Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets

The present study monitors the interrelationship of land surface temperature (LST) with normalized difference vegetation index (NDVI) in Raipur City of India using premonsoon Landsat satellite sensor for the season of 2002, 2006, 2010, 2014, and 2018. The results describe that the mean LST of Raipur...

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Main Authors: Subhanil Guha, Himanshu Govil, Prabhat Diwan
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Advances in Meteorology
Online Access:http://dx.doi.org/10.1155/2020/4539684
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author Subhanil Guha
Himanshu Govil
Prabhat Diwan
author_facet Subhanil Guha
Himanshu Govil
Prabhat Diwan
author_sort Subhanil Guha
collection DOAJ
description The present study monitors the interrelationship of land surface temperature (LST) with normalized difference vegetation index (NDVI) in Raipur City of India using premonsoon Landsat satellite sensor for the season of 2002, 2006, 2010, 2014, and 2018. The results describe that the mean LST of Raipur City is gradually increased with time. The value of mean NDVI is higher in the area below mean LST compared to the area above mean LST. The value of mean NDVI is also higher in Landsat 8 data than Landsat 5 and Landsat 7 data. A strong negative LST-NDVI correlation is observed throughout the period. The correlation coefficient is higher in the area above mean LST and lower in the area below mean LST. The value of the correlation coefficient is decreased with time. The mixed urban landscape of the city is closely related to the changes of LST-NDVI relationship. These results provide systematic planning of the urban environment.
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institution Kabale University
issn 1687-9309
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language English
publishDate 2020-01-01
publisher Wiley
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series Advances in Meteorology
spelling doaj-art-15bb5e2723fd428e97326ce911a387592025-02-03T06:46:34ZengWileyAdvances in Meteorology1687-93091687-93172020-01-01202010.1155/2020/45396844539684Monitoring LST-NDVI Relationship Using Premonsoon Landsat DatasetsSubhanil Guha0Himanshu Govil1Prabhat Diwan2Department of Applied Geology, National Institute of Technology Raipur, Raipur, IndiaDepartment of Applied Geology, National Institute of Technology Raipur, Raipur, IndiaDepartment of Applied Geology, National Institute of Technology Raipur, Raipur, IndiaThe present study monitors the interrelationship of land surface temperature (LST) with normalized difference vegetation index (NDVI) in Raipur City of India using premonsoon Landsat satellite sensor for the season of 2002, 2006, 2010, 2014, and 2018. The results describe that the mean LST of Raipur City is gradually increased with time. The value of mean NDVI is higher in the area below mean LST compared to the area above mean LST. The value of mean NDVI is also higher in Landsat 8 data than Landsat 5 and Landsat 7 data. A strong negative LST-NDVI correlation is observed throughout the period. The correlation coefficient is higher in the area above mean LST and lower in the area below mean LST. The value of the correlation coefficient is decreased with time. The mixed urban landscape of the city is closely related to the changes of LST-NDVI relationship. These results provide systematic planning of the urban environment.http://dx.doi.org/10.1155/2020/4539684
spellingShingle Subhanil Guha
Himanshu Govil
Prabhat Diwan
Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets
Advances in Meteorology
title Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets
title_full Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets
title_fullStr Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets
title_full_unstemmed Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets
title_short Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets
title_sort monitoring lst ndvi relationship using premonsoon landsat datasets
url http://dx.doi.org/10.1155/2020/4539684
work_keys_str_mv AT subhanilguha monitoringlstndvirelationshipusingpremonsoonlandsatdatasets
AT himanshugovil monitoringlstndvirelationshipusingpremonsoonlandsatdatasets
AT prabhatdiwan monitoringlstndvirelationshipusingpremonsoonlandsatdatasets