{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T05:33:31Z","timestamp":1775021611333,"version":"3.50.1"},"reference-count":73,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,11]],"date-time":"2023-03-11T00:00:00Z","timestamp":1678492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41801234"],"award-info":[{"award-number":["41801234"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Surface urban heat islands (SUHIs) are essential for evaluating urban thermal environments. However, current quantitative studies of SUHIs ignore the thermal radiation directionality (TRD), which directly affects study precision; furthermore, they fail to assess the effects of TRD characteristics at different land-use intensities, on the quantitative studies of SUHIs. To bridge this research gap, this study eliminates the interference of atmospheric attenuation and daily temperature variation factors, in quantifying the TRD based on land surface temperature (LST), from MODIS data and station air temperature data for Hefei (China) from 2010\u20132020. The influence of TRD on SUHI intensity quantification was evaluated by comparing the TRD under different land-use intensities in Hefei. The results show that: (1) daytime and nighttime directionality can reach up to 4.7 K and 2.6 K, and occur in areas with the highest and medium urban land-use intensity, respectively. (2) There are two significant TRD hotspots for daytime urban surfaces, where the sensor zenith angle is approximately the same as the forenoon solar zenith angle, and where the sensor zenith angle is near its nadir in the afternoon. (3) The TRD can contribute up to 2.0 K to the results of assessing the SUHI intensity based on satellite data, which is approximately 31\u201344% of the total SUHI in Hefei.<\/jats:p>","DOI":"10.3390\/s23063041","type":"journal-article","created":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T03:28:33Z","timestamp":1678678113000},"page":"3041","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Quantitative Study of a Directional Heat Island in Hefei, China Based on Multi-Source Data"],"prefix":"10.3390","volume":"23","author":[{"given":"Biao","family":"Shi","sequence":"first","affiliation":[{"name":"College of Resources and Environment, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Lili","family":"Tu","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Lu","family":"Jiang","sequence":"additional","affiliation":[{"name":"Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210046, China"},{"name":"School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}]},{"given":"Jiyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Jun","family":"Geng","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"},{"name":"The Centre d\u2019 Etudes Spatiales de la Biosphere, University of Toulouse, 31062 Toulouse, France"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2012.12.008","article-title":"Satellite-derived land surface temperature: Current status and perspectives","volume":"131","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.rse.2014.03.027","article-title":"Minimum configuration of thermal infrared bands for land surface temperature and emissivity estimation in the context of potential future missions","volume":"148","author":"Sobrino","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_3","first-page":"28","article-title":"Application of Landsat 8 imagery to regional-scale assessment of lake water quality","volume":"51","author":"Urbanski","year":"2016","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/S0034-4257(03)00079-8","article-title":"Thermal remote sensing of urban climates","volume":"86","author":"Voogt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.rse.2017.04.008","article-title":"A framework for the retrieval of all-weather land surface temperature at a high spatial resolution from polar-orbiting thermal infrared and passive microwave data","volume":"195","author":"Duan","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Jiang, Y., and Lin, W.P. (2021). A Comparative Analysis of Retrieval Algorithms of Land Surface Temperature from Landsat-8 Data: A Case Study of Shanghai, China. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18115659"},{"key":"ref_7","first-page":"1","article-title":"Split-Window Algorithm for Land Surface Temperature Retrieval from Landsat-9 Remote Sensing Images","volume":"19","author":"Ye","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"112774","DOI":"10.1016\/j.rse.2021.112774","article-title":"Determination of global land surface temperature using data from only five selected thermal infrared channels: Method extension and accuracy assessment","volume":"268","author":"Zheng","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1016\/j.rse.2018.07.019","article-title":"Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data","volume":"216","author":"Ma","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e2021GL094485","DOI":"10.1029\/2021GL094485","article-title":"Reconciling Debates on the Controls on Surface Urban Heat Island Intensity: Effects of Scale and Sampling","volume":"48","author":"Lai","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.isprsjprs.2022.02.019","article-title":"Taxonomy of seasonal and diurnal clear-sky climatology of surface urban heat island dynamics across global cities","volume":"187","author":"Liu","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"12134","DOI":"10.1021\/es5021185","article-title":"Satellite-Derived Subsurface Urban Heat Island","volume":"48","author":"Zhan","year":"2014","journal-title":"Environ. Sci. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e2022GL100689","DOI":"10.1029\/2022GL100689","article-title":"Urban-Rural Gradient in Urban Heat Island Variations Responsive to Large-scale Human Activity Changes during Chinese New Year Holiday","volume":"49","author":"Zhan","year":"2022","journal-title":"Geophys. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.geothermics.2018.12.014","article-title":"Monitoring thermal anomaly and radiative heat flux using thermal infrared satellite imagery\u2014A case study at Tuzla geothermal region","volume":"78","author":"Sekertekin","year":"2019","journal-title":"Geothermics"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s10661-019-7286-6","article-title":"Spatial estimation of surface ozone concentrations in Quito Ecuador with remote sensing data, air pollution measurements and meteorological variables","volume":"191","author":"Teodoro","year":"2019","journal-title":"Environ. Monit. Assess."},{"key":"ref_16","first-page":"5818","article-title":"Research on quantitative evaluations of heat islands for the Beijing-Tianjin-Hebei Urban Agglomeration","volume":"37","author":"Liu","year":"2017","journal-title":"Shengtai Xuebao\/Acta Ecol. Sin."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"156829","DOI":"10.1016\/j.scitotenv.2022.156829","article-title":"Quantifying the spatial pattern of urban heat islands and the associated cooling effect of blue\u2013green landscapes using multisource remote sensing data","volume":"843","author":"Xue","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhang, Y.T., Li, D.L., Liu, L.B., Liang, Z., Shen, J.S., Wei, F.L., and Li, S.C. (2021). Spatiotemporal Characteristics of the Surface Urban Heat Island and Its Driving Factors Based on Local Climate Zones and Population in Beijing, China. Atmosphere, 12.","DOI":"10.3390\/atmos12101271"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"103585","DOI":"10.1016\/j.scs.2021.103585","article-title":"Spatial patterns and temporal variations of footprint and intensity of surface urban heat island in 141 China cities","volume":"77","author":"Hu","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ejiagha, I.R., Ahmed, M.R., Dewan, A., Gupta, A., Rangelova, E., and Hassan, Q.K. (2022). Urban Warming of the Two Most Populated Cities in the Canadian Province of Alberta, and Its Influencing Factors. Sensors, 22.","DOI":"10.3390\/s22082894"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Mohammad, P., Goswami, A., and Bonafoni, S. (2019). The Impact of the Land Cover Dynamics on Surface Urban Heat Island Variations in Semi-Arid Cities: A Case Study in Ahmedabad City, India, Using Multi-Sensor\/Source Data. Sensors, 19.","DOI":"10.3390\/s19173701"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.scs.2016.03.009","article-title":"Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use\/Land Cover in Tehran","volume":"23","author":"Bokaie","year":"2016","journal-title":"Sustain. Cities Soc."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/s13157-016-0738-7","article-title":"Quantifying the Impact of Land use\/Land Cover Changes on the Urban Heat Island: A Case Study of the Natural Wetlands Distribution Area of Fuzhou City, China","volume":"36","author":"Cai","year":"2016","journal-title":"Wetlands"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.landurbplan.2012.05.016","article-title":"Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations","volume":"107","author":"Su","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s12665-021-09540-7","article-title":"Analysis of urban heat island characteristics and mitigation strategies for eight arid and semi-arid gulf region cities","volume":"80","author":"Abulibdeh","year":"2021","journal-title":"Environ. Earth Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Amir Siddique, M., Wang, Y., Xu, N., Ullah, N., and Zeng, P. (2021). The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA\u2013Markov Modeling (2004\u20132050). Remote Sens., 13.","DOI":"10.3390\/rs13224697"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Han, J., Zhao, X., Zhang, H., and Liu, Y. (2021). Analyzing the Spatial Heterogeneity of the Built Environment and Its Impact on the Urban Thermal Environment\u2014Case Study of Downtown Shanghai. Sustainability, 13.","DOI":"10.3390\/su132011302"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Liu, F., Hou, H., and Murayama, Y. (2021). Spatial Interconnections of Land Surface Temperatures with Land Cover\/Use: A Case Study of Tokyo. Remote Sens., 13.","DOI":"10.3390\/rs13040610"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2777","DOI":"10.3390\/su14052777","article-title":"An Investigation to Identify the Effectiveness of Socioeconomic, Demographic, and Buildings&rsquo; Characteristics on Surface Urban Heat Island Patterns","volume":"14","author":"Sidiqui","year":"2022","journal-title":"Sustainability"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"103128","DOI":"10.1016\/j.scs.2021.103128","article-title":"Evaluating the role of urban fabric on surface urban heat island: The case of Istanbul","volume":"73","author":"Terzi","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Shi, L., Ling, F., Foody, G.M., Yang, Z., Liu, X., and Du, Y. (2021). Seasonal SUHI Analysis Using Local Climate Zone Classification: A Case Study of Wuhan, China. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18147242"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Shi, Y., Xiang, Y., and Zhang, Y. (2019). Urban Design Factors Influencing Surface Urban Heat Island in the High-Density City of Guangzhou Based on the Local Climate Zone. Sensors, 19.","DOI":"10.20944\/preprints201906.0010.v1"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Johnson, D.P. (2022). Population-Based Disparities in U.S. Urban Heat Exposure from 2003 to 2018. Int. J. Environ. Res. Public Health, 19.","DOI":"10.20944\/preprints202208.0365.v1"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"103717","DOI":"10.1016\/j.scs.2022.103717","article-title":"Effects of landscape patterns on the morphological evolution of surface urban heat island in Hangzhou during 2000\u20132020","volume":"79","author":"Wu","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.rse.2011.06.022","article-title":"Experimental characterization and modelling of the nighttime directional anisotropy of thermal infrared measurements over an urban area: Case study of Toulouse (France)","volume":"117","author":"Lagouarde","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1002\/qj.49708837811","article-title":"Radiative temperature in the heat balance of natural surfaces","volume":"88","author":"Monteith","year":"1962","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1109\/TGRS.1981.350357","article-title":"Remote Sensing of Temperature Profiles in Vegetation Canopies Using Multiple View Angles And Inversion Techniques","volume":"2","author":"Kimes","year":"1981","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1080\/0143116031000116408","article-title":"Different approaches in estimating heat flux using dual angle observations of radiative surface temperature","volume":"25","author":"Merlin","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","first-page":"365","article-title":"Field observations of background thermal radiation directionality in natural forests","volume":"21","author":"Jun","year":"2017","journal-title":"J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"6911","DOI":"10.1109\/TGRS.2018.2845678","article-title":"A New Directional Canopy Emissivity Model Based on Spectral Invariants","volume":"56","author":"Cao","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2699","DOI":"10.5194\/amt-8-2699-2015","article-title":"The effect of radiometer placement and view on inferred directional and hemispheric radiometric temperatures of an urban canopy","volume":"8","author":"Adderley","year":"2015","journal-title":"Atmos. Meas. Technol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.rse.2003.12.011","article-title":"Airborne experimental measurements of the angular variations in surface temperature over urban areas: Case study of Marseille (France)","volume":"93","author":"Lagouarde","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"109408","DOI":"10.1016\/j.buildenv.2022.109408","article-title":"Diurnal variations in directional brightness temperature over urban areas through a multi-angle UAV experiment","volume":"222","author":"Jiang","year":"2022","journal-title":"Build. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/s00703-008-0325-4","article-title":"Directional anisotropy in thermal infrared measurements over Toulouse city centre during the CAPITOUL measurement campaigns: First results","volume":"102","author":"Lagouarde","year":"2008","journal-title":"Meteorol. Atmos. Phys."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.rse.2016.03.043","article-title":"A first satellite-based observational assessment of urban thermal anisotropy","volume":"181","author":"Hu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_46","first-page":"1","article-title":"Urban Thermal Anisotropy: A Comparison among Observational and Modeling Approaches at Different Time Scales","volume":"60","author":"Wang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.rse.2019.01.021","article-title":"Angular variations of brightness surface temperatures derived from dual-view measurements of the Advanced Along-Track Scanning Radiometer using a new single band atmospheric correction method","volume":"223","author":"Coll","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"112518","DOI":"10.1016\/j.rse.2021.112518","article-title":"Geometry and adjacency effects in urban land surface temperature retrieval from high-spatial-resolution thermal infrared images","volume":"262","author":"Chen","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Krayenhoff, E.S., and Voogt, J.A. (2016). Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation. Remote Sens., 8.","DOI":"10.3390\/rs8020108"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3088482","article-title":"Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Data over Urban Areas Considering Geometry Effect: Method and Application","volume":"60","author":"Ru","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"112361","DOI":"10.1016\/j.rse.2021.112361","article-title":"Modeling the angular effect of MODIS LST in urban areas: A case study of Toulouse, France","volume":"257","author":"Wang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"6226","DOI":"10.1109\/TGRS.2019.2904871","article-title":"A Geometric Model to Simulate Urban Thermal Anisotropy in Simplified Dense Neighborhoods (GUTA-Dense)","volume":"57","author":"Wang","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s00704-011-0521-x","article-title":"High-frequency fluctuations of surface temperatures in an urban environment","volume":"108","author":"Christen","year":"2012","journal-title":"Theor. Appl. Climatol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1016\/j.egypro.2017.12.722","article-title":"Assessment and Improvement of the Accuracy of Radiation Heat Transfer Estimation in Simplified Urban Canopy Models","volume":"143","author":"Pasha","year":"2017","journal-title":"Energy Procedia"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1007\/s00704-020-03094-7","article-title":"The effect of sub-facet scale surface structure on wall brightness temperatures at multiple scales","volume":"140","author":"Hilland","year":"2020","journal-title":"Theor. Appl. Climatol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2018.12.004","article-title":"Analysis of urban surface morphologic effects on diurnal thermal directional anisotropy","volume":"148","author":"Hu","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1941","DOI":"10.1109\/TGRS.2004.831886","article-title":"Directional effects in a daily AVHRR land surface temperature dataset over Africa","volume":"42","author":"Pinheiro","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","first-page":"23","article-title":"Construction and application of urban geospatial infrastructure framework in Hefei","volume":"22","author":"Wu","year":"2007","journal-title":"Urban Geotech. Investig. Surv."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Yao, X., Chen, Y., Zhang, Q., Mou, Z., Yao, X., and Ou, C. (2022). Assessment of the Urban Expansion and Its Impact on the Eco-Environment\u2014A Case Study of Hefei Municipal Area. Sustainability, 14.","DOI":"10.3390\/su141710613"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.limno.2012.03.002","article-title":"Environmental changes in Chaohu Lake (southeast, China) since the mid 20th century: The interactive impacts of nutrients, hydrology and climate","volume":"43","author":"Chen","year":"2013","journal-title":"Limnologica"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1016\/S1001-0742(12)60171-5","article-title":"Temporal and spatial changes in nutrients and chlorophyll-\u03b1 in a shallow lake, Lake Chaohu, China: An 11-year investigation","volume":"25","author":"Yang","year":"2013","journal-title":"J. Environ. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"7537","DOI":"10.3390\/s150407537","article-title":"Determination of Optimum Viewing Angles for the Angular Normalization of Land Surface Temperature over Vegetated Surface","volume":"15","author":"Ren","year":"2015","journal-title":"Sensors"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1175\/1520-0426(2004)021<0683:AMOSST>2.0.CO;2","article-title":"Autonomous measurements of sea surface temperature using in situ thermal infrared data","volume":"21","author":"Niclos","year":"2004","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2004.09.002","article-title":"In situ angular measurements of thermal infrared sea surface emissivity\u2014Validation of models","volume":"94","author":"Niclos","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1109\/36.508406","article-title":"A generalized split-window algorithm for retrieving land-surface temperature from space","volume":"34","author":"Wan","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.rse.2012.04.024","article-title":"Estimating air surface temperature in Portugal using MODIS LST data","volume":"124","author":"Benali","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_67","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_68","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.rse.2014.10.022","article-title":"A new perspective to assess the urban heat island through remotely sensed atmospheric profiles","volume":"158","author":"Hu","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"6376","DOI":"10.1002\/2013JD021227","article-title":"Evaluating the impact of urban morphology configurations on the accuracy of urban canopy model temperature simulations with MODIS","volume":"119","author":"Monaghan","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/BF00119211","article-title":"Simulation of surface urban heat islands under \u2018ideal\u2019 conditions at night part 2: Diagnosis of causation","volume":"56","author":"Oke","year":"1991","journal-title":"Bound.-Layer Meteorol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1080\/014311698215784","article-title":"Effects of urban surface geometry on remotely-sensed surface temperature","volume":"19","author":"Voogt","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1080\/01431168908904002","article-title":"Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology","volume":"10","author":"Roth","year":"1989","journal-title":"Int. J. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3185","DOI":"10.1002\/2013JD021101","article-title":"How can we use MODIS land surface temperature to validate long-term urban model simulations?","volume":"119","author":"Hu","year":"2014","journal-title":"J. Geophys. Res. Atmos."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/6\/3041\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:52:53Z","timestamp":1760122373000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/6\/3041"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,11]]},"references-count":73,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["s23063041"],"URL":"https:\/\/doi.org\/10.3390\/s23063041","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,11]]}}}