Abstract
This paper investigates the urban heat island (UHI) characteristics of Shanghai, China, during 1981–2010 using Landsat thematic mapper/multispectral scanner and moderate-resolution imaging spectroradiometer satellite data from the perspectives of time and space, with further analysis of the landscape pattern, the urban heat island effect ratio, and formative factors. The results show the following: (1) From the interannual variation, the secondary-medium temperature area and the medium temperature area are the main bodies of Shanghai UHI, accounting for 67.16–83.69 % of the total area, and have a rising trend over time. (2) From the landscape pattern, the secondary-medium temperature area and the medium temperature area have a dominant position over the whole UHI landscape pattern of Shanghai; the relatively high-temperature area gradually decreases, and its dominance over the whole UHI landscape pattern declines. (3) From the spatial distribution, the pattern in which the urban area initially had complete domination has gradually transformed to become primarily urban area centered and other construction land supplemented with rapid urbanization. Rapid increase of the green land in the urban area has to some extent reduced the UHI characteristics of the Shanghai area in recent years.
Similar content being viewed by others
References
Agam N, Kustas WP, Anderson MC, Li FQ, Neale CMU (2007) A vegetation index based technique for spatial sharpening of thermal imagery. Rem Sens Environ 107:545–558. doi:10.1016/j.rse.2006.10.006
Chen YH, Shi PJ, Li XB, He CY (2002) Research on urban spatial thermal environment using remote sensing image-fractal measurement of thermal field structure and its change. Acta Geod Cartograph Sin 31:322–326
Chen XL, Zhao HM, Li PX, Yin ZY (2006) Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Rem Sens Environ 104:133–146. doi:10.1016/j.rse.2005.11.016
Chen AL, Sun HR, Chen LX (2012) Studies on urban heat island from a landscape pattern view: a review. Acta Ecol Sin 14:4553–4565
Cui LL, Shi J (2012) Urbanization and its environmental effects in Shanghai, China. Urban Climate 2:1–15. doi:10.1016/j.uclim.2012.10.008
Ding LD, Qin ZH, Mao KB (2005) A research of split window algorithm based on MODIS image data and parameter determination. Rem Sens Technol Appl 20:284–289
Jimenez-Munoz JC, Sobrino JA (2003) A generalized single channel method for retrieving land surface temperature from remote sensing data. J Geophys Res 108:4688–4695. doi:10.1029/2003jd003480
Kelarestaghi A, Jeloudar ZJ (2011) Land use/cover change and driving force analyses in parts of northern Iran using RS and GIS techniques. Arab J Geosci 4:401–411. doi:10.1007/s12517-009-0078-5
Li CF, Yin JY (2013) A study on urban thermal field of Shanghai using multi-source remote sensing data. J Indian Soc Remote Accepted. doi:10.1007/s12524-013-0268-1
Li JJ, Wang XR, Wang XJ, Ma WC, Zhang H (2009) Remote sensing evaluation of urban heat island and its spatial pattern of the Shanghai metropolitan area, China. Ecol Complex 6:413–420. doi:10.1016/j.ecocom.2009.02.002
Li CF, Yin JY, Zhao JJ (2010) Study on the relationship between ground bright temperature and land-use types of city based on Landsat image. Int J Environ Sci Dev 3:234–237
Li HX, Song CH, Cao L, Zhu FG, Meng XL, Wu JG (2011) Impacts of landscape structure on surface urban heat islands: a case study of Shanghai, China. Rem Sens Environ 115:3249–3263. doi:10.1016/j.rse.2011.07.008
Mao KB, Qin ZH, Shi JC, Gong P (2005) The research on split-window algorithm on the MODIS. Geo Inform Sci Wuhan Univ 30:703–707
Matori A, Basith A, Harahap ISH (2012) Study of regional monsoonal effects on landslide hazard zonation in Cameron highlands, Malaysia. Arab J Geosci 5:1069–1084. doi:10.1007/s12517-011-0309-4
Pradhan B, Youssef AM (2010) Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arab J Geosci 3:319–326. doi:10.1007/s12517-009-0089-2
Price JC (1990) Using spatial context in satellite data to infer regional scale evapotranspiration. IEEE Trans Geosci Rem Sens 28:940–948. doi:10.1109/36.58983
Qin ZH, Dall'Olmo G, Karnieli A (2001a) Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-AVHRR data. J Geophys Res 106:22655–22670. doi:10.1029/2000jd900452
Qin ZH, Kernieli A, Berliner P (2001b) A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. Int J Rem Sens 22:3719–3746. doi:10.1080/01431160010006971
Rajasekar U, Weng QH (2009) Spatio-temporal modeling and analysis of urban heat islands by using Landsat TM and ETM+ imagery. Int J Rem Sens 30:3531–3548. doi:10.1080/01431160802562289
Sandholt I, Rasmussen K, Andersen J (2002) A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture. Rem Sens Environ 79:213–224. doi:10.1016/s0034-4257(01)00274-7
Srivastava PK, Majumdar TJ, Bhattacharya AK (2010) Study of land surface temperature and spectral emissivity using multi-sensor satellite data. J Earth Syst Sci 119:67–74
Tan JG, Zheng YF, Tang X, Guo CY, Li LP, Song GX, Zhen XR, Yuan D, Kalkstein AJ, Li FR, Chen H (2010) The urban heat island and its impact on heat waves and human health in Shanghai. Int J Biometeorol 54:75–84. doi:10.1007/s00484-009-0256-x
Xiao RB, OUyang ZY, Li WF, Zhang ZM (2005) A review of the eco-environmental consequences of urban heat islands. Acta Ecol Sin 25:2055–2060
Xu HQ, Chen BQ (2004) Remote sensing of the urban heat island and its changes in Xiamen City of SE China. J Environ Sci 16:276–281
Yin ZE, Xu SY (2007) Changes in land-use and land-cover and their effect on eco-environment in Pudong new area of Shanghai. Resour Environ Yangze Basin 16:430–434
Youssef AM, Pradhan B, Tarabees E (2011) Integrated evaluation of urban development suitability based on remote sensing and GIS techniques: contribution from the analytic hierarchy process. Arab J Geosci 4:463–473. doi:10.1007/s12517-009-0118-1
Yuan F, Bauer ME (2007) Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Rem Sens Environ 106:375–386. doi:10.1016/j.res.2006.09.003
Zha Y, Gao J, Ni S (2003) Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Rem Sens 24:583–594. doi:10.1080/01431160210144570
Acknowledgments
This work was supported by the Project of National Natural Science Foundation of China (no. 41172303). We thank Lan Liu in Shanghai University Press for her contributions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, Cf., Shen, D., Dong, Js. et al. Monitoring of urban heat island in Shanghai, China, from 1981 to 2010 with satellite data. Arab J Geosci 7, 3961–3971 (2014). https://doi.org/10.1007/s12517-013-1053-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12517-013-1053-8