{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T20:37:05Z","timestamp":1776285425817,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,20]],"date-time":"2022-08-20T00:00:00Z","timestamp":1660953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005357","name":"Slovak Research and Development Agency (APVV)","doi-asserted-by":"publisher","award":["APVV-18-0044"],"award-info":[{"award-number":["APVV-18-0044"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005357","name":"Slovak Research and Development Agency (APVV)","doi-asserted-by":"publisher","award":["VEGA 1\/0798\/20"],"award-info":[{"award-number":["VEGA 1\/0798\/20"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005357","name":"Slovak Research and Development Agency (APVV)","doi-asserted-by":"publisher","award":["VVGS-PF-2021-1776"],"award-info":[{"award-number":["VVGS-PF-2021-1776"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic","award":["APVV-18-0044"],"award-info":[{"award-number":["APVV-18-0044"]}]},{"name":"Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic","award":["VEGA 1\/0798\/20"],"award-info":[{"award-number":["VEGA 1\/0798\/20"]}]},{"name":"Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic","award":["VVGS-PF-2021-1776"],"award-info":[{"award-number":["VVGS-PF-2021-1776"]}]},{"name":"Slovak Academy of Sciences (VEGA)","award":["APVV-18-0044"],"award-info":[{"award-number":["APVV-18-0044"]}]},{"name":"Slovak Academy of Sciences (VEGA)","award":["VEGA 1\/0798\/20"],"award-info":[{"award-number":["VEGA 1\/0798\/20"]}]},{"name":"Slovak Academy of Sciences (VEGA)","award":["VVGS-PF-2021-1776"],"award-info":[{"award-number":["VVGS-PF-2021-1776"]}]},{"name":"Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice","award":["APVV-18-0044"],"award-info":[{"award-number":["APVV-18-0044"]}]},{"name":"Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice","award":["VEGA 1\/0798\/20"],"award-info":[{"award-number":["VEGA 1\/0798\/20"]}]},{"name":"Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice","award":["VVGS-PF-2021-1776"],"award-info":[{"award-number":["VVGS-PF-2021-1776"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Thermal infrared (TIR) satellite imagery collected by multispectral scanners is important to map land surface temperature on a global scale. However, the TIR spectral bands are typically available in coarser spatial resolution than other multispectral bands of shorter wavelengths. Therefore, the spatial resolution of the derived land surface temperature (LST) is limited to around 100 m. This constrains the applications of such thermal satellite sensors in which finer detail of LST spatial pattern is relevant, especially in an urban environment where the land cover structure is complex. Among the missions deployed on the Earth\u2019s orbit, NASA\u2019s TIRS sensor onboard Landsat 8 and Landsat 9, and ASTER onboard Terra provide the highest spatial resolution of the thermal band. On the other hand, ESA\u2019s Sentinel-2 multispectral imagery is collected at a higher spatial resolution of 10 m with a 5-day temporal resolution, but scanning in the TIR band is not available. This study makes use of the known relationship between LST and land cover metrics, such as the normalized difference vegetation index (NDVI), built-up index (NDBI), and water index (NDWI). We define a multiple linear regression model based on the spectral indices and LST derived from Landsat 8 data to inform the same model in which the equivalent spectral indices derived from Sentinel-2 are used to predict LST at 10 m resolution. Results of this approach are demonstrated in a case study for Ko\u0161ice city, Slovakia, where the multiple linear model based on Landsat 8 data achieved an R2 of 0.642. The correlation between the observed Landsat 8 LST and predicted LST from Sentinel-2 aggregated to the same resolution as the observed LST was high (r = 0.91). Despite the imperfections of the downscaling model, the derived LST at 10 m resolution provides a better perception of the LST field that can be easily associated with land cover features present in urban environment. The LST downscaling approach was implemented into Google Earth Engine. It provides a user-friendly online application that can be used for any city or urban region for generating a more realistic spatial pattern of LST than can be directly observed by contemporary Earth observation satellites. The tool aids in urban decision making and planning on how to mitigate overheating of cities to improve the life quality of their citizens.<\/jats:p>","DOI":"10.3390\/rs14164076","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T01:56:40Z","timestamp":1661133400000},"page":"4076","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":74,"title":["Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8011-446X","authenticated-orcid":false,"given":"Katar\u00edna","family":"Ona\u010dillov\u00e1","sequence":"first","affiliation":[{"name":"Institute of Geography, Faculty of Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice, 041 54 Ko\u0161ice, Slovakia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0075-4991","authenticated-orcid":false,"given":"Michal","family":"Gallay","sequence":"additional","affiliation":[{"name":"Institute of Geography, Faculty of Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice, 041 54 Ko\u0161ice, Slovakia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9738-938X","authenticated-orcid":false,"given":"Daniel","family":"Paluba","sequence":"additional","affiliation":[{"name":"Department of Applied Geoinformatics and Cartography, Faculty of Science, Charles University, Albertov 6, 128 43 Prague, Czech Republic"}]},{"given":"Anna","family":"P\u00e9liov\u00e1","sequence":"additional","affiliation":[{"name":"Nexus Geographics\u2014Girona Office, Joaquim Botet Sis\u00f3 6, 17003 Girona, Spain"}]},{"given":"Ondrej","family":"Tokar\u010d\u00edk","sequence":"additional","affiliation":[{"name":"Institute of Geography, Faculty of Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice, 041 54 Ko\u0161ice, Slovakia"}]},{"given":"Daniela","family":"Laubertov\u00e1","sequence":"additional","affiliation":[{"name":"Institute of Geography, Faculty of Science, Pavol Jozef \u0160af\u00e1rik University in Ko\u0161ice, 041 54 Ko\u0161ice, Slovakia"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., and Sobrino, J.A. 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