Advances in environmental research

  • 제9권1호
  • /
  • Pages.19-39
  • /
  • 2020
  • /
  • 2234-1722(pISSN)
  • /
  • 2234-1730(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Monitoring and spatio-temporal analysis of UHI effect for Mansa district of Punjab, India

  • Kaur, Rajveer (Department of Environmental Sciences and Technology, Central University of Punjab) ;
  • Pandey, Puneeta (Department of Environmental Sciences and Technology, Central University of Punjab)
  • 투고 : 2019.11.15
  • 심사 : 2020.03.17
  • 발행 : 2020.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

Urban heat island (UHI) is one of the most important climatic implications of urbanization and thus a matter of key concern for environmentalists of the world in the twenty-first century. The relationship between climate and urbanization has been better understood with the introduction of thermal remote sensing. So, this study is an attempt to understand the influence of urbanization on local temperature for a small developing city. The study focuses on the investigation of intensity of atmospheric and surface urban heat island for a small urbanizing district of Punjab, India. Landsat 8 OLI/TIRS satellite data and field observations were used to examine the spatial pattern of surface and atmospheric UHI effect respectively, for the month of April, 2018. The satellite data has been used to cover the larger geographical area while field observations were taken for simultaneous and daily temperature measurements for different land use types. The significant influence of land use/land cover (LULC) patterns on UHI effect was analyzed using normalized built-up and vegetation indices (NDBI, NDVI) that were derived from remote sensing satellite data. The statistical analysis carried out for land surface temperature (LST) and LULC indicators displayed negative correlation for LST and NDVI while NDBI and LST exhibited positive correlation depicting attenuation in UHI effect by abundant vegetation. The comparison of remote sensing and in-situ observations were also carried out in the study. The research concluded in finding both nocturnal and daytime UHI effect based on diurnal air temperature observations. The study recommends the urgent need to explore and impose effective UHI mitigation measures for the sustainable urban growth.

키워드

참고문헌

  1. Adams, M.P. and Smith, P.L. (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, 47-54. https://doi.org/10.1016/j.landurbplan.2014.08.008.
  2. Alonso, M.S., Labajo, J.L. and Fidalgo, M.R. (2003), "Characteristics of the urban heat island in the city of Salamanca, Spain", Atmosfera, 16(3), 137-148.
  3. Artis, D.A. and Carnahan, W.H. (1982), "Survey of emissivity variability in thermography of urban areas", Remote Sens. Environ., 12(4), 313-329. https://doi.org/10.1016/0034-4257(82)90043-8.
  4. Azevedo, J., Chapman, L. and Muller, C. (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 Sensing, 8(2), 153. https://doi.org/10.3390/rs8020153.
  5. Borbora, J. and Das A.K. (2014), "Summertime urban heat island study for Guwahati city, India", Sustain. Cities Soc., 11, 61-66. https://doi.org/10.1016/j.scs.2013.12.001.
  6. Chakraborty, S.D., Kant, Y. and Mitra, D. (2015), "Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data", J. Environ. Manage., 148, 143-152. https://doi.org/10.1016/j.jenvman.2013.11.034.
  7. Chen, X.L., Zhao, H.M., Li, P.X. and Yin, Z.Y. (2006), "Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes", Remote Sens. Environ., 104(2), 133- 146. https://doi.org/10.1016/j.rse.2005.11.016.
  8. Cheng, C., Cai, Z., Yan, W., Li, H.Y., Meng, W.Q., Hao, C. and Mo, X.Q. (2010), "Study of temporal and spatial variation of urban heat island based on Landsat TM in central city and binhai new area of Tianjin", J. Nat. Resour., 25(10), 1727-1737.
  9. dos Santos, A.R., de Oliveira, F.S., da Silva, A.G., Gleriani, J.M., Goncalves, W., Moreira, G.L., Silva, F.G., Branco, E.R.F., Moura, M.M., da Silva, R.G. and Juvanhol, R.S. (2017), "Spatial and temporal distribution of urban heat islands", Sci. Total Environ., 605-606, 946-956. http://dx.doi.org/10.1016/j.scitotenv.2017.05.275.
  10. Eliasson, I. (1994), "Urban-suburban-rural air temperature differences related to street geometry", Phys. Geograph., 15(1), 1-22. https://doi.org/10.1080/02723646.1994.10642501
  11. EPA (2009), Heat Island Effect, http://www.epa.gov/heatisland/about/index.htm.
  12. Farina, A. (2012), "Exploring the relationship between land surface temperature and vegetation abundance for urban heat island mitigation in Seville, Spain", LUMA-GIS Thesis.
  13. Fung, W.Y., Lam, K.S., Nichol, J. and Wong, M.S. (2009), "Derivation of nighttime urban air temperatures using a satellite thermal image", J. Appl. Meteorol. Clim., 48(4), 863-872. https://doi.org/10.1175/2008JAMC2001.1.
  14. Gallo, K.P. and Owen, T.W. (1999), "Satellite-based adjustments for the urban heat island temperature bias", J. Appl. Meteorol., 38(6), 806-813. https://doi.org/10.1175/1520-0450(1999)038<0806:SBAFTU>2.0.CO;2
  15. Gallo, K.P., McNab, A.L., Karl, T.R., Brown, J.F., Hood, J.J. and Tarpley, J.D. (1993), "The use of a vegetation index for assessment of the urban heat island effect", Remote Sens., 14(11), 2223-2230. https://doi.org/10.1080/01431169308954031
  16. Gedzelman, S.D., Austin, S., Cermak, R., Stefano, N., Partridge, S., Quesenberry, S. and Robinson, D.A. (2003), "Mesoscale aspects of the urban heat island around New York City", Theor. Appl. Climatol., 75(1), 29-42. https://doi.org/10.1007/s00704-002-0724-2.
  17. Giridharan, R., Ganesan, S. and Lau, S.S.Y. (2004), "Daytime urban heat island effect in high-rise and highdensity residential developments in Hong Kong", Energy Build., 36(6), 525-534. https://doi.org/10.1016/j.enbuild.2003.12.016.
  18. Gober, P., Brazel, A., Quay, R., Myint, S., Grossman-Clarke, S., Miller, A. and Rossi, S. (2009), "Using watered landscapes to manipulate urban heat island effects: how much water will it take to cool Phoenix?", J. Amer. Plan. Assoc., 76(1), 109-121. https://doi.org/10.1080/01944360903433113.
  19. Grimm, N.B., Faeth, S.H., Golubiewski, N.E., Redman, C.L., Wu, J., Bai, X. and Briggs, J.M. (2008), "Global change and the ecology of cities", Science, 319(5864), 756-760. https://doi.org/10.1126/science.1150195.
  20. Habert, G. and Schlueter, A. (2016), Expanding Boundaries: Systems Thinking in the Built Environment: Sustainable Built Environment (SBE) Regional Conference Zurich 2016. vdfHochschulverlag AG.
  21. Han, S., Bian, H., Tie, X., Xie, Y., Sun, M. and Liu, A. (2009), "Impact of nocturnal planetary boundary layer on urban air pollutants: Measurements from a 250-m tower over Tianjin, China", J. Hazard. Mater., 162(1), 264-269. https://doi.org/10.1016/j.jhazmat.2008.05.056.
  22. Imhoff, M.L., Zhang, P., Wolfe, R.E. and Bounoua, L. (2010), "Remote sensing of the urban heat island effect across biomes in the continental USA", Remote Sens. Environ., 114(3), 504-513. https://doi.org/10.1016/j.rse.2009.10.008.
  23. Julien, Y., Sobrino, J.A., Mattar, C., Ruescas, A.B., Jimenez-Munoz, J.C., Soria, G., Hidalgo, V., Atitar, M., Franch, B. and Cuenca, J. (2011), "Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001", Int. J. Remote Sens., 32(7), 2057-2068. https://doi.org/10.1080/01431161003762363.
  24. Karl, T.R., Diaz, H.F. and Kukla, G. (1988), "Urbanization: Its detection and effect in the United States climate record", J. Climate, 1(11), 1099-1123. https://doi.org/10.1175/1520-0442(1988)001<1099:UIDAEI>2.0.CO;2
  25. Kikon, N., Singh, P., Singh, S.K. and Vyas, A. (2016), "Assessment of urban heat islands (UHI) of Noida City, India using multi-temporal satellite data", Sustain. Cities Soc., 22, 19-28. https://doi.org/10.1016/j.scs.2016.01.005.
  26. Kim, Y.H. and Baik, J.J. (2004), "Daily maximum urban heat island intensity in large cities of Korea", Theor. Appl. Climatol.,79(3-4), 151-164.https://doi.org/10.1007/s00704-004-0070-7.
  27. Kim, Y.H. and Baik, J.J. (2005), "Spatial and temporal structure of the urban heat island in Seoul", J. Appl. Meteorol., 44, 591-605. https://doi.org/10.1175/JAM2226.1.
  28. Klok, L., Zwart, S., Verhagen, H. and Mauri, E. (2012), "The surface heat island of Rotterdam and its relationship with urban surface characteristics", Resour. Conserv. Recycling, 64, 23-29. https://doi.org/10.1016/j.resconrec.2012.01.009.
  29. Kolokotroni, M. and Giridharan, R. (2008), "Urban heat island intensity in London: An investigation of the impact of physical characteristics on changes in outdoor air temperature during summer", Solar Energy, 82(11), 986-998. https://doi.org/10.1016/j.solener.2008.05.004.
  30. Kovats, R.S. and Hajat, S. (2008), "Heat stress and public health: a critical review", Ann. Rev. Public Health, 29, 41-55. https://doi.org/10.1146/annurev.publhealth.29.020907.090843.
  31. Kuang, W., Liu, Y., Dou, Y., Chi, W., Chen, G., Gao, C., Yang, T., Liu, J. and Zhang, R. (2015), "What are hot and what are not in an urban landscape: Quantifying and explaining the land surface temperature pattern in Beijing, China", Landscape Ecol., 30(2), 357-373. https://doi.org/10.1007/s10980-014-0128-6.
  32. Kumari, B., Tayyab, M., Mallick, J., Khan, M.F. and Rahman, A. (2018), "Satellite-driven land surface temperature (LST) using Landsat 5, 7 (TM/ETM+ SLC) and Landsat 8 (OLI/TIRS) data and its association with built-up and green cover over urban Delhi, India", Remote Sen. Earth Syst. Sci., 1(3-4), 63-78. https://doi.org/10.1007/s41976-018-0004-2.
  33. Lam, K.S., Wang, T.J., Wu, C.L. and Li, Y.S. (2005), "Study on an ozone episode in hot season in Hong Kong and transboundary air pollution over Pearl River Delta region of China", Atmosph. Environ., 39(11), 1967-1977. https://doi.org/10.1016/j.atmosenv.2004.11.023.
  34. Landsberg, H.E. (1981), The Urban Climate (Vol. 28), Academic Press.
  35. Lemonsu, A., Viguie, V., Daniel, M. and Masson, V. (2015), "Vulnerability to heat waves: Impact of urban expansion scenarios on urban heat island and heat stress in Paris (France)", Urban Climate, 14, 586-605. https://doi.org/10.1016/j.uclim.2015.10.007.
  36. Li, W., Bai, Y., Chen, Q., He, K., Ji, X. and Han, C. (2014), "Discrepant impacts of land use and land cover on urban heat islands: A case study of Shanghai, China", Ecol. Indicators, 47, 171-178. https://doi.org/10.1016/j.ecolind.2014.08.015.
  37. Liang, B. and Weng, Q. (2008), "Multiscale analysis of census-based land surface temperature variations and determinants in Indianapolis, United States", J. Urban Plan. Dev., 134(3), 129-139. https://doi.org/10.1061/(ASCE)0733-9488(2008)134:3(129).
  38. Liu, L. and Zhang, Y. (2011), "Urban heat island analysis using the Landsat TM data and ASTER data: A case study in Hong Kong", Remote Sens., 3(7), 1535-1552.http://dx.doi.org/10. 3390/rs3071535. https://doi.org/10.3390/rs3071535
  39. Lo, C.P. and Quattrochi, D.A. (2003), "Land-use and land-cover change, urban heat island phenomenon, and health implications", Photogram. Eng. Remote Sens., 69(9), 1053-1063. https://doi.org/10.14358/PERS.69.9.1053.
  40. Lu, Y., Feng, P., Shen, C. and Sun, J. (2009), "Urban heat island in summer of Nanjing based on TM data", Proceedings of the 2009 Joint Urban Remote Sensing Event, Shanghai, China, May.
  41. Mallick, J. (2014), "Land characterization analysis of surface temperature of semi-arid mountainous city Abha, Saudi Arabia using remote sensing and GIS", J. Geograph. Inform. Syst., 6(06), 664. https://doi.org/10.4236/jgis.2014.66055.
  42. Mallick, J., Kant, Y. and Bharath, B.D. (2008), "Estimation of land surface temperature over Delhi using Landsat-7 ETM+", J. Ind. Geophys. Union, 12(3), 131-140.
  43. Markham, B.L., Storey, J.C., Williams, D.L. and Irons, J.R. (2004), "Landsat sensor performance: history and current status", IEEE T. Geosci. Remote Sens., 42(12), 2691-2694. https://doi.org/10.1109/TGRS.2004.840720.
  44. Mathew, A., Khandelwal, S. and Kaul, N. (2016), "Spatial and temporal variations of urban heat island effect and the effect of percentage impervious surface area and elevation on land surface temperature: Study of Chandigarh city, India", Sustain. Cities Soc., 26, 264-277. https://doi.org/10.1016/j.scs.2016.06.018.
  45. Mathew, A., Khandelwal, S. and Kaul, N. (2018), "Analysis of diurnal surface temperature variations for the assessment of surface urban heat island effect over Indian cities", Energy Build., 159, 271-295. https://doi.org/10.1016/j.enbuild.2017.10.062
  46. Mohan, M., Kikegawa, Y., Gurjar, B.R., Bhati, S., Kandya, A. and Ogawa, K. (2012), "Urban heat island assessment for a tropical urban airshed in India", Atmosph. Climate Sci., 2(2), 127-138. https://doi.org/10.4236/acs.2012.22014.
  47. Mukherjee, S., Joshi, P.K. and Garg, R.D. (2017), "Analysis of urban built-up areas and surface urban heat island using downscaled MODIS derived land surface temperature data", Geocarto Int., 32(8), 900-918. https://doi.org/10.1080/10106049.2016.1222634.
  48. Nesarikar-Patki, P. and Raykar-Alange, P. (2012), "Study of influence of land cover on urban heat islands in pune using remote", IOSR J. Mech. Civ. Eng., 3, 39-43.
  49. Nichol, J.E. (1996), "High-resolution surface temperature patterns related to urban morphology in a tropical city: A satellite-based study", J. Appl. Meteorol., 35(1), 135-146. https://doi.org/10.1175/1520-0450(1996)035<0135:HRSTPR>2.0.CO;2.
  50. Oke, T.R. (1981), "Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations", J. Climatol., 1(3), 237-254. https://doi.org/10.1002/joc.3370010304.
  51. Oke, T.R. (1982), "The energetic basis of the urban heat island", Quart. J. Royal Meteorol. Soc., 108(455), 1-24. https://doi.org/10.1002/qj.49710845502.
  52. Oke, T.R. (1987), Boundary Layer Climate, 2nd Edition. Routledge, 435.
  53. Pandey, A.K., Singh, S., Berwal, S., Kumar, D., Pandey, P., Prakash, A., Lodhi, N., Maithani, S., Jain, V.K. and Kumar, K. (2014), "Spatio-temporal variations of urban heat island over Delhi", Urban Climate, 10, 119-133. https://doi.org/10.1016/j.uclim.2014.10.005.
  54. Pandey, P., Kumar, D., Prakash, A., Masih, J., Singh, M., Kumar, S., Jain, V.K. and Kumar, K. (2012), "A study of urban heat island and its association with particulate matter during winter months over Delhi", Sci. Total Environ., 414, 494-507. https://doi.org/10.1016/j.scitotenv.2011.10.043 .
  55. PCA (2011), Primary Census Abstract, in District Census Handbook Mansa, Series-04, PART XII-B, Census of India 2011, Punjab, India.
  56. Phiri, D. and Morgenroth, J. (2017), "Developments in Landsat land cover classification methods: A review", Remote Sens., 9(9), 967. https://doi.org/10.3390/rs9090967.
  57. Rajasekar, U. and Weng, Q. (2009), "Spatio-temporal modelling and analysis of urban heat islands by using Landsat TM and ETM+ imagery", Int. J. Remote Sens., 30(13), 3531-3548. https://doi.org/10.1080/01431160802562289.
  58. Rajeshwari, A. and Mani, N.D. (2014), "Estimation of land surface temperature of Dindigul district using Landsat 8 data", Int. J. Res. Eng. Technol., 3(5), 122-126. https://doi.org/10.15623/ijret.2014.0305025
  59. Roth, M., Oke, T.R. and Emery, W.J. (1989), "Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology", Int. J. Remote Sens., 10(11), 1699-1720. https://doi.org/10.1080/01431168908904002.
  60. Santamouris, M. (2015), "Regulating the damaged thermostat of the cities-Status, impacts and mitigation challenges", Energy Build., 91, 43-56. https://doi.org/10.1016/j.enbuild.2015.01.027.
  61. Sarrat, C., Lemonsu, A., Masson, V. and Guedalia, D. (2006), "Impact of urban heat island on regional atmospheric pollution", Atmosph. Environ., 40(10), 1743-1758. https://doi.org/10.1016/j.atmosenv.2005.11.037.
  62. Senanayake, I.P., Welivitiya, W.D.D.P. and Nadeeka, P.M. (2013), "Remote sensing based analysis of urban heat islands with vegetation cover in Colombo city, Sri Lanka using Landsat-7 ETM+ data", Urban Climate, 5, 19-35. http://dx.doi.org/10.1016/j. uclim.2013.07.004.
  63. Shastri, H., Barik, B., Ghosh, S., Venkataraman, C. and Sadavarte, P. (2017), "Flip flop of day-night and summer-winter surface urban heat island intensity in India", Sci. Reports, 7(1), 40178. https://doi.org/10.1038/srep40178.
  64. Shastri, H., Paul, S., Ghosh, S. and Karmakar, S. (2015), "Impacts of urbanization on Indian summer monsoon rainfall extremes", J. Geophys. Res. Atmosph., 120(2), 496-516. https://doi.org/10.1002/2014JD022061.
  65. Singh, R., Grover, A. and Zhan, J. (2014), "Inter-seasonal variations of surface temperature in the urbanized environment of Delhi using Landsat thermal data", Energies, 7(3), 1811-1828. https://doi.org/10.3390/en7031811.
  66. Sobrino, J.A., Jimenez-Munoz, J.C. and Paolini, L. (2004), "Land surface temperature retrieval from Landsat TM 5", Remote Sens. Environ., 90, 434-440. https://doi.org/10.1016/j.rse.2004.02.003.
  67. Stathopoulou, M., Cartalis, C. and Petrakis, M. (2007), "Integrating Corine Land Cover data and Landsat TM for surface emissivity definition: application to the urban area of Athens, Greece", Int. J. Remote Sens., 28(15), 3291-3304. https://doi.org/10.1080/01431160600993421.
  68. Steeneveld, G.J., Koopmans, S., Heusinkveld, B.G., Van Hove, L.W.A. and Holtslag, A.A.M. (2011), "Quantifying urban heat island effects and human comfort for cities of variable size and urban morphology in the Netherlands", J. Geophys. Res. Atmosph., 116(D20). https://doi.org/10.1029/2011JD015988.
  69. Stewart, I.D. (2011), "A systematic review and scientific critique of methodology in modern urban heat island literature", Int. J. Climatol., 31(2), 200-217. https://doi.org/10.1002/joc.2141.
  70. Streutker, D.R. (2002), "A remote sensing study of the urban heat island of Houston, Texas", Int. J. Remote Sens., 23(13), 2595-2608. http://dx.doi.org/10.1080/01431160110115023.
  71. Sun, Q., Tan, J. and Xu, Y. (2010), "An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta Region in South China", Environ. Earth Sci., 59(5), 1047-1055.https://doi.org/10.1007/s12665-009-0096-3.
  72. Svensson, M.K. (2004), "Sky view factor analysis-implications for urban air temperature differences", Meteorol. Appl., 11(3), 201-211. https://doi.org/10.1017/S1350482704001288.
  73. Taha, H. (1997), "Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat", Energy Build., 25(2), 99-103. https://doi.org/10.1016/S0378-7788(96)00999-1.
  74. Vitousek, P.M., Mooney, H.A., Lubchenco, J. and Melillo, J.M. (1997), "Human domination of Earth's ecosystems", Science, 277(5325), 494-499. https://doi.org/10.1126/science.277.5325.494.
  75. Voogt, J.A. and Oke, T.R. (1998), "Effects of urban surface geometry on remotely-sensed surface temperature", Int. J. Remote Sens., 19(5), 895-920. https://doi.org/10.1080/014311698215784.
  76. Yadav, N., Sharma, C., Peshin, S.K. and Masiwal, R. (2017), "Study of intra-city urban heat island intensity and its influence on atmospheric chemistry and energy consumption in Delhi", Sustain. Cities Soc., 32, 202-211. https://doi.org/10.1016/j.scs.2017.04.003.
  77. Yuan, F. and Bauer, M.E. (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(3), 375-386. https://doi.org/10.1016/j.rse.2006.09.003.
  78. Zha, Y., Gao, J. and NiI, S. (2003), "Use of normalized difference built-up index in automatically mapping urban areas from TM imagery", Int. J. Remote Sens., 24(3), 583-594. http://dx.doi.org/10.1080/01431160304987.
  79. Zhang, H., Qi, Z.F., Ye, X.Y., Cai, Y.B., Ma, W.C. and Chen, M.N. (2013), "Analysis of land use/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China", Appl. Geograph., 44, 121-133. https://doi.org/10.1016/j.apgeog.2013.07.021.