Evaluation of temporal dynamics of land use and land surface temperature (LST) in Agartala city of India

Neog, Rituraj

doi:10.1007/s10668-021-01572-0

Cited by 22 publications

(7 citation statements)

References 36 publications

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“…In the future, we ought to observe potential factors like anthropogenic activities [28], solar irradiance [29], and LUCC [27]. This relationship was similar to the outcome of previous research, where the relationship between both was roughly less than 0.5 [11,30]. 4.…”

Section: Resultssupporting

confidence: 81%

Application of Landsat-8 OLI/TIRS to assess the Urban Heat Island (UHI)

Karyati

Sholihah

Panuju

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Urban Heat Island (UHI) phenomenon is a particular climate change impact in urban areas that can trigger adverse effects on environmental conditions. This effect is usually worsened by increasing anthropogenic activities. While the impact of UHI has mostly been studied in metropolitans around the world, few studies are presented investigating the outcome in mid-sized cities. This study aims to assess spatial distribution of Urban Heat Island (UHI) in Bogor city, Indonesia, by utilizing thermal data (Band-10) from Landsat-8 OLI/TIRS. The Landsat imagery was acquired in May 2021, in the beginning of the dry season. The result of study shows Land Surface Temperature (LST) values ranged from 26.23 to 33.76°C, with an average temperature of 31.29°C, while the range of NDVI was between 0.08 to 0.55. Further, the correlation between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) was calculated to investigate the relationship between vegetation density and surface temperature condition for examining the outlook and possibilities to minimize the impact of UHI through improving vegetal conditions. A negative correlation suggests that expanding vegetation coverage can reduce urban heat island impacts by 35%, and other factors influence the rest. The land surface temperature threshold to determine UHI is 32.01°C, so the UHI area was identified at ca. 13.12 km2 around the city centre.

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Section: Resultssupporting

confidence: 81%

Application of Landsat-8 OLI/TIRS to assess the Urban Heat Island (UHI)

Karyati

Sholihah

Panuju

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…According to previous studies, urbanization would inevitably lead to the change of land use type, structure and pattern, the destruction of the balance between surface radiation and energy, the excessive release of consumed energy, and the change of near surface atmospheric structure [4,5,22,32], which would eventually lead to the change of temporal and spatial pattern of surface temperature. Moreover, for rapidly expanding urban areas, the replacement of vegetation, the changes in building materials and surface reflectivity will be very rapid [30,41,45], which will lead to rapid evolution of the spatial distribution of LST.…”

Section: Discussionmentioning

confidence: 99%

“…It is well known that with the advancement of urbanization, the composition and spatial configuration of land use/land cover (LULC) have undergone tremendous changes, which have had a serious impact on human health, production activities and living environment [1][2][3][4]. In the process of urbanization, natural features such as vegetation and water are gradually replaced by impervious surfaces such as buildings, roads and squares [5] and the land surface temperature (LST) increases, which will lead to the continuous deterioration of urban thermal environment quality [6,7].…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Variation of Land Surface Temperature in Recent 20 Years and Analysis of the Effect of Land Use in Jiangxi Province, China

et al. 2022

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Under the background of global warming, it is of great significance to study the temporal and spatial evolution of land surface temperature (LST) on long-time scale and the impacts of land use in the fields of urban thermal environment and regional climate change. Based on MODIS LST long time series remote sensing data, the temporal and spatial evolution characteristics of pixel-wise LST in Jiangxi Province, the middle inland province of China from 2000 to 2020 were analyzed by using Theil-Sen + Mann-Kendall, coefficient of variation and Hurst index, and the response of LST to land use was identified by combining the contribution and diversity index. The results showed as follows: (1) LST was generally distributed as "high in Middle-East-West-South and low in North-northwest-southeast direction". LST showed an overall downward trend, indicating a weakening of the warming trend. The dynamic trend of LST was characterized by more descending than ascending tendency. The dynamic stability showed a coexistence of high and low fluctuation tendency, with a higher proportion of medium and low fluctuation areas having obvious spatial differences. The overall dynamic sustainability was characterized by uncertainty of future change trend. (2) The LST were strongly affected by land use in the past 20 years. Firstly, the areas of high LST were mostly located in construction land and unused land, while the areas of low LST were mostly in water area and forest land. However, forest land and water area of high temperature were gradually turned to construction land later on. Secondly, the land use structure and pattern had an strong effects on LST. With the increase of the area proportion of different land use, the LST showed significant differences. The more complex the spatial pattern of land use, the more obvious its impact on LST. The research results will provide some reference for the regions with the same characteristics as Jiangxi Province to deal with LST under the background of global climate change.

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“…GeoAI enables the processing of large and complex geographic data using intelligent algorithms to identify patterns, relationships and trends that cannot be seen directly by humans (Ermida et al, 2020). Meanwhile, UAVs provide flexibility in collecting high-resolution spatial data and acquiring accurate thermal images of LST (Neog, 2022).…”

Section: Introductionmentioning

confidence: 99%

Geographic Artificial Intelligence and Unmanned Aerial Vehicles Application for Correlation Analysis of Settlement Density and Land Surface Temperature in Panggang Island Jakarta

Pertuack,

Latue

2023

Buana j. Geografi Ekologi dan Kebencanaan

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This research aims to understand the relationship between high settlement density and land surface temperature associated with the Urban Heat Island (UHI) phenomenon. The data processing method involves collecting settlement density data using UAVs equipped with thermal sensors, as well as using GeoAI, namely GEE, to analyze LST on Panggang Island. The results showed a positive relationship between settlement density and LST on Panggang Island, with high settlement density contributing to an increase in ground surface temperature. The benefits of the application of GeoAI and UAVs in this analysis include accurate mapping, understanding the impacts of urbanization, sustainable urban planning, and fact-based decision-making. It is hoped that this research can contribute to better urban management and reduction of environmental impacts in Pulau Panggang, DKI Jakarta.

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Evaluation of temporal dynamics of land use and land surface temperature (LST) in Agartala city of India

Cited by 22 publications

References 36 publications

Application of Landsat-8 OLI/TIRS to assess the Urban Heat Island (UHI)

Application of Landsat-8 OLI/TIRS to assess the Urban Heat Island (UHI)

Temporal and Spatial Variation of Land Surface Temperature in Recent 20 Years and Analysis of the Effect of Land Use in Jiangxi Province, China

Geographic Artificial Intelligence and Unmanned Aerial Vehicles Application for Correlation Analysis of Settlement Density and Land Surface Temperature in Panggang Island Jakarta

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