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<dc:title xml:lang="en"><![CDATA[Surface temperature extremes in urban areas: distribution, morphological drivers and air temperature patterns]]></dc:title>
<dc:title xml:lang="en"><![CDATA[Geographia Polonica Vol. 98 No. 2 (2025)]]></dc:title>
<dc:title xml:lang="pl"><![CDATA[Surface temperature extremes in urban areas: distribution, morphological drivers and air temperature patterns]]></dc:title>
<dc:title xml:lang="pl"><![CDATA[Geographia Polonica Vol. 98 No. 2 (2025)]]></dc:title>
<dc:creator><![CDATA[Czarnecka, Kaja. Autor]]></dc:creator>
<dc:subject xml:lang="en"><![CDATA[cold spot]]></dc:subject>
<dc:subject xml:lang="en"><![CDATA[hot spot]]></dc:subject>
<dc:subject xml:lang="en"><![CDATA[land surface temperature]]></dc:subject>
<dc:subject xml:lang="en"><![CDATA[air temperature]]></dc:subject>
<dc:subject xml:lang="en"><![CDATA[land cover]]></dc:subject>
<dc:subject xml:lang="en"><![CDATA[local climate zones]]></dc:subject>
<dc:subject xml:lang="en"><![CDATA[spatial development]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[zimne miejsce]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[gorące miejsce]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[temperatura powierzchni terenu]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[temperatura powietrza]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[pokrycie terenu]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[lokalne strefy klimatyczne]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[rozwój przestrzenny]]></dc:subject>
<dc:description xml:lang="en"><![CDATA[24 cm]]></dc:description>
<dc:description xml:lang="en"><![CDATA[The expansion of cities, alongside increasing climate-related risks, requires a better understanding of urban thermal patterns for sustainable planning. This study identifies thermal hot and cold spots in Warsaw using 25 land surface temperature (LST) images (2002-2018), air temperature data from 21 sites, spatial development indicators, CORINE Land Cover, and local climate zones. Spatial autocorrelation (Getis-Ord Gi*) and correlation analyses reveal that LST extremes are related to land cover, spatial development, and city centre proximity. Cluster analysis highlights distinct seasonal and diurnal air temperature regimes in hot/cold spots,emphasizing the need for integrated approaches in urban climate research.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[24 cm]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[The expansion of cities, alongside increasing climate-related risks, requires a better understanding of urban thermal patterns for sustainable planning. This study identifies thermal hot and cold spots in Warsaw using 25 land surface temperature (LST) images (2002-2018), air temperature data from 21 sites, spatial development indicators, CORINE Land Cover, and local climate zones. Spatial autocorrelation (Getis-Ord Gi*) and correlation analyses reveal that LST extremes are related to land cover, spatial development, and city centre proximity. Cluster analysis highlights distinct seasonal and diurnal air temperature regimes in hot/cold spots,emphasizing the need for integrated approaches in urban climate research.]]></dc:description>
<dc:publisher><![CDATA[IGiPZ PAN]]></dc:publisher>
<dc:date><![CDATA[2025]]></dc:date>
<dc:type xml:lang="en"><![CDATA[Text]]></dc:type>
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<dc:identifier><![CDATA[0016-7282 (print)]]></dc:identifier>
<dc:identifier><![CDATA[2300-7362 (online)]]></dc:identifier>
<dc:identifier><![CDATA[10.7163/GPol.0297]]></dc:identifier>
<dc:identifier><![CDATA[https://rcin.org.pl/igipz/dlibra/publication/282055/edition/245360/content]]></dc:identifier>
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<dc:source xml:lang="pl"><![CDATA[CBGiOS. IGiPZ PAN, sygn.: Cz.2085, Cz.2173, Cz.2406]]></dc:source>
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<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[Geographia Polonica]]></dc:relation>
<dc:relation><![CDATA[Ai, X., Zheng, X., Zhang, Y., Liu, Y., Ou, X., Xia, C., & Liu, L. (2024). Climate and land use changes impact the trajectories of ecosystem service bundles in an urban agglomeration: Intricate interaction trends and driver identification under SSP-RCP scenarios. Science of The Total Environment, 944. https://doi.org/10.1016/j.scitotenv.2024.173828]]></dc:relation>
<dc:relation><![CDATA[Anders, J., Schubert, S., Maronga, B., & Salim, M. (2025). Simplifying heat stress assessment: Evaluating meteorological variables as single indicators of outdoor thermal comfort in urban environments. Building and Environment, 274. https://doi.org/10.1016/j.buildenv.2025.112658]]></dc:relation>
<dc:relation><![CDATA[Aram, F., Higueras Garcí a, E., Solgi, E., & Mansournia, S. (2019). Urban green space cooling effect in cities. Heliyon, 5(4). https://doi.org/10.1016/j.heliyon.2019.e01339]]></dc:relation>
<dc:relation><![CDATA[Cao, J., Zhou, W., Zheng, Z., Ren, T., & Wang, W. (2021). Within-city spatial and temporal heterogeneity of air temperature and its relationship with land surface temperature. Landscape and Urban Planning, 206. https://doi.org/10.1016/j.landurbplan.2020.103979]]></dc:relation>
<dc:relation><![CDATA[Chang, C.-R., & Li, M.-H. (2014). Effects of urban parks on the local urban thermal environment. Urban Forestry & Urban Greening, 13(4), 672-681. https://doi.org/10.1016/j.ufug.2014.08.001]]></dc:relation>
<dc:relation><![CDATA[Cheval, S., Micu, D., Dumitrescu, A., Irimescu, A., Frighenciu, M., Iojă, C., Tudose, N. C., Davidescu, Ș., & Antonescu, B. (2020). Meteorological and Ancillary Data Resources for Climate Research in Urban Areas. Climate, 8(3), 37. https://doi.org/10.3390/cli8030037]]></dc:relation>
<dc:relation><![CDATA[Chief Inspectorate for Environmental Protection. (accessed: 1.05.2024). Corine Land Cover 2018 [Dataset]. https://clc.gios.gov.pl/index.php/clc-2018/udostepnianie]]></dc:relation>
<dc:relation><![CDATA[Chief Inspectorate for Environmental Protection. (accessed: 1.08.2024). Corrected database CORINE Land Cover 2000 [Dataset]. https://clc.gios.gov.pl/index.php/clc-2006/udostepnianie]]></dc:relation>
<dc:relation><![CDATA[Copernicus Land Monitoring Service. (accessed: 3.09.2024). CORINE Land Cover. https://land.copernicus.eu/en/products/corine-land-cover]]></dc:relation>
<dc:relation><![CDATA[Coutts, A. M., Harris, R. J., Phan, T., Livesley, S. J., Williams, N. S. G., & Tapper, N. J. (2016). Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning. Remote Sensing of Environment, 186, 637-651. https://doi.org/10.1016/j.rse.2016.09.007]]></dc:relation>
<dc:relation><![CDATA[Czarnecka, K., Kuchcik, M., & Baranowski, J. (2024). Spatial development indicators as a tool to determine thermal conditions in an urban environment. Sustainable Cities and Society, 100. https://doi.org/10.1016/j.scs.2023.105014]]></dc:relation>
<dc:relation><![CDATA[Dąbrowska-Zielińska, K., Gurdak, R., Grzybowski, P., & Olszewski, D. (2019). Opracowanie końcowe określające stan ekosystemu m.st. Warszawy w kontekście zmian klimatu w ramach projektu LIFE_ADAPTCTY_PL. Warsaw: Institute of Geodesy and Cartography, The Remote Sensing Center.]]></dc:relation>
<dc:relation><![CDATA[Dąbrowska-Zielińska, K., Hościło, A., Tomaszewska, M., & Kiryła, W. (2015). LIFE ADAPTCITY PL - Przygotowanie strategii adaptacji do zmian klimatu miasta metropolitarnego przy wykorzystaniu mapy klimatycznej i partycypacji społecznych. Sprawozdanie z realizacji projektu. Warsaw: Institute of Geodesy and Cartography, The Remote Sensing Center.]]></dc:relation>
<dc:relation><![CDATA[Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., van Vliet, J., & Bechtel, B. (2022). A global map of local climate zones to support earth system modelling and urban-scale environmental science. Earth System Science Data, 14(8), 3835-3873. https://doi.org/10.5194/essd-14-3835-2022]]></dc:relation>
<dc:relation><![CDATA[Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., Vliet, J. van, & Bechtel, B. (2023). Global map of Local Climate Zones (3.0.0) (Version 3.0.0) [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.8419340]]></dc:relation>
<dc:relation><![CDATA[Feyisa, G. L., Meilby, H., Darrel Jenerette, G., & Pauliet, S. (2016). Locally optimized separability enhancement indices for urban land cover mapping: Exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia. Remote Sensing of Environment, 175, 14-31. https://doi.org/10.1016/j.rse.2015.12.026]]></dc:relation>
<dc:relation><![CDATA[Gawuć, L., Jefimow, M., Szymankiewicz, K., Kuchcik, M., Sattari, A., & Strużewska, J. (2020). Statistical modeling of urban heat island intensity in Warsaw, Poland using simultaneous air and surface temperature observations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 2716-2728. https://doi.org/10.1109/JSTARS.2020.2989071]]></dc:relation>
<dc:relation><![CDATA[Geletič, J., Lehnert, M., & Dobrovolný, P. (2016). Land surface temperature differences within local climate zones, based on two Central European cities. Remote Sensing, 8(10), 788. https://doi.org/10.3390/rs8100788]]></dc:relation>
<dc:relation><![CDATA[Geletič, J., Lehnert, M., Resler, J., Krč, P., Bureš, M., Urban, A., & Krayenhoff, E. S. (2023). Heat exposure variations and mitigation in a densely populated neighborhood during a hot day: Towards a people-oriented approach to urban climate management. Building and Environment, 242. https://doi.org/10.1016/j.buildenv.2023.110564]]></dc:relation>
<dc:relation><![CDATA[Geletič, J., Lehnert, M., Savić, S., & Milošević, D. (2019). Inter-/intra-zonal seasonal variability of the surface urban heat island based on local climate zones in three central European cities. Building and Environment, 156, 21-32. https://doi.org/10.1016/j.buildenv.2019.04.011]]></dc:relation>
<dc:relation><![CDATA[Greene, C. S., & Kedron, P. J. (2018). Beyond fractional coverage: A multilevel approach to analyzing the impact of urban tree canopy structure on surface urban heat islands. Applied Geography, 95, 45-53. https://doi.org/10.1016/j.apgeog.2018.04.004]]></dc:relation>
<dc:relation><![CDATA[Grigoraș, G., & Urițescu, B. (2018). Spatial hotspot analysis of Bucharest's Urban Heat Island (UHI) using modis data. Annals of Valahia University of Targoviste Geographical Series, 18, 14-22. https://doi.org/10.2478/avutgs-2018-0002]]></dc:relation>
<dc:relation><![CDATA[Grimmond, S. (2007). Urbanization and global environmental change: Local effects of urban warming. The Geographical Journal, 173(1), 83-88. https://doi.org/10.1111/j.1475-4959.2007.232_3.x]]></dc:relation>
<dc:relation><![CDATA[Guerri, G., Crisci, A., Congedo, L., Munafò, M., & Morabito, M. (2022). A functional seasonal thermal hotspot classification: Focus on industrial sites. Science of The Total Environment, 806. https://doi.org/10.1016/j.scitotenv.2021.151383]]></dc:relation>
<dc:relation><![CDATA[Guerri, G., Crisci, A., Messeri, A., Congedo, L., Munafò, M., & Morabito, M. (2021). Thermal summer diurnal hot-spot analysis: The role of local urban features layers. Remote Sensing, 13(3). https://doi.org/10.3390/rs13030538]]></dc:relation>
<dc:relation><![CDATA[Guo, Y., Unger, J., Khabibolla, A., Tian, G., He, R., Li, H., & Gál, T. (2024). Modeling urban air temperature using satellite-derived surface temperature, meteorological data, and local climate zone pattern - A case study in Szeged, Hungary. Theoretical and Applied Climatology, 155(5), 3841-3859. https://doi.org/10.1007/s00704-024-04852-7]]></dc:relation>
<dc:relation><![CDATA[Gupta, R. K. (2024). Identifying urban hotspots and cold spots in Delhi using the biophysical landscape framework. Ecology, Economy and Society-the INSEE Journal, 7. https://doi.org/10.37773/ees.v7i1.954]]></dc:relation>
<dc:relation><![CDATA[He, T., Zhou, R., Ma, Q., Li, C., Liu, D., Fang, X., Hu, Y., & Gao, J. (2023). Quantifying the effects of urban development intensity on the surface urban heat island across building climate zones. Applied Geography, 158. https://doi.org/10.1016/j.apgeog.2023.103052]]></dc:relation>
<dc:relation><![CDATA[Hebbert, M. (2014). Climatology for city planning in historical perspective. Urban Climate, 10, 204-215. https://doi.org/10.1016/j.uclim.2014.07.001]]></dc:relation>
<dc:relation><![CDATA[Hidalgo-Garcí a, D., & Arco-Dí az, J. (2022). Modeling the Surface Urban Heat Island (SUHI) to study of its relationship with variations in the thermal field and with the indices of land use in the metropolitan area of Granada (Spain). Sustainable Cities and Society, 87. https://doi.org/10.1016/j.scs.2022.104166]]></dc:relation>
<dc:relation><![CDATA[Huang, X., & Wang, Y. (2019). Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A case study of Wuhan, Central China. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 119-131. https://doi.org/10.1016/j.isprsjprs.2019.04.010]]></dc:relation>
<dc:relation><![CDATA[Hussain, N., Ahmed, S. M. S., & Shumi, A. M. (2023). Remote sensing-based geostatistical hot spot analysis of Urban Heat Islands in Dhaka, Bangladesh. Singapore Journal of Tropical Geography, 44(3), 438-458. https://doi.org/10.1111/sjtg.12507]]></dc:relation>
<dc:relation><![CDATA[Jamei, Y., Rajagopalan, P., & Sun, Q. (Chayn). (2019). Spatial structure of surface urban heat island and its relationship with vegetation and built-up areas in Melbourne, Australia. Science of The Total Environment, 659, 1335-1351. https://doi.org/10.1016/j.scitotenv.2018.12.308]]></dc:relation>
<dc:relation><![CDATA[Jin, L., Schubert, S., Fenner, D., Salim, M. H., & Schneider, C. (2022). Estimation of mean radiant temperature in cities using an urban parameterization and building energy model within a mesoscale atmospheric model. Meteorologische Zeitschrift, 31(1), 31-52. https://doi.org/10.1127/metz/2021/1091]]></dc:relation>
<dc:relation><![CDATA[Kleerekoper, L., van Esch, M., & Salcedo, T. B. (2012). How to make a city climate-proof, addressing the urban heat island effect. Resources, Conservation and Recycling, 64, 30-38. https://doi.org/10.1016/j.resconrec.2011.06.004]]></dc:relation>
<dc:relation><![CDATA[Krayenhoff, E. S., & Voogt, J. A. (2016). Daytime thermal anisotropy of urban neighbourhoods: Morphological causation. Remote Sensing, 8(2), 108. https://doi.org/10.3390/rs8020108]]></dc:relation>
<dc:relation><![CDATA[Kuchcik, M., & Czarnecka, K. (2023). A general thermal characterisation of the Vistula Valley in Warsaw. Przegląd Geograficzny, 95(3). https://doi.org/10.7163/PrzG.2023.3.6]]></dc:relation>
<dc:relation><![CDATA[Kuchcik, M., Czarnecka, K., & Błażejczyk, K. (2024). Urban heat island in Warsaw (Poland): Current development and projections for 2050. Urban Climate, 55. https://doi.org/10.1016/j.uclim.2024.101901]]></dc:relation>
<dc:relation><![CDATA[Květoňová, V., Pánek, J., Geletič, J., Šimáček, P., & Lehnert, M. (2024). Where is the heat threat in a city? Different perspectives on people-oriented and remote sensing methods: The case of Prague. Heliyon, 10(16). https://doi.org/10.1016/j.heliyon.2024.e36101]]></dc:relation>
<dc:relation><![CDATA[Lehnert, M., Geletič, J., & Jurek, M. (2023). Traditional and novel approaches to studying the human thermal environment in urban areas: A critical review of the current state of the art. Geografie, 128(3), 351-377. https://doi.org/10.37040/geografie.2023.012]]></dc:relation>
<dc:relation><![CDATA[Liu, W., Zhao, H., Sun, S., Xu, X., Huang, T., & Zhu, J. (2022). Green space cooling effect and contribution to mitigate heat island effect of surrounding communities in Beijing Metropolitan Area. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.870403]]></dc:relation>
<dc:relation><![CDATA[Manoli, G., Fatichi, S., Schläpfer, M., Yu, K., Crowther, T. W., Meili, N., Burlando, P., Katul, G., & Zeid, E. B. (2020). Reply to Martilli et al. (2020): Summer average urban-rural surface temperature differences do not indicate the need for urban heat reduction. OSF Preprints. https://doi.org/10.31219/osf.io/mwpna]]></dc:relation>
<dc:relation><![CDATA[Martilli, A., Roth, M., Chow, W. T. L., Demuzere, M., Lipson, M., Krayenhoff, E. S., … & Hart, M. A. (2020). Summer average urban-rural surface temperature differences do not indicate the need for urban heat reduction. Research Collection School of Social Sciences, Paper 3391. https://doi.org/10.31219/osf.io/8gnbf]]></dc:relation>
<dc:relation><![CDATA[Matias, M., & Lopes, A. (2020). Surface radiation balance of urban materials and their impact on air temperature of an urban canyon in Lisbon, Portugal. Applied Sciences, 10(6). https://doi.org/10.3390/app10062193]]></dc:relation>
<dc:relation><![CDATA[Mavrakou, T., Polydoros, A., Cartalis, C., & Santamouris, M. (2018). Recognition of thermal hot and cold spots in urban areas in support of mitigation plans to counteract overheating: Application for Athens. Climate, 6(1). https://doi.org/10.3390/cli6010016]]></dc:relation>
<dc:relation><![CDATA[Naserikia, M., Hart, M. A., Nazarian, N., Bechtel, B., Lipson, M., & Nice, K. A. (2023). Land surface and air temperature dynamics: The role of urban form and seasonality. Science of The Total Environment, 905. https://doi.org/10.1016/j.scitotenv.2023.167306]]></dc:relation>
<dc:relation><![CDATA[Office of Architecture and Spatial Planning of the Capital City of Warsaw City Hall. (2018). Atlas Ekofizjograficzny Miasta Stołecznego Warszawy.]]></dc:relation>
<dc:relation><![CDATA[Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1-24. https://doi.org/10.1002/qj.49710845502]]></dc:relation>
<dc:relation><![CDATA[Oke, T. R. (2006). Towards better scientific communication in urban climate. Theoretical and Applied Climatology, 84(1), 179-190. https://doi.org/10.1007/s00704-005-0153-0]]></dc:relation>
<dc:relation><![CDATA[Peel, M. C., Finlayson, B. L., & McMahon, T. A. (2007). Updated world map of the Kö ppen-Geiger climate classification. Hydrology and Earth System Sciences, 11(5), 1633-1644. https://doi.org/10.5194/hess-11-1633-2007]]></dc:relation>
<dc:relation><![CDATA[Ramani, V., Arjunan, P., Poolla, K., & Miller, C. (2024). Semantic segmentation of longitudinal thermal images for identification of hot and cool spots in urban areas. Building and Environment, 249. https://doi.org/10.1016/j.buildenv.2023.111112]]></dc:relation>
<dc:relation><![CDATA[Rubel, F., & Kottek, M. (2010). Observed and projected climate shifts 1901-2100 depicted by world maps of the Kö ppen-Geiger climate classification. Meteorologische Zeitschrift, 19(2), 135-141. https://doi.org/10.1127/0941-2948/2010/0430]]></dc:relation>
<dc:relation><![CDATA[Sameen, M. I., & Kubaisy, M. A. A. (2014). Automatic surface temperature mapping in ArcGIS using Landsat-8 TIRS and ENVI tools, case study: Al Habbaniyah Lake. Journal of Environment and Earth Science, 4(12).]]></dc:relation>
<dc:relation><![CDATA[Sharma, R., Pradhan, L., Kumari, M., & Bhattacharya, P. (2021). Assessing urban heat islands and thermal comfort in Noida City using geospatial technology. Urban Climate, 35. https://doi.org/10.1016/j.uclim.2020.100751]]></dc:relation>
<dc:relation><![CDATA[Sheng, L., Tang, X., You, H., Gu, Q., & Hu, H. (2017). Comparison of the urban heat island intensity quantified by using air temperature and Landsat land surface temperature in Hangzhou, China. Ecological Indicators, 72, 738-746. https://doi.org/10.1016/j.ecolind.2016.09.009]]></dc:relation>
<dc:relation><![CDATA[Sismanidis, P., Keramitsoglou, I., & Kiranoudis, C. T. (2017). Identifying and characterizing the diurnal evolution of urban land surface temperature patterns. 2017 Joint Urban Remote Sensing Event (JURSE), 1-4. https://doi.org/10.1109/JURSE.2017.7924598]]></dc:relation>
<dc:relation><![CDATA[Smid, M., Russo, S., Costa, A. C., Granell, C., & Pebesma, E. (2019). Ranking European capitals by exposure to heat waves and cold waves. Urban Climate, 27, 388-402. https://doi.org/10.1016/j.uclim.2018.12.010]]></dc:relation>
<dc:relation><![CDATA[Statistics Poland. (accessed: 14.08.2024). M.st. Warszawa. Categories: Population, Territorial division. Years: 2001, 2018. https://bdl.stat.gov.pl/bdl/dane/teryt/jednostka#]]></dc:relation>
<dc:relation><![CDATA[Středová, H., Chuchma, F., Rožnovský, J., & Středa, T. (2021). Local climate zones, land surface temperature and air temperature interactions: Case study of Hradec Králové, the Czech Republic. ISPRS International Journal of Geo-Information, 10(10). https://doi.org/10.3390/ijgi10100704]]></dc:relation>
<dc:relation><![CDATA[USGS. (accessed: 31.07.2024). Frequently Asked Questions. https://www.usgs.gov/faqs/]]></dc:relation>
<dc:relation><![CDATA[Walawender, J. P., Szymanowski, M., Hajto, M. J., & Bokwa, A. (2014). Land surface temperature patterns in the urban agglomeration of Krakow (Poland) derived from Landsat-7/ETM+ data. Pure and Applied Geophysics, 171(6), 913-940. https://doi.org/10.1007/s00024-013-0685-7]]></dc:relation>
<dc:relation><![CDATA[Yuan, B., Zhou, L., Dang, X., Sun, D., Hu, F., & Mu, H. (2021). Separate and combined effects of 3D building features and urban green space on land surface temperature. Journal of Environmental Management, 295, 113116. https://doi.org/10.1016/j.jenvman.2021.113116]]></dc:relation>
<dc:relation><![CDATA[Zhao, K., Qi, M., Yan, X., Li, L., & Huang, X. (2023). Dynamic impact of urban built environment on land surface temperature considering spatio-temporal heterogeneity: A perspective of local climate zone. Land, 12(12). https://doi.org/10.3390/land12122148]]></dc:relation>
<dc:relation><![CDATA[oai:rcin.org.pl:publication:282055]]></dc:relation>
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