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Seasonal variability of LST-NDVI correlation on different land use/land cover using Landsat satellite sensor: a case study of Raipur City, India

Author

Listed:
  • Subhanil Guha

    (National Institute of Technology)

  • Himanshu Govil

    (National Institute of Technology)

Abstract

The modern cities of the world are characterized by continuous warming status. Land surface temperature (LST) is a very important part of the environmental status of mixed urban land and it is intimately associated with normalized difference vegetation index (NDVI). The current study makes an attempt on the seasonal fluctuation of LST-NDVI relation on diversified land surface material in Raipur City of India by using a large Landsat dataset for different seasons from 1991–92 to 2018–19. The results present the considerable rising trend of mean LST (1.6 °C, 5.3 °C, 4.8 °C, and 1.1 °C in the pre-monsoon, monsoon, post-monsoon, and winter, respectively) during the study period. The LST and NDVI produce a strong negative correlation (− 0.74, − 0.54, − 0.63, and − 0.49 in these four seasons) on plants; a moderate negative correlation (− 0.42, − 0.34, − 0.42, and − 0.21 in the four aforesaid seasons) on the barren land and urban settlement; and an insignificant correlation (0.27, 0.08, 0.05, and 0.19 in the four abovementioned seasons) on water bodies. This study is helpful in future planning for the ecological development of a city in tropical environment.

Suggested Citation

  • Subhanil Guha & Himanshu Govil, 2022. "Seasonal variability of LST-NDVI correlation on different land use/land cover using Landsat satellite sensor: a case study of Raipur City, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8823-8839, June.
    • Handle: RePEc:spr:endesu:v:24:y:2022:i:6:d:10.1007_s10668-021-01811-4
    DOI: 10.1007/s10668-021-01811-4
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