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Original Articles

Spatio-temporal pattern of urban eco-environmental quality of Indian megacities using geo-spatial techniques

ORCID Icon, , &
Pages 5067-5090 | Received 19 Dec 2020, Accepted 01 Mar 2021, Published online: 05 Apr 2021

References

  • Aithal BH, Chandan MC, Nimish G. 2019. Assessing land surface temperature and land use change through spatio-temporal analysis: a case study of select major cities of India. Arab J Geosci 12:367. https://doi.org/10.1007/s12517-019-4547-1.
  • Alam SM, Markandey K. 2020. Consequences of unplanned growth: a case study of metropolitan hyderabad. Urban and regional planning: 20th century forms and 21st century transformations. Urban and Regional Planning and Development, Springer, Cham; p. 203–219.
  • Anselin L, Syabri I, Kho Y. 2006. GeoDa: an introduction to spatial data analysis. Geogr Anal. 38(1):5–22.
  • As-Syakur AR, Adnyana IWS, Arthana IW, Nuarsa IW. 2012. Enhanced built-UP and bareness index (EBBI) for mapping built-UP and bare land in an urban area. Remote Sens. 4(10):2957–2970.
  • Azhar G, Saha S, Ganguly P, Mavalankar D, Madrigano J. 2017. Heat wave vulnerability mapping for India. Int J Environ Res Public Health. 14(4):357.
  • Azhar GS, Mavalankar D, Nori-Sarma A, Rajiva A, Dutta P, Jaiswal A, Sheffield P, Knowlton K, Hess JJ, on behalf of the Ahmedabad HeatClimate Study Group 2014. Heat-related mortality in India: excess all-cause mortality associated with the 2010 Ahmedabad heat wave. PLoS One. 9(3):e91831.
  • Azizi Z, Najafi A, Sohrabi H. 2008. Forest canopy density estimating, using satellite images. Beijing, China: ISPRS. Vol. XXXVII; p. 1127–1130.
  • Bhaduri B, Nad Phillip Coleman EB, Dobson J. 2002. Land scan: locating people is what matters. Geoinformatics. 5:34–37.
  • Bharath HA, Vinay S, Chandan MC, Gouri BA, Ramachandra TV. 2018. Green to gray: silicon Valley of India. J Environ Manage. 206:1287–1295.
  • Bose T, Bandyopadhyay S, Rawal D. 2016. Impacts of climate variability on urban floods—A case of Ahmedabad. Environ Urban ASIA. 7(2):234–242.
  • Brown de Colstoun EC, Huang C, Wang P, Tilton JC, Tan B, Phillips J, Niemczura S, Ling P-Y, Wolfe RE. 2017. Global man-made impervious surface (GMIS) dataset from landsat. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4P55KKF
  • Chakraborti S, Banerjee A, Sannigrahi S, Pramanik S, Maiti A, Jha S. 2019. Assessing the dynamic relationship among land use pattern and land surface temperature: a spatial regression approach. Asian Geogr. 36:93–116. https://doi.org/10.1080/10225706.2019.1623054.
  • Chen D, Lu X, Liu X, Wang X. 2019. Measurement of the eco-environmental effects of urban sprawl: theoretical mechanism and spatiotemporal differentiation. Ecol Indic. 105:6–15.
  • Chowdhury S, Dey S, Di Girolamo L, Smith KR, Pillarisetti A, Lyapustin A. 2019. Tracking ambient PM2. 5 build-up in Delhi national capital region during the dry season over 15 years using a high-resolution (1 km) satellite aerosol dataset. Atmos Environ. 204:142–150.
  • Crist EP. 1985. A TM Tasseled Cap equivalent transformation for reflectance factor data. Remote Sens Environ. 17(3):301–306. (85)90102-6
  • Franco S, Mandla VR, Ram Mohan Rao K. 2017. Trajectory of urban growth and its socioeconomic impact on a rapidly emerging megacity. J Urban Plan Dev. 143:1–10. DOI:10.1061/(ASCE)UP.1943-5444.0000378.
  • Govind NR, Ramesh H. 2019. The impact of spatiotemporal patterns of land use land cover and land surface temperature on an urban cool island: a case study of Bengaluru. Environ Monit Assess. 191:283. DOI:10.1007/s10661-019-7440-1.
  • Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, Briggs JM. 2008. Global change and the ecology of cities. Science. 319(5864):756–760.
  • Gumma MK, Mohammad I, Nedumaran S, Whitbread A, Lagerkvist CJ. 2017. Urban sprawl and adverse impacts on agricultural land: a case study on Hyderabad. India Remote Sens. 9(11):1136–1116.
  • Guttikunda SK, Nishadh KA, Gota S, Singh P, Chanda A, Jawahar P, Asundi J. 2019. Air quality, emissions, and source contributions analysis for the Greater Bengaluru region of India. Atmos Pollut Res. 10(3):941–953.
  • He J, Wang S, Liu Y, Ma H, Liu Q. 2017. Examining the relationship between urbanization and the eco-environment using a coupling analysis: case study of Shanghai, China. Ecol Indic. 77:185–193.
  • Hu X, Xu H. 2019. A new remote sensing index based on the pressure-state-response framework to assess regional ecological change. Environ Sci Pollut Res Int. 26(6):5381–5393.
  • Hu X, Xu H. 2018. A new remote sensing index for assessing the spatial heterogeneity in urban ecological quality: a case from Fuzhou City, China. Amsterdam, Netherlands: Elsevier. https://doi.org/10.1016/j.ecolind.2018.02.006
  • Hu Y, Liu X, Bai J, Shih K, Zeng EY, Cheng H. 2013. Assessing heavy metal pollution in the surface soils of a region that had undergone three decades of intense industrialization and urbanization. Environ Sci Pollut Res Int. 20(9):6150–6159.
  • Huete AR. 1988. A soil-adjusted vegetation index (SAVI). Remote Sens Environ. 25(3):295–309.
  • Jat MK, Khare D, Garg PK, Shankar V. 2009. Remote sensing and GIS-based assessment of urbanisation and degradation of watershed health. Urban Water J. 6(3):251–263.
  • Kauth RJ, Thomas GS. 1976. The tasselled cap–a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. LARS Symposia. Indiana: Purude University; p. 159. http://docs.lib.purdue.edu/lars_symp
  • Kou G, Wu W, Zhao Y, Peng Y, Yaw NE, Shi Y. 2010. A dynamic assessment method for urban eco-environmental quality evaluation. J Multi Criteria Decis Anal. 110:79–110. DOI:10.1002/mcda.
  • Kulkarni PS, Ghude SD, Bortoli D. 2010. Tropospheric ozone (TOR) trend over three major inland Indian cities: Delhi, Hyderabad and Bangalore. Ann Geophys. 28(10):1879–1885.
  • Kumar P, Geneletti D, Nagendra H. 2016. Spatial assessment of climate change vulnerability at city scale: a study in Bangalore, India. Land Use Policy. 58:514–532.
  • Lehner A, Kraus V, Steinnocher K. 2016. Urban growth scenarios of a future mega city: case study Ahmedabad. ISPRS Ann Photogramm Remote Sens Spatial Inf Sci. III-2:165–172.
  • Liou YA, Nguyen AK, Li MH. 2017. Assessing spatiotemporal eco-environmental vulnerability by Landsat data. Ecol Indic. 80:52–65.
  • Liu N, Liu C, Xia Y, Da B. 2018. Examining the coordination between urbanization and eco-environment using coupling and spatial analyses: a case study in China. Ecol Indic. 93:1163–1175.
  • Liu Q, Shi T. 2019. Spatiotemporal differentiation and the factors of ecological vulnerability in the Toutun river basin based on remote sensing data. Sustainability. 11(15):4160.
  • Liu Y, Yue W, Fan P, Zhang Z, Huang J. 2017. Assessing the urban environmental quality of mountainous cities: a case study in Chongqing, China. Ecol Indic. 81:132–145.
  • Lu L, Weng Q, Guo H, Feng S, Li Q. 2019. Assessment of urban environmental change using multi-source remote sensing time series (2000-2016): a comparative analysis in selected megacities in Eurasia. Sci Total Environ. 684:567–577.
  • Mahadevia D, Deasi R, Vyas S. 2014. City profile: Ahmedabad, CUE working paper; 26. http://hdl.handle.net/10625/55670
  • Mell IC. 2018. Greening Ahmedabad—creating a resilient Indian city using a green infrastructure approach to investment. Landsc Res. 43(3):289–314.
  • Mohan M, Kandya A. 2015. Impact of urbanization and land-use/land-cover change on diurnal temperature range: a case study of tropical urban airshed of India using remote sensing data. Sci Total Environ. 506–507:453–465.
  • MoHUA. 2019a. Consulation paper on city GDP measurement framework. https://smartnet.niua.org/sites/default/files/resources/city_gdp_measurement_framework-for_web.pdf
  • MoHUA. 2019b. Climate smart cities. https://www.niua.org/csc/assessment-overview.html
  • Mondal B, Dolui G, Pramanik M, Maity S, Biswas SS, Pal R. 2017. Urban expansion and wetland shrinkage estimation using a GIS-based model in the East Kolkata Wetland, India. Ecol Indic. 83:62–73.
  • Musse MA, Barona DA, Santana Rodriguez LM. 2018. Urban environmental quality assessment using remote sensing and census data. Int J Appl Earth Obs Geoinf. 71:95–108.
  • Nagendra H, Gopal D. 2010. Street trees in Bangalore: density, diversity, composition and distribution. Urban For Urban Green. 9(2):129–137.
  • Nagendra H, Nagendran S, Paul S, Pareeth S. 2012. Graying, greening and fragmentation in the rapidly expanding Indian city of Bangalore. Landsc Urban Plan. 105(4):400–406.
  • Nagendra H, Ostrom E. 2014. Applying the social-ecological system framework to the diagnosis of urban lake commons in Bangalore, India. Ecol Soc. 19:67. https://doi.org/10.5751/ES-06582-190267.
  • Nagendra H, Sudhira HS, Katti M, Schewenius M. 2013. Sub-regional assessment of India: effects of urbanization on land use, biodiversity and ecosystem services. Urbanization, biodiversity and ecosystem services: challenges and opportunities. Dordrecht, the Netherlands: Springer; p. 65–74.
  • Naik PK, Tambe JA, Dehury BN, Tiwari AN. 2008. Impact of urbanization on the groundwater regime in a fast growing city in central India. Environ Monit Assess. 146(1–3):339–373.
  • Pramanik S, Punia M. 2019a. Land use/land cover change and surface urban heat island intensity: source–sink landscape-based study in Delhi, India. Environ Dev Sustain. 22:7331–7356.
  • Pramanik S, Punia M. 2019b. Assessment of green space cooling effects in dense urban landscape: a case study of Delhi, India. Model Earth Syst Environ. 5(3):867–884.
  • Pramanik S, Punia M, Chakraborty S. 2020. Does urban landscape composition and configuration regulate heat-related health risk? A spatial regression-based study in world’s dense city Delhi, India. Preprints 2020, 2020110046.
  • Rahman A, Kumar Y, Fazal S, Bhaskaran S. 2011. Urbanization and quality of urban environment using remote sensing and GIS techniques in East Delhi-India. J Geograph Inform Syst. 03(01):62–84.
  • Ramachandra TV, Aithal BH, Sanna DD. 2012. Insights to urban dynamics through landscape spatial pattern analysis. Int J Appl Earth Obs Geoinf. 18:329–343.
  • Rose AN, McKee JJ, Urban ML, Bright EA. 2018. Land Scan 2017. LandScan. https://landscan.ornl.gov/
  • Rouse J, Haas RH. Schell JA, Deering DW. 1974. Monitoring vegetation systems in the great plains with ERTS. NASA special publication 351, 1974; p. 309. https://ntrs.nasa.gov/citations/19740022614.
  • Sankhe S, Vittal I, Dobbs R, Mohan A, Gulati A, Ablett J, Gupta S, Kim A, Paul S, Sanghvi A, et al. 2010. India's urban awakening: building inclusive cities, sustaining economic growth. Mumbai: McKinsey Global Institute; p. 234.
  • Sannigrahi S, Bhatt S, Rahmat S, Uniyal B, Banerjee S, Chakraborti S, Jha S, Lahiri S, Santra K, Bhatt A. 2018. Analyzing the role of biophysical compositions in minimizing urban land surface temperature and urban heating. Urban Clim. 24:803–819.
  • Sannigrahi S, Zhang Q, Joshi PK, Sutton PC, Keesstra S, Roy PS, Pilla F, Basu B, Wang Y, Jha S, et al. 2020. Examining effects of climate change and land use dynamic on biophysical and economic values of ecosystem services of a natural reserve region. J Clean Prod. 257:120424.
  • Sathyakumar V, Ramsankaran RAAJ, Bardhan R. 2019. Linking remotely sensed urban green space (UGS) distribution patterns and socio-economic status (SES) - A multi-scale probabilistic analysis based in Mumbai, India. GIScience Remote Sens. 56(5):645–669.
  • Seddon AWR, Macias-Fauria M, Long PR, Benz D, Willis KJ. 2016. Sensitivity of global terrestrial ecosystems to climate variability. Nature. 531(7593):229–232.
  • Seto KC, Parnell S, Elmqvist T. 2013. A global outlook on urbanization. Urbanization, biodiversity and ecosystem services: challenges and opportunities. Dordrecht, the Netherlands: Springer; p. 1–12.
  • Shastri H, Barik B, Ghosh S, Venkataraman C, Sadavarte P. 2017. Flip flop of day-night and summer-winter surface urban heat island intensity in India. Sci Rep. 7:40178.
  • Sudhira HS, Ramachandra TV, Subrahmanya MHB. 2007. Bangalore. Cities. 24(5):379–390.
  • Sun X, Liu X, Li F, Tao Y, Song Y. 2017. Comprehensive evaluation of different scale cities’ sustainable development for economy, society, and ecological infrastructure in China. J Clean Prod. 163:S329–S337.
  • UNDP. 2017. Sustainable development goals [WWW document]. New York (NY): UNDP.
  • United Nation. 2018. World urbanization prospects, demographic research.
  • United Nations. 2018. 2018 revision of world urbanization prospects. New York (NY): United Nations.
  • Vyas A, Shastri B, Joshi Y. 2014. Spatio-temporal analysis of UHI using geo-spatial techniques: a case study of Ahmedabad city. Int Arch Photogramm Remote Sens Spatial Inf Sci. XL-8:997–1002.
  • Wan Z, Hulley G. 2015. MYD11A2 MODIS/Aqua land surface temperature/emissivity 8-day L3 global 1km SIN grid V006 [data set]. NASA EOSDIS Land Processes DAAC. DOI:10.5067/MODIS/MYD11A2.006.
  • Wikipedia. 2020a. Sensitivity analysis. Greenwich, England: Wikipedia.
  • Wikipedia. 2020b. Elasticity (economics). Greenwich, England: Wikipedia.
  • Wilson EH, Sader SA. 2002. Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sens Environ 80(3):385–396.
  • Yatoo SA, Sahu P, Kalubarme MH, Kansara BB. 2020. Monitoring land use changes and its future prospects using cellular automata simulation and artificial neural network for Ahmedabad city, India. GeoJournal. 1–22.DOI:10.1007/s10708-020-10274-5
  • Yue H, Liu Y, Li Y, Lu Y. 2019. Eco-environmental quality assessment in china’s 35 major cities based on remote sensing ecological index. IEEE Access. 7:51295–51311.
  • Zanter K. 2016. Landsat 8 (L8) data users handbook. USGS. https://www.usgs.gov/media/files/landsat-8-data-users-handbook.
  • Zha Y, Gao J, Ni 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.

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