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Assessment of spatio-temporal changes in land use and land cover, urban sprawl, and land surface temperature in and around Vijayawada city, India

  • M. VaniEmail author
  • P. Rama Chandra Prasad
Article
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Abstract

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.

Keywords

Sprawl pattern Change detection Entropy Growth metric Mono-window algorithm 

Notes

Acknowledgements

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.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Lab for Spatial InformaticsInternational Institute of Information Technology-HyderabadHyderabadIndia

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