-title":"Introducing new Crops and Crop Rotations in the Lower Monde Valley Irrigation Project, Portugal","volume":"89","author":"Speetzen","year":"1988","journal-title":"Der Tropenlandwirt-Journal Agric. Trop. Subtrop."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1080\/01621459.1993.10476339","article-title":"The Identification of Multiple Outliers","volume":"88","author":"Davies","year":"1993","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.rse.2019.02.020","article-title":"Validation of Collection 6 MODIS land surface temperature product using in situ measurements","volume":"225","author":"Duan","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"11607","DOI":"10.3390\/rs61111607","article-title":"Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration","volume":"6","author":"Barsi","year":"2014","journal-title":"Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Liu, Y., Yu, Y., Yu, P., and Wang, H. (2016, January 10\u201315). Ground validation and uncertainty esitmation of VIIRS land surface temperature product. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7730806"},{"key":"ref_72","unstructured":"Martins, J.P., Trigo, I.F., and Freitas, S.C. (2019). Copernicus Global Land Operations\u2014Scientific Quality Evaluation of Land Surface Temperature, version 1.2, issue 1.00 (CGLOPS1_SQE2018_LST), Copernicus European Union."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1109\/TGRS.2011.2162338","article-title":"Validation of GOES-R Satellite Land Surface Temperature Algorithm Using SURFRAD Ground Measurements and Statistical Estimates of Error Properties","volume":"50","author":"Yu","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/9\/1471\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:26:03Z","timestamp":1760174763000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/9\/1471"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,6]]},"references-count":73,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["rs12091471"],"URL":"https:\/\/doi.org\/10.3390\/rs12091471","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,6]]}}}