Assessment of spatio-temporal changes in land use and land cover, urban sprawl, and land surface temperature in and around Vijayawada city, India
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The urban agglomeration is the unplanned growth of a city into its surrounding peri/rural areas causing unsustainable exploitation of natural resources. This leads to an increase in the land surface temperature that in turn results in climatic issues ranging from local to global scales. In the current study, an attempt has been made to map the urban growth and its associated land surface temperature variations in and around Vijayawada city of Andhra Pradesh state, India. Temporal Landsat satellite images from 4 years, viz. 1990, 2000, 2010, and 2018, were used to generate land use/land cover maps with four major classes such as built-up, vegetation, water body, and others. Change detection and transition of the natural land cover to man-made land use were statistically computed for the study area. Sprawl analysis of the city was carried out by generating multiple buffer rings over the study region to evaluate the urban density and annual urban growth rate. Shannon’s entropy was employed to identify the nature of city expansion. The seasonal variation of the land surface temperature was studied using Mono-window algorithm. The temperature variation over individual classes was computed with the aid of a self-designed random point method. Results showed a steady increasing trend in the urban density and land surface temperature with the distinct formation of a heat island over the city, especially during winters throughout the study period. The settlement area has increased from 28.20 km2 in 1990 to 138.01 km2 in 2018. The directional growth analysis captured the pattern of city growth as tentacle-type development in conjunction with infill development. The sprawl happening around Vijayawada ignores the depletion of natural resources, leading to anomalies in the land surface temperature.
KeywordsSprawl pattern Change detection Entropy Growth metric Mono-window algorithm
The authors express gratitude to the Human Resource Development Group (HRDG)—Council of Scientific and Industrial Research (CSIR), Government of India (GoI), for funding this research. Authors also thank USGS for providing multi-temporal satellite data used in this study and also Vijayawada Municipal Corporation (VMC) for their inputs and suggestions. We are grateful to the anonymous reviewers for their constructive suggestions in revising this article.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- APCRDA. (2016). Amaravati project. Vijayawada: Andhra Pradesh Capital Region Development Authority.Google Scholar
- Baldinelli, G., Bonafoni, S., & Verducci, P. (2016). Sustainable strategies for smart cities: Analysis of the town development effect on surface urban heat island through remote sensing methodologies. Sustainable Cities and Society, 29, 211–218.Google Scholar
- Barnes, K. B., Morgan, J. M., III, Roberge, M. C., & Lowe, S. (2001). Sprawl development: Its patterns, consequences, and measurement. Towson: Towson University.Google Scholar
- Bekele, H. (2005). Urbanization and urban sprawl. Dissertation, Kungliga Tekniska Högskolan, StockholmGoogle Scholar
- Epstein, J., Payne, K., & Kramer, E. (2002). Techniques for mapping suburban sprawl. Photogrammetric Engineering and Remote Sensing, 63(9), 913–918.Google Scholar
- Girard, L. F., Cerreta, M., de Toro, P. & Forte F. (2007). The human sustainable city: Values, approaches and evaluative tools. Sustainable urban development 2: The environmental assessment methods, pp. 65–93.Google Scholar
- Hall, P. (2003). The sustainable city in an age of globalization. In L. Fusco Girard, B. Forte, M. Cerreta, P. De Toro, & F. Forte (Eds.), The human sustainable city: Challenges and perspectives from the habitat agenda (pp. 55–69). Aldershot: Ashgate.Google Scholar
- IMD (2015). Vijayawada climatological table period: 1981–2010. Indian Meteorological Department. http://www.imd.gov.in/section/climate/extreme/vijaywada2.htm. Accessed 29 Aug 2018.
- Kant, Y., Mallick, J., & Bharath, B. D. (2008). Estimation of land surface temperature over Delhi using Landsat-7 ETM+. Journal of Indian Geophysical Union, 12(3), 131–140.Google Scholar
- Kumar, K. S., Bhaskar, P. U., & Padmakumari, K. (2012). Estimation of land surface temperature to study urban heat Island effect using Landsat ETM + Image. International Journal of Engineering Science and Technology, 4(2), 771–778.Google Scholar
- Li, M. M., Wu, B. F., Yan, C. Z., et al. (2004). The remote sensing evaluation of green coverage ratio in upstream of Miyun reservoir. Resource Science, 26(4), 153–158.Google Scholar
- Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2004). Remote sensing and image interpretation (5th ed.). New York: Wiley.Google Scholar
- Longley, P. A., Goodchild, M. E., Maguire, D. J., & Rhind, D. W. (1999). Geographic information systems, I and II. New York: Wiley.Google Scholar
- Makbouli, Y., Hakdaoui, M., Ghafir, A., & Elmutaki, S. (2015). Monitoring urban evolution between 1975 and 2015 using GIS and remote sensing technics: Case of Lâayoune City (Morocco). International Journal of Advanced Research, 3(10), 331–342.Google Scholar
- NDMA. (2016). Guidelines for preparation of action plan—Prevention and management of heat wave. New Delhi: National Disaster Management Authority, Government of India.Google Scholar
- NIC (2014). India—National profile, Disaster risk profile, Institutional setup, Initiatives. National portal of India. https://www.india.gov.in/. Accessed 29 Aug 2018.
- Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108, 1–24.Google Scholar
- Park, R. E., & Burgess Ernest W. (1925). The growth of the city: An introduction to a research project. Chicago: University of Chicago Press, pp. 47–62. ISBN: 9780226148199.Google Scholar
- Prasad, R. C. P., Karuna, C. V. L., & Asha Kumari, J. (2017). Evaluating mangroves of Krishna Wildlife Sanctuary in relation to the general status of mangroves in Andhra Pradesh, India. International Journal of Environmental Studies. https://doi.org/10.1080/00207233.2017.1283939.CrossRefGoogle Scholar
- Rahman A. (2005). Urban sprawl and its environmental impact assessment (EIA) of twin city Hyderabad-Secundrabad using remote sensing and GIS techniques. Project report, Centre for Space Science and Technology (CSSTEAP-UN), IIRS Campus, Dehradun.Google Scholar
- Setturu, B., Aithal, B. H., Sanna Durgappa, D., & Ramachandra, T. V. (2012). Landscape dynamics through spatial metrics. In Proceedings of 14th annual international conference and exhibition on geospatial information technology and applications, India Geospatial Forum.Google Scholar
- Shi, Y., & Zhang, Y. (2017). Remote sensing retrieval of urban land surface temperature in hot-humid region. Journal of Urban Climate, 24, 2212-0955.Google Scholar
- Silambarasan, K., Vinaya, M. S., & Suresh Babu, S. (2014). Urban sprawl mapping and landuse change detection in and around Udupi Town: A remote sensing based approach. International Journal of Science Research in Engineering and Technology, 2(12), 815–820.Google Scholar
- Stan, A. I. (2013). Morphological patterns of urban sprawl territories. Urbanism Arhitectură Construcţii, 4(4), 11–24.Google Scholar
- Stathopoulou, M., Synnefa, A., Caralis, C., Santamouris, M., Karless, T., & Akbari, H. (2009). A surface heat island study of Athens using high-resolution satellite imagery and measurements of the optical and thermal properties of commonly used building and paving materials. International Journal of Sustainable Energy, 28(1), 59–76.CrossRefGoogle Scholar
- Sundarakumar, K., Harika, M., Aspiya Begum, S. K., Yamini, S., & Balakrishna, K. (2012). Land use and land cover change detection and urban sprawl analysis of Vijayawada city using multi temporal Landsat data. International Journal of Engineering Science and Technology, 4, 1.Google Scholar
- Thomas, R. W. (1981). Information Statistics in Geography. Geo Abstracts. University of East Anglia, Norwich, United Kingdom. p. 42Google Scholar
- UN DESA. (2018). Revision of world urbanization prospects. New York: United Nations Department of Economic and Social Affairs.Google Scholar
- USGS. (2016). Landsat 8(L8) data user’s handbook (2.0). Reston: Department of the interior U.S. geological survey.Google Scholar
- Van, T. T., Phuong, D. T. K., Phan Y. V., & Xuan Bao, H. D. 22 June–5 July (2015). Mapping changes of surface topography under urbanization process in Ho Chi Minh City, Vietnam, Using Satellite Imagery. In International electronic conference on Remote Sensing.Google Scholar
- VMC (2015). Vijayawada city disaster management plan. Government of India-UNDP disaster management project. Vijayawada Municipal Corporation.Google Scholar
- Yeh, A. G., & Xia, U. (2001). Measurement and monitoring of urban sprawl in a rapidly growing region using entropy. Photogrammetric Engineering and Remote Sensing, 67(1), 83–90.Google Scholar