Effect of Land Surface Temperature on Urban Heat Island in Varanasi City, India

Dengue fever, which is spread by Aedes mosquitoes, has claimed many lives in Kerala, with the Thiruvananthapuram district bearing the brunt of the toll. This study aims to demarcate the dengue risk zones in Thiruvananthapuram district using the analytical hierarchy process (AHP) and the fuzzy-AHP (F-AHP) methods. For the risk modelling, geo-environmental factors (normalized difference vegetation index, land surface temperature, topographic wetness index, land use/land cover types, elevation, normalized difference built-up index) and demographic factors (household density, population density) have been utilized. The ArcGIS 10.8 and ERDAS Imagine 8.4 software tools have been used to derive the risk zone maps. The area of the risk maps is classified into five zones. The dengue risk zone maps were validated using dengue case data collected from the Integrated Disease Surveillance Programme portal. From the receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) values, it is proved that the F-AHP method (AUC value of 0.971) has comparatively more prediction capability than the AHP method (AUC value of 0.954) in demarcating the dengue risk zones. Also, based on the comparison of the risk zone map with actual case data, it was confirmed that around 82.87% of the dengue cases occurred in the very high and high-risk zones, thus proving the efficacy of the model. According to the dengue risk map prepared using the F-AHP model, 9.09% of the area of Thiruvananthapuram district is categorized as very high risk. The prepared dengue risk maps will be helpful for decision-makers, staff with the health, and disaster management departments in adopting effective measures to prevent the risks of dengue spread and thereby minimize loss of life.

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“…Land surface temperature The steps involved with the extraction of LST are mentioned below (as in Dang et al, 2020 , and Kumar et al, 2021a ):…”

Section: Methodsmentioning

confidence: 99%

Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods

et al. 2022

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“…The integration of these technologies has led to significant progress in water management. Remote sensing data aids in flood monitoring and prediction, identification of aquifer recharge zones, and development of sustainable water management strategies [39,40]. Furthermore, GIS facilitates information exchange among government institutions, water resource management organizations, and researchers, fostering effective collaboration in addressing water-related crises [41].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Land Use and Land Cover Changes and Associated Runoff Impact in Itaperuna, Brazil

da Silva,

Campos,

Reis

et al. 2023

Sustainability

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The urban growth intricately linked to the hydrological cycle outlines a crucial dynamic in the environmental transformations of cities. Utilizing the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Urban Flood Risk Mitigation model, we conducted hydrological modeling to assess the impact of urbanization on land use and land cover (LULC) changes and their subsequent effects on runoff generation in Itaperuna, Brazil, spanning the years 2015 to 2020. The analysis, performed across 17 urban sub-basins, highlights rapid urban expansion, notably in sub-basins 3 and 7, reflecting the city’s spatial dynamics and growth. Significantly, sub-basin 3 exhibited a 7.42% increase in runoff production capacity. The study meticulously documents changes in six LULC categories—water bodies, urban area, exposed soil, forest, natural pasture, and grassland vegetation—revealing that urban growth has directly amplified surface runoff in specific sub-basins, thereby impacting water resource management and flood prevention. Emphasizing the urgency of environmental conservation, especially in deforested basins, the findings hold substantial importance for urban planners and local authorities, offering relevant insights for flood risk mitigation and water security. Future research directions may explore additional facets, including water quality, advanced hydrological models, impacts on biodiversity and society, socioeconomic assessments of preventative measures, public policy considerations, and monitoring systems.

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“…These problems will result in a significant increase in surface temperature in downtown areas compared to suburban areas (Blooshi et al, 2020). This considerable temperature difference between the downtown area and the suburbs are referred to as the urban heat island phenomenon (Kumar et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Monitoring the Impact of Land Cover Change on Urban Heat Island with Remote Sensing & GIS

Nugroho,

Sugara,

Priana

et al. 2023

Geos. Ind.

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The increasing need for land has resulted in a higher rate of land conversion and urbanization, leading to a rise in urban density and the occurrence of an Urban Heat Island (UHI) effect. The application of remote sensing and GIS can serve as a substitute for data collection in monitoring the UHI phenomena. This work utilizes Landsat 8 OLI satellite image data, namely band 10, to analyze Land Surface Temperature (LST). Bands 5 and 4 are employed to assess the distribution of Normalized Difference Vegetation Index (NDVI) in Bekasi Regency during the years 2014 and 2020. The relationship between NDVI and LST is highly correlated as they can effectively forecast the influence of areas with sparse vegetation on temperature. The guided classification approach, employing the maximum likelihood algorithm and kappa validation, is utilized to evaluate alterations in land use. The kappa accuracy test yielded a score of 0.90% for 2014 and 0.99% for 2020. The research conducted between 2014 and 2020 revealed changes in land distribution. Specifically, the built-up land area increased by 99.92 Km2, empty land expanded by 280.82 Km2, bodies of water covered an additional 46.13 Km2, and vegetation expanded by 293.91 Km^2. According to the UHI research, it is evident that there has been a rise in surface temperature in Bekasi Regency from 2014 to 2020. In 2014, the minimum temperature reached 30 °C, and the maximum temperature reached 51 °C. In 2020, the minimum temperature was recorded at 34 °C, while the maximum temperature reached 52 °C.

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Effect of Land Surface Temperature on Urban Heat Island in Varanasi City, India

Cited by 14 publications

References 49 publications

Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods

Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods

Spatiotemporal Land Use and Land Cover Changes and Associated Runoff Impact in Itaperuna, Brazil

Monitoring the Impact of Land Cover Change on Urban Heat Island with Remote Sensing & GIS

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