2,317
Views
15
CrossRef citations to date
0
Altmetric
Research Article

Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale

, ORCID Icon, &
Pages 327-340 | Received 03 Sep 2019, Accepted 06 Oct 2020, Published online: 06 Nov 2020

References

  • Aghabozorgi, S., A. S. Shirkhorshidi, and T. Y. Wah. 2015. “Time-series Clustering – A Decade Review.” Information Systems 53: 16–38. doi:10.1016/j.is.2015.04.007.
  • Bonilla, E. V. 2008. “Multi-task Gaussian Process Prediction.” Advances in Neural Information Processing Systems 20: 153–160.
  • Breiman, L. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
  • Chen, A., L. Yao, R. Sun, and L. Chen. 2014. “How Many Metrics are Required to Identify the Effects of the Landscape Pattern on Land Surface Temperature?” Ecological Indicators 45: 424–433. doi:10.1016/j.ecolind.2014.05.002.
  • Chen, Y.-C., H.-W. Chiu, Y.-F. Su, Y.-C. Wu, and K.-S. Cheng. 2017. “Does Urbanization Increase Diurnal Land Surface Temperature Variation? Evidence and Implications.” Landscape and Urban Planning 157: 247–258. doi:10.1016/j.landurbplan.2016.06.014.
  • Dos Santos, A. R., F. S. De Oliveira, A. G. Da Silva, J. M. Gleriani, W. Gonçalves, G. L. Moreira, F. G. Silva, et al. 2017. “Spatial and Temporal Distribution of Urban Heat Islands”. Science of the Total Environment 605–606: 946–956. doi:10.1016/j.scitotenv.2017.05.275.
  • Gong, P., X. Li, and W. Zhang. 2019. “40-Year (1978–2017) Human Settlement Changes in China Reflected by Impervious Surfaces from Satellite Remote Sensing.” Science Bulletin 64 (11): 756–763. doi:10.1016/j.scib.2019.04.024.
  • Hao, P., Z. Niu, Y. Zhan, Y. Wu, L. Wang, and Y. Liu. 2016. “Spatiotemporal Changes of Urban Impervious Surface Area and Land Surface Temperature in Beijing from 1990 to 2014.” GIScience & Remote Sensing 53 (1): 63–84. doi:10.1080/15481603.2015.1095471.
  • Huang, B., and J. Wang. 2020. “Big Spatial Data for Urban and Environmental Sustainability.” Geo-spatial Information Science 23 (2): 125–140. doi:10.1080/10095020.2020.1754138.
  • Huang, Q., J. Huang, X. Yang, C. Fang, and Y. Liang. 2019. “Quantifying the Seasonal Contribution of Coupling Urban Land Use Types on Urban Heat Island Using Land Contribution Index: A Case Study in Wuhan, China.” Sustainable Cities and Society 44: 666–675. doi:10.1016/j.scs.2018.10.016.
  • Koenderink, J. J., and A. J. van Doorn. 1992. “Surface Shape and Curvature Scales.” Image and Vision Computing 10 (8): 557–564. doi:10.1016/0262-8856(92)90076-F.
  • Kuang, W., A. Liu, Y. Dou, G. Li, and D. Lu. 2019. “Examining the Impacts of Urbanization on Surface Radiation Using Landsat Imagery.” GIScience & Remote Sensing 56 (3): 462–484. doi:10.1080/15481603.2018.1508931.
  • Kuang, W., Y. Liu, Y. Dou, W. Chi, G. Chen, C. Gao, T. Yang, J. Liu, and R. Zhang. 2015. “What are Hot and What are Not in an Urban Landscape: Quantifying and Explaining the Land Surface Temperature Pattern in Beijing, China.” Landscape Ecology 30 (2): 357–373. doi:10.1007/s10980-014-0128-6.
  • Kuang, W., Z. Li, and R. Hamdi. 2020. “Comparison of Surface Radiation and Turbulent Heat Fluxes in Olympic Forest Park and on a Building Roof in Beijing, China.” Urban Climate 31: 100562. doi:10.1016/j.uclim.2019.100562.
  • Li, H., Y. Zhou, X. Li, L. Meng, X. Wang, S. Wu, and S. Sodoudi. 2018. “A New Method to Quantify Surface Urban Heat Island Intensity.” Science of the Total Environment 624: 262–272. doi:10.1016/j.scitotenv.2017.11.360.
  • Li, W., Q. Cao, K. Lang, and J. Wu. 2017. “Linking Potential Heat Source and Sink to Urban Heat Island: Heterogeneous Effects of Landscape Pattern on Land Surface Temperature.” Science of the Total Environment 586: 457–465. doi:10.1016/j.scitotenv.2017.01.191.
  • Li, X., and P. Gong. 2016. “An “Exclusion-inclusion” Framework for Extracting Human Settlements in Rapidly Developing Regions of China from Landsat Images.” Remote Sensing of Environment 186: 286–296.
  • Li, X., P. Gong, and L. Liang. 2015. “A 30-year (1984–2013) Record of Annual Urban Dynamics of Beijing City Derived from Landsat Data.” Remote Sensing of Environment 166: 78–90. doi:10.1016/j.rse.2015.06.007.
  • Liu, H., B. Huang, and C. Yang. 2020. “Assessing the Coordination between Economic Growth and Urban Climate Change in China from 2000 to 2015.” Science of the Total Environment 732: 139283. doi:10.1016/j.scitotenv.2020.139283.
  • Liu, H., Q. Zhan, C. Yang, and J. Wang. 2018. “Characterizing the Spatio-temporal Pattern of Land Surface Temperature through Time Series Clustering: Based on the Latent Pattern and Morphology.” Remote Sensing 10 (4): 654. doi:10.3390/rs10040654.
  • Liu, H., Q. Zhan, C. Yang, and J. Wang. 2019b. “The Multi-timescale Temporal Patterns and Dynamics of Land Surface Temperature Using Ensemble Empirical Mode Decomposition.” Science of the Total Environment 652: 243–255. doi:10.1016/j.scitotenv.2018.10.252.
  • Liu, H., Q. Zhan, S. Gao, and C. Yang. 2019a. “Seasonal Variation of the Spatially Non-stationary Association between Land Surface Temperature and Urban Landscape.” Remote Sensing 11 (9): 1016. doi:10.3390/rs11091016.
  • Liu, Y., J. Peng, and Y. Wang. 2017. “Diversification of Land Surface Temperature Change under Urban Landscape Renewal: A Case Study in the Main City of Shenzhen, China.” Remote Sensing 9 (9): 919. doi:10.3390/rs9090919.
  • Mcgarigal, K. 1995. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure. Vol. 351. US Department of Agriculture, Forest Service, Pacific Northwest Research Station.
  • Nistor, -M.-M. 2019. “Vulnerability of Groundwater Resources under Climate Change in the Pannonian Basin.” Geo-spatial Information Science 22 (4): 345–358. doi:10.1080/10095020.2019.1613776.
  • Oke, T. R. 1988. “Street Design and Urban Canopy Layer Climate.” Energy and Buildings 11 (1): 103–113. doi:10.1016/0378-7788(88)90026-6.
  • Qiao, Z., N. Huang, X. Xu, Z. Sun, W. Chen, and J. Yang. 2019. “Spatio-temporal Pattern and Evolution of Urban Land Surface Thermal Landscape in Beijing Metropolitan Area between 2003 and 2017.” (in Chinese) Acta Geographica Sinica 74 (3): 475–489.
  • Rajasekar, U., and Q. Weng. 2009. “Urban Heat Island Monitoring and Analysis Using A Non-parametric Model: A Case Study of Indianapolis.” ISPRS Journal of Photogrammetry and Remote Sensing 64 (1): 86–96. doi:10.1016/j.isprsjprs.2008.05.002.
  • Rasul, A., H. Balzter, and C. Smith. 2015. “Spatial Variation of the Daytime Surface Urban Cool Island during the Dry Season in Erbil, Iraqi Kurdistan, from Landsat 8.” Urban Climate 14: 176–186. doi:10.1016/j.uclim.2015.09.001.
  • Shao, Z., N. S. Sumari, A. Portnov, F. Ujoh, W. Musakwa, and P. J. Mandela. 2020. “Urban Sprawl and Its Impact on Sustainable Urban Development: A Combination of Remote Sensing and Social Media Data.” Geo-spatial Information Science 1–15. doi:10.1080/10095020.2020.1787800.
  • Shen, H., L. Huang, L. Zhang, P. Wu, and C. Zeng. 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 Sensing of Environment 172: 109–125. doi:10.1016/j.rse.2015.11.005.
  • Stewart, I. D., and T. R. Oke. 2012. “Local Climate Zones for Urban Temperature Studies.” Bulletin of the American Meteorological Society 93 (12): 1879–1900.
  • Streutker, D. R. 2003. “Satellite-measured Growth of the Urban Heat Island of Houston, Texas.” Remote Sensing of Environment 85 (3): 282–289. doi:10.1016/S0034-4257(03)00007-5.
  • Tomlinson, C. J., L. Chapman, J. E. Thornes, and C. J. Baker. 2012. “Derivation of Birmingham’s Summer Surface Urban Heat Island from MODIS Satellite Images.” International Journal of Climatology 32 (2): 214–224. doi:10.1002/joc.2261.
  • Trinder, J., and Q. Liu. 2020. “Assessing Environmental Impacts of Urban Growth Using Remote Sensing.” Geo-spatial Information Science 23 (1): 20–39. doi:10.1080/10095020.2019.1710438.
  • Wan, Z. 2008. “New Refinements and Validation of the MODIS Land-Surface Temperature/Emissivity Products.” Remote Sensing of Environment 112 (1): 59–74. doi:10.1016/j.rse.2006.06.026.
  • Wan, Z. 2014. “New Refinements and Validation of the Collection-6 MODIS Land-surface Temperature/emissivity Product.” Remote Sensing of Environment 140: 36–45. doi:10.1016/j.rse.2013.08.027.
  • Wang, J., Q. Zhan, and H. Guo. 2016b. “The Morphology, Dynamics and Potential Hotspots of Land Surface Temperature at a Local Scale in Urban Areas.” Remote Sensing 8 (1): 18. doi:10.3390/rs8010018.
  • Wang, J., Q. Zhan, H. Guo, and Z. Jin. 2016a. “Characterizing the Spatial Dynamics of Land Surface Temperature–impervious Surface Fraction Relationship.” International Journal of Applied Earth Observation and Geoinformation 45: 55–65. doi:10.1016/j.jag.2015.11.006.
  • Wang, Y., Q. Zhan, and W. Ouyang. 2019. “How to Quantify the Relationship between Spatial Distribution of Urban Waterbodies and Land Surface Temperature?” Science of the Total Environment 671: 1–9. doi:10.1016/j.scitotenv.2019.03.377.
  • Warren Liao, T. 2005. “Clustering of Time Series Data—a Survey.” Pattern Recognition 38 (11): 1857–1874. doi:10.1016/j.patcog.2005.01.025.
  • Weng, Q., M. K. Firozjaei, A. Sedighi, M. Kiavarz, and S. K. Alavipanah. 2019. “Statistical Analysis of Surface Urban Heat Island Intensity Variations: A Case Study of Babol City, Iran.” GIScience & Remote Sensing 56 (4): 576–604. doi:10.1080/15481603.2018.1548080.
  • Weng, Q., and P. Fu. 2014a. “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 Sensing of Environment 140: 267–278. doi:10.1016/j.rse.2013.09.002.
  • Weng, Q., and P. Fu. 2014b. “Modeling Diurnal Land Temperature Cycles over Los Angeles Using Downscaled GOES Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 97: 78–88. doi:10.1016/j.isprsjprs.2014.08.009.
  • Xu, J., Y. Zhao, K. Zhong, F. Zhang, X. Liu, and C. Sun. 2018. “Measuring Spatio-temporal Dynamics of Impervious Surface in Guangzhou, China, from 1988 to 2015, Using Time-series Landsat Imagery.” Science of the Total Environment 627: 264–281. doi:10.1016/j.scitotenv.2018.01.155.
  • Yang, C., Q. Zhan, J. Zhang, H. Liu, and Z. Fan. 2018a. “Quantifying the Relationship between Natural and Socioeconomic Factors and with Fine Particulate Matter (PM2.5) Pollution by Integrating Remote Sensing and Geospatial Big Data.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W5: 77–82. doi:10.5194/isprs-archives-XLII-3-W5-77-2018.
  • Yang, C., Q. Zhan, S. Gao, and H. Liu. 2019a. “How Do the Multi-temporal Centroid Trajectories of Urban Heat Island Correspond to Impervious Surface Changes: A Case Study in Wuhan, China.” International Journal of Environmental Research and Public Health 16 (20): 3865. doi:10.3390/ijerph16203865.
  • Yang, C., Q. Zhan, Y. Lv, and H. Liu. 2019b. “Downscaling Land Surface Temperature Using Multiscale Geographically Weighted Regression over Heterogeneous Landscapes in Wuhan, China.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12 (12): 5213–5222. doi:10.1109/JSTARS.2019.2955551.
  • Yang, C., Q. Zhan, Y. Xiao, and H. Liu. 2020. “Identifying the Driving Factors of Population Exposure to Fine Particulate Matter (PM2.5) In Wuhan, China.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020: 355–361. doi:10.5194/isprs-annals-V-3-2020-355-2020.
  • Yang, J., J. Su, J. C. Jin, X. Li, and Q. Ge. 2018b. “The Impact of Spatial Form of Urban Architecture on the Urban Thermal Environment: A Case Study of the Zhongshan District, Dalian, China.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (8): 2709–2716. doi:10.1109/JSTARS.2018.2808469.
  • Yang, J., P. Gong, R. Fu, M. Zhang, J. Chen, S. Liang, B. Xu, J. Shi, and R. Dickinson. 2013. “The Role of Satellite Remote Sensing in Climate Change Studies.” Nature Climate Change 3: 1001. doi:10.1038/nclimate2033.
  • Zhan, Q., Y. Yue, and Y. Xiao. 2018. “Evolution of Built-up Area Expansion and Verification of Planning Implementation in Wuhan, City.” Planning Review 42: 63–71.
  • Zhang, D., X. Liu, X. Wu, Y. Yao, X. Wu, and Y. Chen. 2019. “Multiple Intra-urban Land Use Simulations and Driving Factors Analysis: A Case Study in Huicheng, China.” GIScience & Remote Sensing 56 (2): 282–308.
  • Zhao, B., Y. Zhong, A. Ma, and L. Zhang. 2016. “A Spatial Gaussian Mixture Model for Optical Remote Sensing Image Clustering.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (12): 5748–5759. doi:10.1109/JSTARS.2016.2546918.
  • Zhou, D., J. Xiao, S. Bonafoni, C. Berger, K. Deilami, Y. Zhou, S. Frolking, R. Yao, Z. Qiao, and A. J. Sobrino. 2018. “Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives.” Remote Sensing 11 (1): 48. doi:10.3390/rs11010048.
  • Zhou, J., Y. Chen, J. Wang, and W. Zhan. 2011a. “Maximum Nighttime Urban Heat Island (UHI) Intensity Simulation by Integrating Remotely Sensed Data and Meteorological Observations.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4 (1): 138–146. doi:10.1109/JSTARS.2010.2070871.
  • Zhou, W., G. Huang, and M. L. Cadenasso. 2011b. “Does Spatial Configuration Matter? Understanding the Effects of Land Cover Pattern on Land Surface Temperature in Urban Landscapes.” Landscape and Urban Planning 102 (1): 54–63. doi:10.1016/j.landurbplan.2011.03.009.