Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives

Remote Sensing - Tập 11 Số 1 - Trang 48
Decheng Zhou1, Jingfeng Xiao2, Stefania Bonafoni3, Christian Berger4, Kaveh Deilami5, Yuyu Zhou6, Steve Frolking2, Rui Yao7, Zhi Qiao8, José A. Sobrino9
1Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
2Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
3Department of Engineering, University of Perugia, Via G. Duranti 93, 06125, Perugia, Italy
4Department for Earth Observation, Friedrich-Schiller-Universität Jena, Löbdergraben 32, 07743 Jena, Germany
5School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
6Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, USA 50011
7Laboratory of Critical Zone Evolution, School of Earth Sciences, China University of Geosciences, Wuhan 430074, China
8Key Lab. of Indoor Air Environment Quality Control, School of Environmental Science and Engineering, Tianjin University, Weijin Road 92, Tianjin 300072, China
9Global Change Unit, Department of Thermodynamics, Faculty of Physics, University of Valencia, E-46071 Valencia, Spain

Tóm tắt

The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms/sensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI/LST variability at a local scale. The Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+)/Thermal Infrared Sensor (TIRS) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite/sensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions/cities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.

Từ khóa


Tài liệu tham khảo

Oke, 1982, The energetic basis of the urban heat island, Q. J. R. Meteorol. Soc., 108, 1

Clinton, 2013, Modis detected surface urban heat islands and sinks: Global locations and controls, Remote Sens. Environ., 134, 294, 10.1016/j.rse.2013.03.008

Li, 2017, The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States, Sci. Total Environ., 605, 426, 10.1016/j.scitotenv.2017.06.229

Peng, 2012, Surface urban heat island across 419 global big cities, Environ. Sci. Technol., 46, 696, 10.1021/es2030438

Zhou, 2017, The role of city size and urban form in the surface urban heat island, Sci. Rep., 7, 4791, 10.1038/s41598-017-04242-2

Zhou, 2014, Surface urban heat island in China’s 32 major cities: Spatial patterns and drivers, Remote Sens. Environ., 152, 51, 10.1016/j.rse.2014.05.017

Rizwan, 2008, A review on the generation, determination and mitigation of urban heat island, J. Environ. Sci., 20, 120, 10.1016/S1001-0742(08)60019-4

Arnfield, 2003, Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island, Int. J. Clim., 23, 1, 10.1002/joc.859

Shepherd, 2005, A review of current investigations of urban-induced rainfall and recommendations for the future, Earth Interact., 9, 1, 10.1175/EI156.1

Stocker, T. (2014). Climate Change 2013: The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.

Zhao, 2016, Prevalent vegetation growth enhancement in urban environment, Proc. Natl. Acad. Sci. USA, 113, 6313, 10.1073/pnas.1602312113

Zhou, 2016, Remotely sensed assessment of urbanization effects on vegetation phenology in China’s 32 major cities, Remote Sens. Environ., 176, 272, 10.1016/j.rse.2016.02.010

Grimm, 2008, Global change and the ecology of cities, Science, 319, 756, 10.1126/science.1150195

Patz, 2005, Impact of regional climate change on human health, Nature, 438, 310, 10.1038/nature04188

Santamouris, 2015, On the impact of urban heat island and global warming on the power demand and electricity consumption of buildings—A review, Energy Build., 98, 119, 10.1016/j.enbuild.2014.09.052

Witmer, 2012, Climate variability and conflict risk in East Africa, 1990–2009, Proc. Natl. Acad. Sci. USA, 109, 18344, 10.1073/pnas.1205130109

UN (2018). United Nations Department of Economic Social Affairs Population Division. World Urbanization Prospects: The 2018 Revision, United Nations. Online Edition.

Seto, 2012, Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools, Proc. Natl. Acad. Sci. USA, 109, 16083, 10.1073/pnas.1211658109

Nichol, 2009, Urban heat island diagnosis using ASTER satellite images and ‘in situ’ air temperature, Atmos. Res., 94, 276, 10.1016/j.atmosres.2009.06.011

Schwarz, 2012, Relationship of land surface and air temperatures and its implications for quantifying urban heat island indicators-an application for the city of Leipzig (Germany), Ecol. Indic., 18, 693, 10.1016/j.ecolind.2012.01.001

Smoliak, 2015, Dense network observations of the twin cities canopy-layer urban heat island, J. Appl. Meteorol. Clim., 54, 1899, 10.1175/JAMC-D-14-0239.1

Clay, 2016, Urban heat island traverses in the city of Adelaide, South Australia, Urban Clim., 17, 89, 10.1016/j.uclim.2016.06.001

Voogt, J. (2018, December 26). How Researchers Measure Urban Heat Islands. Available online: https://bit.ly/2V9awXv.

Mirzaei, 2010, Approaches to study urban heat island—Abilities and limitations, Build. Environ., 45, 2192, 10.1016/j.buildenv.2010.04.001

Anniballe, 2014, Spatial and temporal trends of the surface and air heat island over Milan using MODIS data, Remote Sens. Environ., 150, 163, 10.1016/j.rse.2014.05.005

Jin, 2010, Land surface skin temperature climatology: Benefitting from the strengths of satellite observations, Environ. Res. Lett., 5, 044004, 10.1088/1748-9326/5/4/044004

Wang, 2017, Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network, J. Geophys. Res. Atmos., 122, 2131, 10.1002/2016JD025304

Weng, 2009, Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends, ISPRS J. Photogramm. Remote Sens., 64, 335, 10.1016/j.isprsjprs.2009.03.007

Voogt, 2003, Thermal remote sensing of urban climates, Remote Sens. Environ., 86, 370, 10.1016/S0034-4257(03)00079-8

Deilami, 2018, Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures, Int. J. Appl. Earth Obs. Geoinf., 67, 30

Ho, 2014, Mapping maximum urban air temperature on hot summer days, Remote Sens. Environ., 154, 38, 10.1016/j.rse.2014.08.012

Pichierri, 2012, Satellite air temperature estimation for monitoring the canopy layer heat island of Milan, Remote Sens. Environ., 127, 130, 10.1016/j.rse.2012.08.025

Rao, 1972, Remote sensing of urban “heat islands” from an environmental satellite, Bull. Am. Meteorol. Soc., 53, 647

Gallo, 1995, Assessment of urban heat islands: A satellite perspective, Atmos. Res., 37, 37, 10.1016/0169-8095(94)00066-M

Tomlinson, 2011, Remote sensing land surface temperature for meteorology and climatology: A review, Meteorol. Appl., 18, 296, 10.1002/met.287

Jensen, R.R., Gatrell, J.D., and McLean, D.D. (2005). Satellite remote sensing of urban heat islands: Current practice and prospects. Geo-Spatial Technologies in Urban Environments, Springer.

Huang, 2018, Urban heat island research from 1991 to 2015: A bibliometric analysis, Theor. Appl. Clim., 131, 1055, 10.1007/s00704-016-2025-1

Li, 2013, Satellite-derived land surface temperature: Current status and perspectives, Remote Sens. Environ., 131, 14, 10.1016/j.rse.2012.12.008

Mohamed, 2017, Land surface temperature and emissivity estimation for urban heat island assessment using medium- and low-resolution space-borne sensors: A review, Geocarto Int., 32, 455, 10.1080/10106049.2016.1155657

Bechtel, 2012, Downscaling land surface temperature in an urban area: A case study for Hamburg, Germany, Remote Sens., 4, 3184, 10.3390/rs4103184

Bonafoni, 2016, Downscaling of Landsat and MODIS land surface temperature over the heterogeneous urban area of Milan, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 9, 2019, 10.1109/JSTARS.2016.2514367

Unger, 2004, Intra-urban relationship between surface geometry and urban heat island: Review and new approach, Clim. Res., 27, 253, 10.3354/cr027253

Stewart, 2011, A systematic review and scientific critique of methodology in modern urban heat island literature, Int. J. Clim., 31, 200, 10.1002/joc.2141

Mirzaei, 2015, Recent challenges in modeling of urban heat island, Sustain. Cities Soc., 19, 200, 10.1016/j.scs.2015.04.001

Chapman, 2017, The impact of urbanization and climate change on urban temperatures: A systematic review, Landsc. Ecol., 32, 1921, 10.1007/s10980-017-0561-4

Gago, 2013, The city and urban heat islands: A review of strategies to mitigate adverse effects, Renew Sustain. Energy Rev., 25, 749, 10.1016/j.rser.2013.05.057

Santamouris, 2014, Cooling the cities—A review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environments, Sol. Energy, 103, 682, 10.1016/j.solener.2012.07.003

Larsen, 2015, Urban climate and adaptation strategies, Front. Ecol. Environ., 13, 486, 10.1890/150103

Jamei, 2016, Review on the impact of urban geometry and pedestrian level greening on outdoor thermal comfort, Renew. Sustain. Energy Rev., 54, 1002, 10.1016/j.rser.2015.10.104

Zhang, 2010, Characterizing urban heat islands of global settlements using MODIS and nighttime lights products, Can. J. Remote Sens., 36, 185, 10.5589/m10-039

Zhang, Y., and Liang, S. (2018). Impacts of land cover transitions on surface temperature in China based on satellite observations. Environ. Res. Lett., 13.

Imhoff, 2010, Remote sensing of the urban heat island effect across biomes in the continental USA, Remote Sens. Environ., 114, 504, 10.1016/j.rse.2009.10.008

Zhou, D., Zhang, L., Li, D., Huang, D., and Zhu, C. (2016). Climate-vegetation control on the diurnal and seasonal variations of surface urban heat islands in China. Environ. Res. Lett., 11.

Zhan, 2013, Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats, Remote Sens. Environ., 131, 119, 10.1016/j.rse.2012.12.014

Matson, 1978, Satellite detection of urban heat islands, Mon. Weather Rev., 106, 1725, 10.1175/1520-0493(1978)106<1725:SDOUHI>2.0.CO;2

Matson, 1980, Urban heat islands detected by satellite, Bull. Am. Meteorol. Soc., 61, 212

Price, 1979, Assessment of the urban heat island effect through the use of satellite data, Mon. Weather Rev., 107, 1554, 10.1175/1520-0493(1979)107<1554:AOTUHI>2.0.CO;2

Carnahan, 1990, An analysis of an urban heat sink, Remote Sens. Environ., 33, 65, 10.1016/0034-4257(90)90056-R

Wan, 2002, Validation of the land-surface temperature products retrieved from terra moderate resolution imaging spectroradiometer data, Remote Sens. Environ., 83, 163, 10.1016/S0034-4257(02)00093-7

Zhang, X., Friedl, M.A., Schaaf, C.B., Strahler, A.H., and Schneider, A. (2004). The footprint of urban climates on vegetation phenology. Geophys. Res. Lett., 31.

Nichol, 2005, Remote sensing of urban heat islands by day and night, Photogramm. Eng. Remote Sens., 71, 613, 10.14358/PERS.71.5.613

Roth, 1989, Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology, Int. J. Remote Sens., 10, 1699, 10.1080/01431168908904002

Gallo, 1993, The use of a vegetation index for assessment of the urban heat island effect, Int. J. Remote Sens., 14, 2223, 10.1080/01431169308954031

Weng, 2004, Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies, Remote Sens. Environ., 89, 467, 10.1016/j.rse.2003.11.005

Jin, 2005, The footprint of urban areas on global climate as characterized by MODIS, J. Clim., 18, 1551, 10.1175/JCLI3334.1

Lu, 2006, Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, IN, USA, Remote Sens. Environ., 104, 157, 10.1016/j.rse.2005.11.015

Liu, 2008, Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, IN, USA, Environ. Monit. Assess., 144, 199, 10.1007/s10661-007-9979-5

Schwarz, 2011, Exploring indicators for quantifying surface urban heat islands of european cities with MODIS land surface temperatures, Remote Sens. Environ., 115, 3175, 10.1016/j.rse.2011.07.003

Hu, 2016, A first satellite-based observational assessment of urban thermal anisotropy, Remote Sens. Environ., 181, 111, 10.1016/j.rse.2016.03.043

Chen, 2017, Challenges to quantitative applications of Landsat observations for the urban thermal environment, J. Environ. Sci., 59, 80, 10.1016/j.jes.2017.02.009

Young, 2017, A survival guide to Landsat preprocessing, Ecology, 98, 920, 10.1002/ecy.1730

Wulder, 2016, The global Landsat archive: Status, consolidation, and direction, Remote Sens. Environ., 185, 271, 10.1016/j.rse.2015.11.032

Popkin, 2018, US government considers charging for popular Earth-observing data, Nature, 556, 417, 10.1038/d41586-018-04874-y

Malakar, 2018, An operational land surface temperature product for Landsat thermal data: Methodology and validation, IEEE Trans. Geosci. Remote Sens., 56, 5717, 10.1109/TGRS.2018.2824828

Liao, W.L., Liu, X.P., Wang, D.G., and Sheng, Y.L. (2017). The impact of energy consumption on the surface urban heat island in China’s 32 major cities. Remote Sens., 9.

Peng, 2018, Spatial-temporal change of land surface temperature across 285 cities in China: An urban-rural contrast perspective, Sci. Total Environ., 635, 487, 10.1016/j.scitotenv.2018.04.105

Wan, Z., Zhang, Y., Wang, R., and Li, Z. (2018, December 26). Early Land-Surface Temperature Product Retrieved from MODIS Data, IGARSS 2001. Available online: https://bit.ly/2V3SllY.

Wan, 1996, A generalized split-window algorithm for retrieving land-surface temperature from space, IEEE Trans. Geosci. Remote. Sens., 34, 892, 10.1109/36.508406

Hulley, 2014, Thermal-based techniques for land cover change detection using a new dynamic MODIS multispectral emissivity product (MOD21), Remote Sens. Environ., 140, 755, 10.1016/j.rse.2013.10.014

Abrams, 2000, The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA’s Terra platform, Int. J. Remote Sens., 21, 847, 10.1080/014311600210326

Zhang, 2017, Optimizing green space locations to reduce daytime and nighttime urban heat island effects in Phoenix, Arizona, Landsc. Urban Plan., 165, 162, 10.1016/j.landurbplan.2017.04.009

Zheng, 2014, Spatial configuration of anthropogenic land cover impacts on urban warming, Landsc. Urban Plan., 130, 104, 10.1016/j.landurbplan.2014.07.001

Feng, 2016, Exploring the effect of neighboring land cover pattern on land surface temperature of central building objects, Build. Environ., 95, 346, 10.1016/j.buildenv.2015.09.019

Fan, 2015, Measuring the spatial arrangement of urban vegetation and its impacts on seasonal surface temperatures, Prog. Phys. Geogr. Earth Environ., 39, 199, 10.1177/0309133314567583

Morabito, M., Crisci, A., Georgiadis, T., Orlandini, S., Munafo, M., Congedo, L., Rota, P., and Zazzi, M. (2018). Urban imperviousness effects on summer surface temperatures nearby residential buildings in different urban zones of Parma. Remote Sens., 10.

Abrams, 2015, The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) after fifteen years: Review of global products, Int. J. Appl. Earth Obs. Geoinf., 38, 292

Song, 2016, Examining the impact of urban biophysical composition and neighboring environment on surface urban heat island effect, Adv. Space Res., 57, 96, 10.1016/j.asr.2015.10.036

Wang, 2018, Detection of urban expansion and land surface temperature change using multi-temporal Landsat images, Resour. Conserv. Recycl., 128, 526, 10.1016/j.resconrec.2016.05.011

Zhang, L., Meng, Q., Sun, Z., and Sun, Y. (2017). Spatial and temporal analysis of the mitigating effects of industrial relocation on the surface urban heat island over China. ISPRS Int. J. Geoinf., 6.

Chen, W., Zhang, Y., Pengwang, C., and Gao, W. (2017). Evaluation of urbanization dynamics and its impacts on surface heat islands: A case study of Beijing, China. Remote Sens., 9.

Peng, 2018, Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas, Remote Sens. Environ., 215, 255, 10.1016/j.rse.2018.06.010

Meng, 2018, Characterizing spatial and temporal trends of surface urban heat island effect in an urban main built-up area: A 12-year case study in Beijing, China, Remote Sens. Environ., 204, 826, 10.1016/j.rse.2017.09.019

Estoque, 2017, Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987–2015), ISPRS J. Photogramm. Remote Sens., 133, 18, 10.1016/j.isprsjprs.2017.09.008

Berger, 2017, Spatio-temporal analysis of the relationship between 2D/3D urban site characteristics and land surface temperature, Remote Sens. Environ., 193, 225, 10.1016/j.rse.2017.02.020

Peng, 2016, Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region, Remote Sens. Environ., 173, 145, 10.1016/j.rse.2015.11.027

Li, 2016, Remote sensing of the surface urban heat island and land architecture in Phoenix, Arizona: Combined effects of land composition and configuration and cadastral-demographic-economic factors, Remote Sens. Environ., 174, 233, 10.1016/j.rse.2015.12.022

Quan, 2014, Multi-temporal trajectory of the urban heat island centroid in Beijing, China based on a gaussian volume model, Remote Sens. Environ., 149, 33, 10.1016/j.rse.2014.03.037

Kong, 2014, Effects of spatial pattern of greenspace on urban cooling in a large metropolitan area of Eastern China, Landsc. Urban Plan., 128, 35, 10.1016/j.landurbplan.2014.04.018

Qiao, 2013, Diurnal and seasonal impacts of urbanization on the urban thermal environment: A case study of Beijing using MODIS data, ISPRS J. Photogramm. Remote Sens., 85, 93, 10.1016/j.isprsjprs.2013.08.010

Li, 2013, Relationship between land surface temperature and spatial pattern of greenspace: What are the effects of spatial resolution?, Landsc. Urban Plan., 114, 1, 10.1016/j.landurbplan.2013.02.005

Connors, 2013, Landscape configuration and urban heat island effects: Assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona, Landsc. Ecol., 28, 271, 10.1007/s10980-012-9833-1

Li, 2011, Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China, Remote Sens. Environ., 115, 3249, 10.1016/j.rse.2011.07.008

Naeem, S., Cao, C., Qazi, W.A., Zamani, M., Wei, C., Acharya, B.K., and Rehman, A.U. (2018). Studying the association between green space characteristics and land surface temperature for sustainable urban environments: An analysis of Beijing and Islamabad. ISPRS Int. J. Geoinf., 7.

Madanian, 2018, Analyzing the effects of urban expansion on land surface temperature patterns by landscape metrics: A case study of Isfahan City, Iran, Environ. Monit. Assess., 190, 189, 10.1007/s10661-018-6564-z

Buyantuyev, 2010, Urban heat islands and landscape heterogeneity: Linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns, Landsc. Ecol., 25, 17, 10.1007/s10980-009-9402-4

Liang, 2008, Multiscale analysis of census-based land surface temperature variations and determinants in Indianapolis, United States, J. Urban Plan. Dev., 134, 129, 10.1061/(ASCE)0733-9488(2008)134:3(129)

Yuan, 2007, Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery, Remote Sens. Environ., 106, 375, 10.1016/j.rse.2006.09.003

Coutts, 2016, Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning, Remote Sens. Environ., 186, 637, 10.1016/j.rse.2016.09.007

Yao, 2017, Temporal trends of surface urban heat islands and associated determinants in major Chinese Cities, Sci. Total Environ., 609, 742, 10.1016/j.scitotenv.2017.07.217

Dousset, 2003, Satellite multi-sensor data analysis of urban surface temperatures and landcover, ISPRS J. Photogramm. Remote Sens., 58, 43, 10.1016/S0924-2716(03)00016-9

Zhou, 2013, On the statistics of urban heat island intensity, Geophys. Res. Lett., 40, 5486, 10.1002/2013GL057320

Wang, 2015, Spatiotemporal variation in surface urban heat island intensity and associated determinants across major Chinese Cities, Remote Sens., 7, 3670, 10.3390/rs70403670

Zhao, 2016, Data concurrency is required for estimating urban heat island intensity, Environ. Pollut., 208, 118, 10.1016/j.envpol.2015.07.037

Miles, V., and Esau, I. (2017). Seasonal and spatial characteristics of urban heat islands (uhis) in Northern West Siberian Cities. Remote Sens., 9.

Yang, 2017, Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China, Sci. Rep., 7, 9337, 10.1038/s41598-017-09628-w

Chen, 2006, Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes, Remote Sens. Environ., 104, 133, 10.1016/j.rse.2005.11.016

Haashemi, S., Weng, Q., Darvishi, A., and Alavipanah, S. (2016). Seasonal variations of the surface urban heat island in a semi-arid city. Remote Sens., 8.

Liu, 2017, Assessment of surface urban heat island across China’s three main urban agglomerations, Theor. Appl. Clim., 133, 473, 10.1007/s00704-017-2197-3

Quan, 2016, Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands, J. Geophys. Res. Atmos., 121, 2638, 10.1002/2015JD024354

Zhou, 2018, Remote sensing of the urban heat island effect in a highly populated urban agglomeration area in East China, Sci. Total Environ., 628–629, 415, 10.1016/j.scitotenv.2018.02.074

Zhou, 2016, Spatiotemporal trends of urban heat island effect along the urban development intensity gradient in China, Sci. Total Environ., 544, 617, 10.1016/j.scitotenv.2015.11.168

Tomlinson, 2012, Derivation of birmingham’s summer surface urban heat island from MODIS satellite images, Int. J. Clim., 32, 214, 10.1002/joc.2261

Gallo, 1993, The use of NOAA AVHRR data for assessment of the urban heat island effect, J. Appl. Meteorol., 32, 899, 10.1175/1520-0450(1993)032<0899:TUONAD>2.0.CO;2

Zhang, 2014, Comparison of MODIS land surface temperature and air temperature over the continental USA meteorological stations, Can. J. Remote Sens., 40, 110

Zhao, 2014, Strong contributions of local background climate to urban heat islands, Nature, 511, 216, 10.1038/nature13462

Cao, 2016, Urban heat islands in China enhanced by haze pollution, Nat. Commun., 7, 12509, 10.1038/ncomms12509

Hung, 2006, Assessment with satellite data of the urban heat island effects in Asian mega cities, Int. J. Appl. Earth Obs. Geoinf., 8, 34

Streutker, 2002, A remote sensing study of the urban heat island of Houston, Texas, Int. J. Remote Sens., 23, 2595, 10.1080/01431160110115023

Streutker, 2003, Satellite-measured growth of the urban heat island of Houston, Texas, Remote Sens. Environ., 85, 282, 10.1016/S0034-4257(03)00007-5

Rajasekar, 2009, Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis, ISPRS J. Photogramm. Remote Sens., 64, 86, 10.1016/j.isprsjprs.2008.05.002

Li, 2018, A new method to quantify surface urban heat island intensity, Sci. Total Environ., 624, 262, 10.1016/j.scitotenv.2017.11.360

Oke, 1988, The urban energy balance, Prog. Phys. Geogr. Earth Environ., 12, 471, 10.1177/030913338801200401

Estoque, 2017, Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia, Sci. Total Environ., 577, 349, 10.1016/j.scitotenv.2016.10.195

Xie, 2013, Assessment of landscape patterns affecting land surface temperature in different biophysical gradients in Shenzhen, China, Urban Ecosyst., 16, 871, 10.1007/s11252-013-0325-0

Zhou, 2014, Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures, Landsc. Ecol., 29, 153, 10.1007/s10980-013-9950-5

Bao, T., Li, X., Zhang, J., Zhang, Y., and Tian, S. (2016). Assessing the distribution of urban green spaces and its anisotropic cooling distance on urban heat island pattern in Baotou, China. ISPRS Int. J. Geoinf., 5.

Feyisa, 2014, Efficiency of parks in mitigating urban heat island effect: An example from Addis Ababa, Landsc. Urban Plan., 123, 87, 10.1016/j.landurbplan.2013.12.008

Guo, 2015, Impacts of urban biophysical composition on land surface temperature in urban heat island clusters, Landsc. Urban Plan., 135, 1, 10.1016/j.landurbplan.2014.11.007

Heinl, 2015, Determinants of urban-rural land surface temperature differences—A landscape scale perspective, Landsc. Urban Plan., 134, 33, 10.1016/j.landurbplan.2014.10.003

Yang, C., He, X., Yu, L., Yang, J., Yan, F., Bu, K., Chang, L., and Zhang, S. (2017). The cooling effect of urban parks and its monthly variations in a snow climate city. Remote Sens., 9.

Du, 2017, Quantifying the cool island effects of urban green spaces using remote sensing data, Urban For. Urban Green., 27, 24, 10.1016/j.ufug.2017.06.008

Sun, 2012, How can urban water bodies be designed for climate adaptation?, Landsc. Urban Plan., 105, 27, 10.1016/j.landurbplan.2011.11.018

Wang, X., Cheng, H., Xi, J., Yang, G., and Zhao, Y. (2018). Relationship between park composition, vegetation characteristics and cool island effect. Sustainability, 10.

Lazzarini, 2013, Temperature-land cover interactions: The inversion of urban heat island phenomenon in desert city areas, Remote Sens. Environ., 130, 136, 10.1016/j.rse.2012.11.007

Pan, J. (2015). Analysis of human factors on urban heat island and simulation of urban thermal environment in Lanzhou city, China. J. Appl. Remote Sens., 9.

Yue, 2012, Assessing spatial pattern of urban thermal environment in Shanghai, China, Stoch. Environ. Res. Risk Assess., 26, 899, 10.1007/s00477-012-0638-1

Gage, 2017, Urban forest structure and land cover composition effects on land surface temperature in a semi-arid suburban area, Urban For. Urban Green., 28, 28, 10.1016/j.ufug.2017.10.003

Weng, 2008, The spatial variations of urban land surface temperatures: Pertinent factors, zoning effect, and seasonal variability, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 1, 154, 10.1109/JSTARS.2008.917869

Ranagalage, M., Estoque, R.C., Zhang, X., and Murayama, Y. (2018). Spatial changes of urban heat island formation in the colombo district, Sri Lanka: Implications for sustainability planning. Sustainability, 10.

Li, 2017, Linking potential heat source and sink to urban heat island: Heterogeneous effects of landscape pattern on land surface temperature, Sci. Total Environ., 586, 457, 10.1016/j.scitotenv.2017.01.191

Chen, 2017, Does urbanization increase diurnal land surface temperature variation? Evidence and implications, Landsc. Urban Plan., 157, 247, 10.1016/j.landurbplan.2016.06.014

Yu, 2018, Variations in land surface temperature and cooling efficiency of green space in rapid urbanization: The case of Fuzhou City, China, Urban For. Urban Green., 29, 113, 10.1016/j.ufug.2017.11.008

Bhang, 2009, Evaluation of the surface temperature variation with surface settings on the urban heat island in Seoul, Korea, using Landsat-7 ETM+ and spot, IEEE Geosci. Remote Sens. Lett., 6, 708, 10.1109/LGRS.2009.2023825

Guo, 2016, Characterizing the impact of urban morphology heterogeneity on land surface temperature in Guangzhou, China, Environ. Model. Softw., 84, 427, 10.1016/j.envsoft.2016.06.021

Kuang, 2015, What are hot and what are not in an urban landscape: Quantifying and explaining the land surface temperature pattern in Beijing, China, Landsc. Ecol., 30, 357, 10.1007/s10980-014-0128-6

Yin, 2018, Effects of urban form on the urban heat island effect based on spatial regression model, Sci. Total Environ., 634, 696, 10.1016/j.scitotenv.2018.03.350

Zhou, 2011, Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes, Landsc. Urban Plan., 102, 54, 10.1016/j.landurbplan.2011.03.009

Nassar, 2016, Dynamics and controls of urban heat sink and island phenomena in a desert city: Development of a local climate zone scheme using remotely-sensed inputs, Int. J. Appl. Earth Obs. Geoinf., 51, 76

Scarano, 2015, On the relationship between the sky view factor and the land surface temperature derived by Landsat-8 images in Bari, Italy, Int. J. Remote Sens., 36, 4820, 10.1080/01431161.2015.1070325

Asgarian, 2015, Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach, Urban Ecosyst., 18, 209, 10.1007/s11252-014-0387-7

Lin, 2015, Calculating cooling extents of green parks using remote sensing: Method and test, Landsc. Urban Plan., 134, 66, 10.1016/j.landurbplan.2014.10.012

Alavipanah, 2015, The role of vegetation in mitigating urban land surface temperatures: A case study of Munich, Germany during the warm season, Sustainability, 7, 4689, 10.3390/su7044689

Li, 2012, Spatial pattern of greenspace affects land surface temperature: Evidence from the heavily urbanized Beijing metropolitan area, China, Landsc. Ecol., 27, 887, 10.1007/s10980-012-9731-6

Gage, 2017, Relationships between landscape pattern metrics, vertical structure and surface urban heat island formation in a Colorado suburb, Urban Ecosyst., 20, 1229, 10.1007/s11252-017-0675-0

Adams, 2014, A systematic approach to model the influence of the type and density of vegetation cover on urban heat using remote sensing, Landsc. Urban Plan., 132, 47, 10.1016/j.landurbplan.2014.08.008

Wu, 2014, Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China, Int. J. Appl. Earth Obs. Geoinf., 32, 67

Zhang, 2017, Analyzing the impacts of urbanization and seasonal variation on land surface temperature based on subpixel fractional covers using Landsat images, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10, 1344, 10.1109/JSTARS.2016.2608390

Cai, 2018, Do water bodies play an important role in the relationship between urban form and land surface temperature?, Sustain. Cities Soc., 39, 487, 10.1016/j.scs.2018.02.033

Chen, 2014, How many metrics are required to identify the effects of the landscape pattern on land surface temperature?, Ecol. Indic., 45, 424, 10.1016/j.ecolind.2014.05.002

Chen, 2017, Impacts of urban landscape patterns on urban thermal variations in Guangzhou, China, Int. J. Appl. Earth Obs. Geoinf., 54, 65

Du, 2016, Quantifying the multilevel effects of landscape composition and configuration on land surface temperature, Remote Sens. Environ., 178, 84, 10.1016/j.rse.2016.02.063

Li, 2017, On the association between land system architecture and land surface temperatures: Evidence from a desert metropolis-Phoenix, AZ, USA, Landsc. Urban Plan., 163, 107, 10.1016/j.landurbplan.2017.02.009

Zhou, 2017, Effects of the spatial configuration of trees on urban heat mitigation: A comparative study, Remote Sens. Environ., 195, 1, 10.1016/j.rse.2017.03.043

Chen, 2014, Effect of urban green patterns on surface urban cool islands and its seasonal variations, Urban For. Urban Green., 13, 646, 10.1016/j.ufug.2014.07.006

Maimaitiyiming, 2014, Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation, ISPRS J. Photogramm. Remote Sens., 89, 59, 10.1016/j.isprsjprs.2013.12.010

Liu, 2018, Application of partial least squares regression in detecting the important landscape indicators determining urban land surface temperature variation, Landsc. Ecol., 33, 1133, 10.1007/s10980-018-0663-7

Zhang, 2012, Exploring the influence of impervious surface density and shape on urban heat islands in the northeast United States using MODIS and Landsat, Can. J. Remote Sens., 38, 441

Du, 2016, Influences of land cover types, meteorological conditions, anthropogenic heat and urban area on surface urban heat island in the Yangtze River Delta urban agglomeration, Sci. Total Environ., 571, 461, 10.1016/j.scitotenv.2016.07.012

Benas, 2017, Trends of urban surface temperature and heat island characteristics in the Mediterranean, Theor. Appl. Clim., 130, 807, 10.1007/s00704-016-1905-8

Ma, 2016, A hierarchical analysis of the relationship between urban impervious surfaces and land surface temperatures: Spatial scale dependence, temporal variations, and bioclimatic modulation, Landsc. Ecol., 31, 1139, 10.1007/s10980-016-0356-z

Kumar, 2017, Dominant control of agriculture and irrigation on urban heat island in India, Sci. Rep., 7, 14054, 10.1038/s41598-017-14213-2

Shastri, 2017, Flip flop of day-night and summer-winter surface urban heat island intensity in India, Sci. Rep., 7, 40178, 10.1038/srep40178

Schwarz, N., and Manceur, A.M. (2015). Analyzing the influence of urban forms on surface urban heat islands in Europe. J. Urban Plan. Dev., 141.

Cui, Y., Xu, X., Dong, J., and Qin, Y. (2016). Influence of urbanization factors on surface urban heat island intensity: A comparison of countries at different developmental phases. Sustainability, 8.

Lazzarini, 2015, Urban climate modifications in hot desert cities: The role of land cover, local climate, and seasonality, Geophys. Res. Lett., 42, 9980, 10.1002/2015GL066534

Zhou, 2016, Contrasting effects of urbanization and agriculture on surface temperature in Eastern China, J. Geophys. Res. Atmos., 121, 9597, 10.1002/2016JD025359

Zhang, 2008, Study of the relationships between the spatial extent of surface urban heat islands and urban characteristic factors based on Landsat ETM Plus data, Sensors, 8, 7453, 10.3390/s8117453

Fabrizi, 2010, Satellite and ground-based sensors for the urban heat island analysis in the city of Rome, Remote Sens., 2, 1400, 10.3390/rs2051400

Sun, 2015, Comparing surface- and canopy-layer urban heat islands over Beijing using MODIS data, Int. J. Remote Sens., 36, 5448, 10.1080/01431161.2015.1101504

Huang, W., Li, J., Guo, Q., Mansaray, L.R., Li, X., and Huang, J. (2017). A satellite-derived climatological analysis of urban heat island over Shanghai during 2000–2013. Remote. Sens., 9.

Li, 2018, Developing a 1 km resolution daily air temperature dataset for urban and surrounding areas in the conterminous United States, Remote Sens. Environ., 215, 74, 10.1016/j.rse.2018.05.034

Bonafoni, S., Baldinelli, G., Verducci, P., and Presciutti, A. (2017). Remote sensing techniques for urban heating analysis: A case study of sustainable construction at district level. Sustainability, 9.

Zhang, 2014, Birmingham’s air and surface urban heat islands associated with lamb weather types and cloudless anticyclonic conditions, Prog. Phys. Geogr. Earth Environ., 38, 431, 10.1177/0309133314538725

Azevedo, J.A., Chapman, L., and Muller, C.L. (2016). Quantifying the daytime and night-time urban heat island in Birmingham, UK: A comparison of satellite derived land surface temperature and high resolution air temperature observations. Remote Sens., 8.

Li, L., Huang, X., Li, J., and Wen, D. (2017). Quantifying the spatiotemporal trends of canopy layer heat island (CLHI) and its driving factors over Wuhan, China with satellite remote sensing. Remote Sens., 9.

Sheng, 2017, Comparison of the urban heat island intensity quantified by using air temperature and Landsat land surface temperature in Hangzhou, China, Ecol. Indic., 72, 738, 10.1016/j.ecolind.2016.09.009

Becker, 1995, Surface temperature and emissivity at various scales: Definition, measurement and related problems, Remote Sens. Rev., 12, 225, 10.1080/02757259509532286

Sobrino, 2013, Evaluation of the surface urban heat island effect in the city of madrid by thermal remote sensing, Int. J. Remote Sens., 34, 3177, 10.1080/01431161.2012.716548

Hafner, 1999, Urban heat island modeling in conjunction with satellite-derived surface/soil parameters, J. Appl. Meteorol., 38, 448, 10.1175/1520-0450(1999)038<0448:UHIMIC>2.0.CO;2

Hu, 2014, How can we use MODIS land surface temperature to validate long-term urban model simulations?, J. Geophys. Res. Atmos., 119, 3185, 10.1002/2013JD021101

Brines, 2013, Validating satellite-derived land surface temperature with in situ measurements: A public health perspective, Environ. Health Perspect., 121, 925, 10.1289/ehp.1206176

Wan, 2014, New refinements and validation of the Collection-6 MODIS land-surface temperature/emissivity product, Remote Sens. Environ., 140, 36, 10.1016/j.rse.2013.08.027

Gawuc, L., and Struzewska, J. (2016). Impact of MODIS quality control on temporally aggregated urban surface temperature and long-term surface urban heat island intensity. Remote Sens., 8.

Williamson, 2013, Evaluating cloud contamination in clear-sky MODIS Terra daytime land surface temperatures using ground-based meteorology station observations, J. Clim., 26, 1551, 10.1175/JCLI-D-12-00250.1

Li, 2018, Creating a seamless 1 km resolution daily land surface temperature dataset for urban and surrounding areas in the conterminous United States, Remote Sens. Environ., 206, 84, 10.1016/j.rse.2017.12.010

Li, 2013, Synergistic interactions between urban heat islands and heat waves: The impact in cities is larger than the sum of its parts, J. Appl. Meteorol. Clim., 52, 2051, 10.1175/JAMC-D-13-02.1

Hu, 2013, The impact of temporal aggregation of land surface temperature data for surface urban heat island (SUHI) monitoring, Remote Sens. Environ., 134, 162, 10.1016/j.rse.2013.02.022

Huang, 2016, Temporal upscaling of surface urban heat island by incorporating an annual temperature cycle model: A tale of two cities, Remote Sens. Environ., 186, 1, 10.1016/j.rse.2016.08.009

Lai, 2018, Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products, ISPRS J. Photogramm. Remote Sens., 139, 212, 10.1016/j.isprsjprs.2018.03.012

Weng, 2014, Modeling annual parameters of clear-sky land surface temperature variations and evaluating the impact of cloud cover using time series of Landsat TIR data, Remote Sens. Environ., 140, 267, 10.1016/j.rse.2013.09.002

Shen, 2015, Missing information reconstruction of remote sensing data: A technical review, IEEE Geosci. Remote Sens. Mag., 3, 61, 10.1109/MGRS.2015.2441912

Liu, H., and Weng, Q. (2018). Scaling effect of fused ASTER-MODIS land surface temperature in an urban environment. Sensors, 18.

Shen, 2016, Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China, Remote Sens. Environ., 172, 109, 10.1016/j.rse.2015.11.005

Liu, 2016, Quantifying spatial-temporal pattern of urban heat island in Beijing: An improved assessment using land surface temperature (LST) time series observations from Landsat, MODIS, and Chinese new satellite Gaofen-1, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 9, 2028, 10.1109/JSTARS.2015.2513598

Weng, 2014, Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data, Remote Sens. Environ., 145, 55, 10.1016/j.rse.2014.02.003

Crosson, 2012, A daily merged MODIS Aqua–Terra land surface temperature data set for the conterminous United States, Remote Sens. Environ., 119, 315, 10.1016/j.rse.2011.12.019

Fan, 2014, Reconstruction of MODIS land-surface temperature in a flat terrain and fragmented landscape, Int. J. Remote Sens., 35, 7857, 10.1080/01431161.2014.978036

Kilibarda, 2014, Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution, J. Geophys. Res. Atmos., 119, 2294, 10.1002/2013JD020803

Weiss, 2014, An effective approach for gap-filling continental scale remotely sensed time-series, ISPRS J. Photogramm. Remote Sens., 98, 106, 10.1016/j.isprsjprs.2014.10.001

Metz, M., Andreo, V., and Neteler, M. (2017). A new fully gap-free time series of land surface temperature from MODIS LST data. Remote Sens., 9.

Kou, X., Jiang, L., Bo, Y., Yan, S., and Chai, L. (2016). Estimation of land surface temperature through blending MODIS and AMSR-E data with the Bayesian maximum entropy method. Remote Sens., 8.

Duan, 2017, 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, Remote Sens. Environ., 195, 107, 10.1016/j.rse.2017.04.008

Stathopoulou, 2009, Downscaling AVHRR land surface temperatures for improved surface urban heat island intensity estimation, Remote Sens. Environ., 113, 2592, 10.1016/j.rse.2009.07.017

Keramitsoglou, I., Daglis, I.A., Amiridis, V., Chrysoulakis, N., Ceriola, G., Manunta, P., Maiheu, B., De Ridder, K., Lauwaet, D., and Paganini, M. (2012). Evaluation of satellite-derived products for the characterization of the urban thermal environment. J. Appl. Remote Sens., 6.

Song, 2014, The relationships between landscape compositions and land surface temperature: Quantifying their resolution sensitivity with spatial regression models, Landsc. Urban Plan., 123, 145, 10.1016/j.landurbplan.2013.11.014

Sobrino, 2012, Impact of spatial resolution and satellite overpass time on evaluation of the surface urban heat island effects, Remote Sens. Environ., 117, 50, 10.1016/j.rse.2011.04.042

Huang, 2013, Generating high spatiotemporal resolution land surface temperature for urban heat island monitoring, IEEE Geosci. Remote Sens. Lett., 10, 1011, 10.1109/LGRS.2012.2227930

Chudnovsky, 2004, Diurnal thermal behavior of selected urban objects using remote sensing measurements, Energy Build., 36, 1063, 10.1016/j.enbuild.2004.01.052

Nichol, 2009, An emissivity modulation method for spatial enhancement of thermal satellite images in urban heat island analysis, Photogramm. Eng. Remote Sens., 75, 547, 10.14358/PERS.75.5.547

Essa, 2013, Downscaling of thermal images over urban areas using the land surface temperature-impervious percentage relationship, Int. J. Appl. Earth Obs. Geoinf., 23, 95

Weng, 2014, Modeling diurnal land temperature cycles over Los Angeles using downscaled GOES imagery, ISPRS J. Photogramm. Remote Sens., 97, 78, 10.1016/j.isprsjprs.2014.08.009

Sandau, 2010, Small satellites for global coverage: Potential and limits, ISPRS J. Photogramm. Remote Sens., 65, 492, 10.1016/j.isprsjprs.2010.09.003

Yao, 2018, The influence of different data and method on estimating the surface urban heat island intensity, Ecol. Indic., 89, 45, 10.1016/j.ecolind.2018.01.044

Zhou, 2015, The footprint of urban heat island effect in China, Sci. Rep., 5, 11160, 10.1038/srep11160

Stewart, 2012, Local climate zones for urban temperature studies, Bull. Am. Meteorol. Soc., 93, 1879, 10.1175/BAMS-D-11-00019.1

Schneider, 2010, Mapping global urban areas using MODIS 500-m data: New methods and datasets based on ‘urban ecoregions’, Remote Sens. Environ., 114, 1733, 10.1016/j.rse.2010.03.003

Zhou, 2018, A global record of annual urban dynamics (1992–2013) from nighttime lights, Remote Sens. Environ., 219, 206, 10.1016/j.rse.2018.10.015

Tang, 2015, Estimation and validation of land surface temperatures from Chinese second-generation polar-orbit FY-3A VIRR data, Remote Sens., 7, 3250, 10.3390/rs70303250

Rigo, 2006, Validation of satellite observed thermal emission with in-situ measurements over an urban surface, Remote Sens. Environ., 104, 201, 10.1016/j.rse.2006.04.018

Song, 2014, Validation of ASTER surface temperature data with in situ measurements to evaluate heat islands in complex urban areas, Adv. Meteorol., 2014, 620410, 10.1155/2014/620410

Deilami, K., Kamruzzaman, M., and Hayes, J.F. (2016). Correlation or causality between land cover patterns and the urban heat island effect? Evidence from Brisbane, Australia. Remote Sens., 8.

Sun, 2018, A distributed model for quantifying temporal-spatial patterns of anthropogenic heat based on energy consumption, J. Clean. Prod., 170, 601, 10.1016/j.jclepro.2017.09.153

Madanian, 2018, The study of thermal pattern changes using Landsat-derived land surface temperature in the central part of Isfahan province, Sustain. Cities Soc., 39, 650, 10.1016/j.scs.2018.03.018

Wang, 2018, Patterns of land change and their potential impacts on land surface temperature change in Yangon, Myanmar, Sci. Total Environ., 643, 738, 10.1016/j.scitotenv.2018.06.209

Fu, 2016, Consistent land surface temperature data generation from irregularly spaced Landsat imagery, Remote Sens. Environ., 184, 175, 10.1016/j.rse.2016.06.019

Field, C.B. (2014). Climate Change 2014—Impacts, Adaptation and Vulnerability: Regional Aspects, Cambridge University Press.

Center for International Earth Science Information Network—CIESIN—Columbia University (2017). Gridded Population of the World, Version 4 (gpwv4): Population Density, Revision 10.

Zhou, 2018, Administrative-hierarchical urban land expansion in China: Urban agglomeration in the Yangtze River Delta, J. Urban Plan. Dev., 144, 05018018, 10.1061/(ASCE)UP.1943-5444.0000480

Stewart, 2014, Evaluation of the ‘local climate zone’ scheme using temperature observations and model simulations, Int. J. Clim., 34, 1062, 10.1002/joc.3746

Hu, 2015, A new perspective to assess the urban heat island through remotely sensed atmospheric profiles, Remote Sens. Environ., 158, 393, 10.1016/j.rse.2014.10.022

Bonafoni, S., and Keeratikasikorn, C. (2018). Land surface temperature and urban density: Multiyear modeling and relationship analysis using MODIS and Landsat data. Remote Sens., 10.

Qiao, 2014, Influences of urban expansion on urban heat island in Beijing during 1989–2010, Adv. Meteorol., 2014, 1, 10.1155/2014/187169

Lo, 2003, Land-use and land-cover change, urban heat island phenomenon, and health implications, Photogramm. Eng. Remote Sens., 69, 1053, 10.14358/PERS.69.9.1053

Amiri, 2009, Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran, Remote Sens. Environ., 113, 2606, 10.1016/j.rse.2009.07.021

Jiang, 2015, Assessing the impacts of urbanization-associated land use/cover change on land surface temperature and surface moisture: A case study in the midwestern United States, Remote Sens., 7, 4880, 10.3390/rs70404880

Barat, 2018, Characteristics of surface urban heat island (SUHI) over the gangetic plain of Bihar, India, Asia-Pac. J. Atmos. Sci., 54, 205, 10.1007/s13143-018-0004-4

Keeratikasikorn, C., and Bonafoni, S. (2018). Satellite images and Gaussian parameterization for an extensive analysis of urban heat islands in Thailand. Remote Sens., 10.

Quan, 2018, An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes, Remote Sens. Environ., 206, 403, 10.1016/j.rse.2017.12.003

Cao, 1997, Understanding the scale and resolution effects in remote sensing and GIS, Scale Remote Sens. GIS, 57, 72

Liu, 2009, Scaling effect on the relationship between landscape pattern and land surface temperature: A case study of Indianapolis, United States, Photogramm. Eng. Remote Sens., 75, 291, 10.14358/PERS.75.3.291

Zhang, 2009, Scaling of impervious surface area and vegetation as indicators to urban land surface temperature using satellite data, Int. J. Remote Sens., 30, 841, 10.1080/01431160802395219

Li, 2010, Investigating spatial non-stationary and scale-dependent relationships between urban surface temperature and environmental factors using geographically weighted regression, Environ. Model. Softw., 25, 1789, 10.1016/j.envsoft.2010.06.011

Luo, 2014, Scale effect analysis of the relationships between urban heat island and impact factors: Case study in Chongqing, J. Appl. Remote Sens., 8, 084995, 10.1117/1.JRS.8.084995

Ferguson, G., and Woodbury, A.D. (2007). Urban heat island in the subsurface. Geophys. Res. Lett., 34.

Zhan, 2014, Satellite-derived subsurface urban heat island, Environ. Sci. Technol., 48, 12134, 10.1021/es5021185

Huang, 2009, Detecting urbanization effects on surface and subsurface thermal environment—A case study of Osaka, Sci. Total Environ., 407, 3142, 10.1016/j.scitotenv.2008.04.019

Shi, 2012, Observation and analysis of the urban heat island effect on soil in Nanjing, China, Environ. Earth Sci., 67, 215, 10.1007/s12665-011-1501-2

Menberg, 2013, Subsurface urban heat islands in German Cities, Sci. Total Environ., 442, 123, 10.1016/j.scitotenv.2012.10.043

Qiao, Z., Zhang, D., Xu, X., and Liu, L. (2018). Robustness of satellite-derived land surface parameters to urban land surface temperature. Int. J. Remote Sens., 1–17.

Tu, 2016, Surface urban heat island effect and its relationship with urban expansion in Nanjing, China, J. Appl. Remote Sens., 10, 026037, 10.1117/1.JRS.10.026037

Meng, 2013, Remote-sensing image-based analysis of the patterns of urban heat islands in rapidly urbanizing Jinan, China, Int. J. Remote Sens., 34, 8838, 10.1080/01431161.2013.853895

Kamruzzaman, 2018, Investigating the urban heat island effect of transit oriented development in Brisbane, J. Transp. Geogr., 66, 116, 10.1016/j.jtrangeo.2017.11.016

Thông tin
Thông tin xuất bản

Remote Sensing

Tập 11 Số 1

48

Thông tin tác giả