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Vegetation changes and formation of small-scale urban heat islands in three populated districts of Kerala State, India

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Currently, more than half of the world’s population is living in cities. Rapid and unplanned urbanization became a common scenario in rapidly developing countries such as those in Asia. Decline in vegetation coverage and increase in local air and land surface temperatures are among the adverse effects of unplanned urban growth. We used Landsat data for the period 1991–2017 to estimate the expansion of urban areas in terms of vegetation loss and the development of small-scale urban heat islands in developing cities in Kerala state of India. For the last 27 years, unplanned urbanization in Kerala state has increased and this resulted in the enhanced loss of vegetation and, possibly, resulted in the increase in land surface temperature (LST). Our results indicate that vegetation coverage, particularly near the urban areas, has been decreased by 5.8%, 10.4%, and 9.6% in Ernakulam, Trichur, and Kozhikode districts, respectively. The land surface temperatures also have been increased during the study period. It is interesting to note that higher increase in LST and higher reduction in vegetation coverage were observed in Trichur and Kozhikode districts compared with highly populated and urbanized Ernakulam district.
Czasopismo
Rocznik
Strony
1063--1072
Opis fizyczny
Bibliogr. 28 poz.
Twórcy
  • Department for Management of Science and Technology Development Ton Duc Thang University Ho Chi Minh City Vietnam
  • Faculty of Environment and Labour Safety Ton Duc Thang University Ho Chi Minh City Vietnam
  • Centro Estadual de Pesquisas em Sensoriamento Remoto e Meteorologia Universidade Federal do Rio Grande do Sul (UFRGS) Porto Alegre Brazil
Bibliografia
  • 1. Carlson TN, Arthur ST (2000) The impact of land use—land cover changes due to urbanization on surface microclimate and hydrology: a satellite perspective. Global Planet Change 25:49–65. https://doi.org/10.1016/S0921-8181(00)00021-7
  • 2. Chen H-W, Cheng K-S (2012) A conceptual model of surface reflectance estimation for satellite remote sensing images using in situ reference data. Remote Sens 4:934–949. https://doi.org/10.3390/rs4040934
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  • 9. Gandhi GM, Parthiban S, Thummalu N, Christy A (2015) NDVI: vegetation change detection using remote sensing and GIS—a case study of Vellore District. Procedia Comput Sci 57:1199–1210. https://doi.org/10.1016/j.procs.2015.07.415
  • 10. Gratani L, Bonito A, Crescente MF, Catoni R, Varone L, Tinelli A (2015) The use of maps as a monitoring tool of protected area management. Rend Lincei 26:325–335. https://doi.org/10.1007/s12210-014-0355-4
  • 11. Grondona AEB, Veettil BK, Rolim SBA (2013) Urban heat island development during the last two decades in Porto Alegre, Brazil, and its monitoring. In: Proceedings of the joint urban remote sensing event (JURSE), Sao Paulo, Brazil, pp 61–64
  • 12. Karunakaran N (2014) Paddy cultivation in Kerala—trends, determinants and effects on food security. Artha J Soc Sci 13:21–36. https://doi.org/10.12724/ajss.31.2
  • 13. Liu L, Zhang Y (2011) Urban heat island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sensing 3:1535–1552. https://doi.org/10.3390/rs3071535
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  • 15. Ranagalage M, Estoque RC, Murayama Y (2014) An urban heat island study of the Colombo metropolitan area, Sri Lanka, based on Landsat data (1997–2017). Int J Geo-Inf 6(7):189. https://doi.org/10.3390/ijgi6070189
  • 16. Senanayake IP, Welivitiya WDDP, Nadeeka PM (2013a) Urban green spaces analysis for development planning in Colombo, Sri Lanka, utilizing THEOS satellite imagery—a remote sensing and GIS approach. Urban For Urban Green 12:307–314. https://doi.org/10.1016/j.ufug.2013.03.011
  • 17. Senanayake IP, Welivitiya WDDP, Nadeeka PM (2013b) Remote sensing based analysis of urban heat islands with vegetation cover in Colombo city, Sri Lanka using Landsat-7 ETM+ data. Urban Clim 5:19–35. https://doi.org/10.1016/j.uclim.2013.07.004
  • 18. Sobrino JA, Jiménez-Muñoz JC, Paolini P (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
  • 19. Son NT, Thanh BX (2018) Decadal assessment of urban sprawl and its effects on local temperature using Landsat data in Cantho city, Vietnam. Sustain Cities Soc 36:81–91. https://doi.org/10.1016/j.scs.2017.10.010
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  • 21. UN (2016) The world’s cities in 2016–data booklet (ST/ESA/SER.A/392). Department of Economic and Social Affairs, Population Division, United Nations, New York, p 29
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  • 23. Veettil BK (2012) A comparative study of urban change detection techniques using high spatial resolution images. In: Proceedings of the geographic object-based image analysis (GEOBIA), Rio de Janeiro, Brazil, pp 29–34
  • 24. Voogt JA, Oke TR (2003) Thermal remote sensing of urban climates. Remote Sens Environ 86:370–384. https://doi.org/10.1016/S0034-4257(03)00079-8
  • 25. Yu X, Guo X, Wu Z (2014) Land surface temperature retrieval from Landsat 8 TIRS—comparison between radiative transfer equation-based method, split window algorithm and single channel method. Remote Sens 6:9829–9852. https://doi.org/10.3390/rs6109829
  • 26. 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. Remote Sens Environ 106:375–386. https://doi.org/10.1016/j.rse.2006.09.003
  • 27. Zachariah KC, Rajan SI (2015) Dynamics of emigration and remittances in Kerala: results from the Kerala Migration Survey 2014. Working Paper No. 463, Centre for Development Studies, Thiruvananthapuram, Kerala, India
  • 28. Zhang Y, Yu T, Gu XF, Chen LF (2006) Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heal island effect. J Remote Sens 10:789–797
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-239842dd-1011-49e8-a31d-5a572d41d475
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