Abstract
Rapid urbanization has led to an increase in urban land surface temperature (LST). In contrast to individual cities or megacity scale, urban agglomeration can increase LST in a continuous area due to decreasing or disappearing distance between cities. Thus, the impact of ISA on LST needs further understanding in the large scale of urban agglomerations. This study investigated the impacts of impervious surface area (ISA) on LST in urban agglomeration region. The distribution of ISA and LST of the Greater Pearl River Delta in 2015 was extracted using the Landsat 8 OLI and Aqua MODIS images. Next, the standard deviational ellipse methods were used to systematically analyze the spatial correlation of ISA and LST. Subsequently, the influences of ISA density and landscape pattern of ISA on LST were analyzed by various methods. The results showed that when the ISA density increased 10%, the daytime LST increased 0.46 °C at the density level lower than 70% and 0.55 °C at the density level higher than 70%, respectively. Likewise, when the ISA density increased 10%, the nighttime LST increased 0.285 °C at the density level lower than 70% and 0.39 °C at the density level higher than 70%, respectively. In addition, the results of correlation analysis indicated that landscape metrics of ISA and the density of ISA had significant correlation with the LST. However, the correlation was higher at daytime than at nighttime, due to the large terrain, complex environment and diverse surface cover types in the study area.
Similar content being viewed by others
References
Alberti, M. (2005). The effects of urban patterns on ecosystem function. International Regional Science Review, 28(2), 168–192.
Chen, L., & Sun, R. (2013). Eco-environmental effects of urban landscape pattern changes: Progresses, problems, and perspectives. Acta Ecologica Sinica, 33(4), 1042–1050.
Chen, S., & Wang, T. (2009). Comparison analyses of equal interval method and mean-standard deviation method used to delimitate urban heat island. Journal of Geo-information Science, 2, 001.
Du, H., Wang, D., Wang, Y., Zhao, X., Qin, F., Jiang, H., et al. (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. Science of the Total Environment, 571, 461–470.
Estoque, R. C., Murayama, Y., & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349.
Fang, C. (2015). Important progress and future direction of studies on China’s urban agglomerations. Journal of Geographical Sciences, 25(8), 1003–1024.
Fischer, M. M. (2010). Handbook of Applied Spatial Analysis. Journal of Geographical Systems, 10(2), 109–139.
Gong, J. (2002). Clarifying the standard deviational ellipse. Geographical Analysis, 34(2), 155–167.
Gong, A. D., Chen, Y. H., Jing, L. I., & Hua-Lang, H. U. (2007). Study on relationship between urban heat island and urban land use and cover change in Beijing. Journal of Image and Graphics, 12, 1476–1482.
Gustafson, E. J. (1998). Quantifying landscape spatial pattern: What is the state of the art? Ecosystems, 1(2), 143–156.
Huang, J., Zhao, X., Tang, L., & Qiu, Q. (2012). Analysis on spatiotemporal changes of urban thermal landscape pattern in the context of urbanisation: A case study of Xiamen City. Shengtai Xuebao/Acta Ecologica Sinica, 32(2), 622–631.
Jiang, X. D. (2007). Spatial characteristics and dynamic simulations of urban heat environment of cities in Pearl River Delta. Acta Ecologica Sinica, 27(4), 1461–1470.
Jun Xiang, L. I., Wang, Y. J., Shen, X. H., & Song, Y. C. (2004). Landscape pattern analysis along an urban-rural gradient in the Shanghai metropolitan region. Acta Ecologica Sinica, 24(9), 1973–1980.
Kaloustian, N., & Diab, Y. (2015). Effects of urbanization on the urban heat island in Beirut. Urban Climate, 14, 154–165.
Kittler, J., & Illingworth, J. (1986). Minimum error thresholding. Pattern Recognition, 19(1), 41–47.
Lefever, D. W. (1926). Measuring geographic concentration by means of the standard deviational ellipse. American Journal of Sociology, 32(1), 88–94.
Li, J., Song, C., Cao, L., Zhu, F., Meng, X., & Wu, J. (2011). Impacts of landscape structure on surface urban heat islands: A case study of Shanghai. China. Remote Sensing of Environment, 115(12), 3249–3263.
Li, X., Zhou, W., Ouyang, Z., & Zheng, H. (2012). Spatial pattern of greenspace affects land surface temperature: Evidence from the heavily urbanized Beijing metropolitan area, China. Landscape Ecology, 27(6), 887–898.
Li, X., Zhou, W., & Ouyang, Z. (2013). Relationship between land surface temperature and spatial pattern of greenspace: What are the effects of spatial resolution? Landscape and Urban Planning, 114(8), 1–8.
Liu, Y., Peng, J., & Wang, Y. (2017). Relationship between urban heat island and landscape patterns: From city size and landscape composition to spatial configuration. Acta Ecologica Sinica, 37(23), 1–12.
Lo, C. P., Quattrochi, D. A., & Luvall, J. C. (1997). Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing, 18(2), 287–304.
McGarigal, K., & Marks, B. J. (1995). FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure. In Genetics Technical Report PNW-GTR-351. Portland, OR: US Department of Agriculture, Forest Service, Pacific Northwest Research Station.
McGarigal, K., Cushman, S. A., Neel, M. C., & Ene, E. (2002). Fragstats: spatial pattern analysis program for categorical maps. https://www.umass.edu/landeco/research/fragstats/fragstats.html.
Morabito, M., Crisci, A., Messeri, A., Orlandini, S., Raschi, A., Maracchi, G., et al. (2016). The impact of built-up surfaces on land surface temperatures in Italian urban areas. Science of the Total Environment, 551–552, 317–326.
Noro, M., & Lazzarin, R. (2015). Urban heat island in Padua, Italy: Simulation analysis and mitigation strategies. Urban Climate, 14(2), 187–196.
Peng, J., Liu, Y., Shen, H., Xie, P., Xiaoxu, H. U., & Wang, Y. (2016a). Using impervious surfaces to detect urban expansion in Beijing of China in 2000s. Chinese Geographical Science, 26(2), 229–243.
Peng, J., Xie, P., Liu, Y., & Ma, J. (2016b). Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region. Remote Sensing of Environment, 173, 145–155.
Rao, S., Zhang, H. Y., Jin, T. T., & Dou, H. Y. (2010). The spatial character of regional heat island in Pearl River Delta using MODIS remote sensing data. Geographical Research, 29(1), 127–136.
Rondeaux, G., Steven, M., & Baret, F. (1996). Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55(2), 95–107.
Roy, D. P., Wulder, M. A., Loveland, T. R., Woodcock, C. E., Allen, R. G., Anderson, M. C., et al. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145(145), 154–172.
Runpeng, Z. (2013). Zhujiang delta spatial reorganization for new urbanization development. Planners, 29(4), 27–31.
Science (2016). Rise of the City. Science, 352(6288), 906. https://doi.org/10.1126/science.352.6288.906.
Sun, R. (2012). How can urban water bodies be designed for climate adaptation? Landscape and Urban Planning, 105(1–2), 27–33.
Sungzoon, C., Robert, H., & Seungku, Y. (1989). Improvement of kittler and illingworth’s minimum error thresholding. Pattern Recognition, 22(5), 609–617.
Turner, M. G. (2005). Landscape ecology: What is the state of the science? Annual Review of Ecology Evolution and Systematics, 36(36), 319–344.
Urban Agglomeration in the Pearl River Delta Yearbook (2016). (Vol. 2016). Guangzhou: Fangzhi Publishing House.
Wan, Z. (2008). New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote Sensing of Environment, 112(1), 59–74.
Wan, Z., & Dozier, J. (1996). A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Transactions on Geoscience and Remote Sensing, 34(4), 892–905.
Weng, Q., & Lu, D. (2008). A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States. International Journal of Applied Earth Observation and Geoinformation, 10(1), 68–83.
Weng, Q., Lu, D., & Schubring, J. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467–483.
Weng, Q., Liu, H., & Lu, D. (2007). Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis. United States. Urban Ecosystems, 10(2), 203–219.
Wong, D. S. (1999). Several fundamentals in implementing spatial statistics in GIS: Using centrographic measures as examples. Geographic Information Sciences, 5(2), 163–174.
Wu, C. (2004). Normalized spectral mixture analysis for monitoring urban composition using ETM + imagery. Remote Sensing of Environment, 93(4), 480–492.
Xian, G., & Crane, M. (2006). An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data. Remote Sensing of Environment, 104(2), 147–156.
Xu, H. (2009). Quantitative analysis on the relationship of urban impervious surface with other components of the urban ecosystem. Acta Ecologica Sinica, 29(5), 2456–2462.
Xu, H. Q. (2010). Analysis of impervious surface and its impact on urban heat environment using the normalized difference impervious surface index (NDISI). Photogrammetric Engineering and Remote Sensing, 76(5), 557–565.
Xu, H., & Chen, B. (2003). An image processing technique for the study of urban heat island changes using different seasonal remote sensing data. Remote Sensing Technology and Application, 18(3), 129–133.
Xu, S., Li, F. X., & Zhang, L. (2015). Spatiotemporal change of thermal environment landscape pattern in Changsha. Acta Ecologica Sinica, 35, 3743–3754.
Yue, W. Z., & Li-Hua, X. U. (2007). Thermal environment effect of urban land use type and pattern—A case study of central area of Shanghai City. Scientia Geographica Sinica, 27(2), 243–248.
Zhang, J. (2006). Thermal environment detection in the Pearl River Delta Area by remote sensing and analysis of its spatial and temporal evolutions. Ph. D. Dissertation, Guangzhou: Guangzhou Institute of Geochemistry, Chinese Academy of Sciences.
Zhang, Y., Yu, T., Gu, X., Zhang, Y., & Chen, L. (2006). Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heat island effect. Journal of Remote Sensing, 10(5), 789.
Zhang, L., Weng, Q., & Shao, Z. (2017a). An evaluation of monthly impervious surface dynamics by fusing Landsat and MODIS time series in the Pearl River Delta, China, from 2000 to 2015. Remote Sensing of Environment, 201(11), 99–114.
Zhang, S., Liu, Y., & Huang, H. (2017b). Research on quantitative evaluations and spatial and temporal distribution of heat islands for the Pearl River Delta agglomeration. Ecology and Environmental Sciences, 26(7), 1157–1166.
Zhang, S., Yang, K., Li, M., Ma, Y., & Sun, M. (2018). Combinational Biophysical Composition Index (CBCI) for effective mapping biophysical composition in urban areas. IEEE Access, 6, 41224–41237.
Zhao, Z.-Q., He, B.-J., Li, L.-G., Wang, H.-B., & Darko, A. (2017). Profile and concentric zonal analysis of relationships between land use/land cover and land surface temperature: Case study of Shenyang, China. Energy and Buildings, 155, 282–295.
Zheng, T., Lau, K. L., & Ng, E. (2016). Urban tree design approaches for mitigating daytime urban heat island effects in a high-density urban environment. Energy and Buildings, 114, 265–274.
Zhou, W., Huang, G., & Cadenasso, M. L. (2011). 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.
Zhou, D., Dan, L., Ge, S., Zhang, L., Liu, Y., & Lu, H. (2016). Contrasting effects of urbanization and agriculture on surface temperature in eastern China. Journal of Geophysical Research Atmospheres, 121(16), 9597–9606.
Zhou, D., Bonafoni, S., Zhang, L., & Wang, R. (2018). Remote sensing of the urban heat island effect in a highly populated urban agglomeration area in East China. Science of the Total Environment, 628–629, 415–429.
Acknowledgements
The authors would like to thank the anonymous reviewers and editor for constructive comments and suggestions.
Funding
This work was supported by the Yunnan Normal University Postgraduate Innovation Fund [Grant Number yjs201680], Yunnan Provincial Department of Education Research Fund [Grant Number 2011Y307], National Natural Science Foundation of China [Grant Number 41461038], Yunnan Provincial Science and Technology Project [Grant Number 2011XX2005] and Specialized Research Fund for the Doctoral Program of Higher Education [Grant Number 20115303110002].
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
No potential conflict of interest was reported by the authors.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Ma, Y., Yang, K., Zhang, S. et al. Impacts of Large-Area Impervious Surfaces on Regional Land Surface Temperature in the Great Pearl River Delta, China. J Indian Soc Remote Sens 47, 1831–1845 (2019). https://doi.org/10.1007/s12524-019-01023-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-019-01023-4