<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The study focused on investigating the seasonal and spatiotemporal relationship between the relationships of LST with four spectral indices (MNDWI, NDBaI, NDBI, and NDVI) in and around Manipur City of India using eight cloud-free Landsat data from the summer and winter seasons for 1991, 2001, 2011, and 2021. These spectral indices respond differently to the change of LST in an urban landscape. Pearson’s linear correlation coefficient was the basis of the correlation analysis. The study finds that LST builds a moderate negative relationship with NDVI (R = -0.42) and MNDWI (R = -0.42), a moderate positive relationship with NDBaI (R=0.48), and NDBI (R = 0.61). The relationship is more stable in the winter season (CV = 7.31, 7.04, 10.45, and 28.71 for MNDWI, NDBaI, NDBI, and NDVI, respectively) than in summer (CV = 44.46, 36.09, 23.67, and 29.71 for MNDWI, NDBaI, NDBI, and NDVI, respectively). The strength of the relationship is gradually increasing in the winter season while there is no such effect noticed on the trend in the summer season. The LST-NDBI relationship is the most consistent (CV = 18.19), while the LST-NDVI relationship is the most variable (CV = 30.37).</p>
</abstract>

The study focused on investigating the seasonal and spatiotemporal relationship between the relationships of LST with four spectral indices (MNDWI, NDBaI, NDBI, and NDVI) in and around Manipur City of India using eight cloud-free Landsat data from the summer and winter seasons for 1991, 2001, 2011, and 2021. These spectral indices respond differently to the change of LST in an urban landscape. Pearson’s linear correlation coefficient was the basis of the correlation analysis. The study finds that LST builds a moderate negative relationship with NDVI (R = -0.42) and MNDWI (R = -0.42), a moderate positive relationship with NDBaI (R=0.48), and NDBI (R = 0.61). The relationship is more stable in the winter season (CV = 7.31, 7.04, 10.45, and 28.71 for MNDWI, NDBaI, NDBI, and NDVI, respectively) than in summer (CV = 44.46, 36.09, 23.67, and 29.71 for MNDWI, NDBaI, NDBI, and NDVI, respectively). The strength of the relationship is gradually increasing in the winter season while there is no such effect noticed on the trend in the summer season. The LST-NDBI relationship is the most consistent (CV = 18.19), while the LST-NDVI relationship is the most variable (CV = 30.37).

A Seasonal Investigation on Land Surface Temperature and Spectral Indices in Imphal City, India

Journal of Landscape Ecology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The study focused on investigating the seasonal and spatiotemporal relationship between the relationships of LST with four spectral indices (MNDWI, NDBaI,...

A Seasonal Investigation on Land Surface Temperature and Spectral Indices in Imphal City, India

Online veröffentlicht: 08. Dez. 2022

Seitenbereich: 1 - 18

Eingereicht: 05. Aug. 2022

Akzeptiert: 14. Sept. 2022

DOI: https://doi.org/10.2478/jlecol-2022-0015

Schlüsselwörter
Imphal city, LST, MNDWI, NDBaI, NDBI, NDVI

© 2022 Anupam Pandey et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A Seasonal Investigation on Land Surface Temperature and Spectral Indices in Imphal City, India

Online veröffentlicht: 08. Dez. 2022

Seitenbereich: 1 - 18

Eingereicht: 05. Aug. 2022

Akzeptiert: 14. Sept. 2022

DOI: https://doi.org/10.2478/jlecol-2022-0015

SchlüsselwörterImphal city, LST, MNDWI, NDBaI, NDBI, NDVI

© 2022 Anupam Pandey et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Imphal city, LST, MNDWI, NDBaI, NDBI, NDVI