Analysing transition of land surface temperature and derived indices with respect to elevation values in Kohima Saddar

Kikon, Noyingbeni; Kumar, Deepak; Ahmed, S. A.

doi:10.1007/s10708-022-10580-0

Cited by 3 publications

(4 citation statements)

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“…This is due to the emission characteristics of the various land surface features, where the ground surface has a low emissivity coefficient value in the range of about 0.65–0.99, for open and barren land, and when the solar radiation falls on the ground, there are no restrictions, and the radiation comes into direct contact with the surface and which is then immediately released, resulting in high land surface temperatures (Lin et al 2018 ; Liu et al 2021 ). In built-up areas, the various building materials such as brick and concrete have an emissivity of 0.93 and 0.85, respectively, which traps solar radiation and slowly releases it as heat, creating an urban heat island and resulting in increased land surface temperature (Kikon et al 2022 ; Kumar 2017 ; Kumar et al 2018a ; Kumar and Shekhar 2015 ). As can be seen in Fig.…”

Section: Discussionmentioning

confidence: 99%

“…The selected grids are numbered 1 and 2 as shown in the map in Figs. 9 , 10 , 11 , 12 , and 13 (Kikon et al 2022 ; Najafzadeh et al 2021 ). From the results of this analysis, it can be concluded that the lockdown period has a direct impact on the decreasing LST value (Shetty et al 2021 ; Shi et al 2021 ; Wang et al 2021a , b ).…”

Section: Discussionmentioning

confidence: 99%

“…Likewise, LST and NDVI are negatively correlated with a Pearson correlation value of − 0.517 and − 0.736 in 2009 and 2020, respectively, for grid number 1, and a Pearson correlation value of − 0.533 and − 0.519 in 2009 and 2020, respectively, for grid number 2. This is because plants absorb the incoming solar radiation, resulting in low land surface temperature due to their high emissivity (Kikon et al 2022 ). A strong inverse correlation was found between NDVI and NDBI, with Pearson correlation values of − 0.771 and − 0.843 in 2009 and 2020, respectively for grid number 1, and Pearson correlation values of − 0.816 and − 0.954 in 2009 and 2020, respectively, for grid number 2.…”

Section: Discussionmentioning

confidence: 99%

“…The urban areas have a higher LST as compared to the surrounding rural regions (Kikon et al 2022 ). One of the main reasons for the increase in environmental problems in the world is urbanization, which has a direct impact on climate variability (McCarthy et al 2010 ).…”

Section: Introductionmentioning

confidence: 99%

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Quantitative assessment of land surface temperature and vegetation indices on a kilometer grid scale

Kikon

Kumar

Ahmed

2023

Environ Sci Pollut Res

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Due to expanding populations and thriving economies, studies into the built environment’s thermal characteristics have increased. This research tracks and predicts how land use and land cover (LULC) changes may affect ground temperatures, urban heat islands, and city thermal fields (UTFVI). The current study examines land surface temperature (LST), urban thermal field variance index (UTFVI), normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI), and land use land cover (LULC) on a kilometer scale. According to the comparative study, the mean LST decreases by 3 °C and the NDVI increases considerably. Correlation analysis showed that LST and NDVI are inversely connected, while LST and NDBI are positively correlated. NDVI and NDBI have a strong negative association, while LST and UTFVI have a positive correlation. Urban planners and environmentalists can study the LST’s effects on land surface parameters in different environmental contexts during the lockout period. The urban heat island (UHI) phenomenon, in which the land surface qualities of an urban region cause a change in the urban thermal environment, forms and intensifies over an urban area. The minimum and maximum LST in grid number 1 in 2009 was 20.30 °C and 29.91 °C, respectively, with a mean LST of 25.1 °C. There was a decline in the minimum and maximum LST in grid number 1 in 2020 with a minimum and maximum LST of 17.31 °C and 25.35 °C, respectively, with a mean LST of 21.33 °C. There was a 3.8 °C drop in the LST of this grid. The minimum and maximum NDVI were also − 0.16 and 0.59, respectively, with an average NDVI value of 0.21. Therefore, it is essential to evaluate and foresee the impact of LULC change on the thermal environment and examines the connection between LULC shifts with subsequent changes in land surface temperature (LST) along with the UHI phenomenon. Maps of the UTFVI reveal positive UHI phenomena, with the highest UTFVI zones occurring over the developed area and none over the adjacent rural territory. During the summer months, the urban area with the strongest UTFVI zone grows noticeably larger than it does during the winter months during the forecasted years. Future policymakers and city planners can mitigate the effects of heat stress and create more sustainable urban environments by evaluating the expected distribution maps of LULC, LST, UHI, and UTFVI.

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