{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:06:18Z","timestamp":1781193978775,"version":"3.54.1"},"reference-count":58,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2012,10,19]],"date-time":"2012-10-19T00:00:00Z","timestamp":1350604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring of (surface) urban heat islands (UHI) is possible through satellite remote sensing of the land surface temperature (LST). Previous UHI studies are based on medium and high spatial resolution images, which are in the best-case scenario available about four times per day. This is not adequate for monitoring diurnal UHI development. High temporal resolution LST data (a few measurements per hour) over a whole city can be acquired by instruments onboard geostationary satellites. In northern Germany, geostationary LST data are available in pixels sized 3,300 by 6,700 m. For UHI monitoring, this resolution is too coarse, it should be comparable instead to the width of a building block: usually not more than 100 m. Thus, an LST downscaling is proposed that enhances the spatial resolution by a factor of about 2,000, which is much higher than in any previous study. The case study presented here (Hamburg, Germany) yields promising results. The latter, available every 15 min in 100 m spatial resolution, showed a high explained variance (R2: 0.71) and a relatively low root mean square error (RMSE: 2.2 K). For lower resolutions the downscaling scheme performs even better (R2: 0.80, RMSE: 1.8 K for 500 m; R2: 0.82, RMSE: 1.6 K for 1,000 m).<\/jats:p>","DOI":"10.3390\/rs4103184","type":"journal-article","created":{"date-parts":[[2012,10,22]],"date-time":"2012-10-22T05:32:03Z","timestamp":1350883923000},"page":"3184-3200","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":147,"title":["Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany"],"prefix":"10.3390","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8802-7934","authenticated-orcid":false,"given":"Benjamin","family":"Bechtel","sequence":"first","affiliation":[{"name":"KlimaCampus Hamburg, University of Hamburg, Bundesstra\u00dfe 55, D-20146 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Klemen","family":"Zak\u0161ek","sequence":"additional","affiliation":[{"name":"Institute of Geophysics, University of Hamburg, Bundesstra\u00dfe 55, D-20146 Hamburg, Germany"},{"name":"Centre of excellence Space-Si, A\u0161ker\u010deva 12, SI-1000 Ljubljana, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gholamali","family":"Hoshyaripour","sequence":"additional","affiliation":[{"name":"Institute of Geophysics, University of Hamburg, Bundesstra\u00dfe 55, D-20146 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2012,10,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"83","DOI":"10.3390\/rs3010083","article-title":"Satellite-observed urbanization characters in Shanghai, China: Aerosols, urban heat island effect, and land-atmosphere interactions","volume":"3","author":"Jin","year":"2011","journal-title":"Remote Sens"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2033","DOI":"10.3390\/rs4072033","article-title":"The impacts of rapid urbanization on the thermal environment: A remote sensing study of Guangzhou, South China","volume":"4","author":"Xiong","year":"2012","journal-title":"Remote Sens"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2635","DOI":"10.3390\/rs4092635","article-title":"Flux measurements in Cairo. 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