Predicting the impacts of urban development on seasonal urban thermal environment in Guwahati city, northeast India

Mohammad, Pir; Goswami, Ajanta

doi:10.1016/j.buildenv.2022.109724

Cited by 18 publications

(11 citation statements)

References 31 publications

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“…UTFVI was used in this analysis for the environmental assessment of UHI zones in Beijing. UTFVI was estimated using the following Equation ( 11) [47][48][49]:…”

Section: Delineating Urban Hot Spot Areas (Uhs)mentioning

confidence: 99%

Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)

2023

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Rapid urbanization poses a threat to various ecosystem services. Beijing has undergone extensive infrastructure development in recent years. The study aims to extract land surface temperature (LST) and land use cover (LUC) data from satellite imagery, identify urban heat island (UHI) areas in Beijing, and determine the correlation between LST, LUC, NDVI, and BUI. It will also investigate the relationship between UHI and built/unbuilt areas, evaluate thermal comfort in Beijing using UTFVI, and assess the ecological quality of different land use types using the Ecological Evaluation Index (EEI). The results can inform urban planning and management in rapidly urbanizing and climate-changing regions. Changes in LUC and other activities affect the distribution of LST. For the study years (2005–2020), the estimated mean LST in Beijing was 24.72 °C, 27.07 °C, 26.22 °C, and 27.03 °C, respectively. A significant positive correlation (r = 0.96 p > 0.005) was found between LST and urban areas with other infrastructures. Geographically weighted regression (GWR) outperformed with Adj R2 > 0.74, suggesting that the extent of an urban heat island (UHI) is strongly dependent on the settlements, LUC composition, size, and terrain of surrounding communities. Urban hotspots in the city were identified and validated using Google Earth imagery. The Ecological Evaluation Index (EEI) value was relatively low compared to other ecosystem-related units. EEI showed a continuous increase of six percent in the most negative categories, indicating an unstable environment. This study concludes that urbanization affects the city’s environment, and study findings would help to regulate the urban ecosystem in Beijing.

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“…UTFVI was used in this analysis for the environmental assessment of UHI zones in Beijing. UTFVI was estimated using the following Equation ( 11) [47][48][49]:…”

Section: Delineating Urban Hot Spot Areas (Uhs)mentioning

confidence: 99%

Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)

2023

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“…In any urban area, urbanization is necessary for a country's development, especially economic development. However, development also negatively affects natural resources and surface temperatures (Mohammad and Goswami, 2022). Furthermore, urban development in the river basin area leads to land use changes and affects water resources, which eventfully leads to climate change (Praskievicz and Chang, 2011).…”

Section: Introductionmentioning

confidence: 99%

Impact of Urbanization on the Vegetation Dynamic in Tama River Basin

Fatmawati,

Aurora,

Thong

et al. 2024

IRSPSD International

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Vegetation dynamic in river basins is significantly considered in environmental studies. However, the relationship between urbanization, vegetation change, and its driving factors are still lacking a connection in the previous study. Therefore, this study aimed to examine the impact of urban development on vegetation dynamics in the Tama River from 1990 to 2021 to enable future planning. In this study, vegetation dynamics were quantified with the Normal Difference Vegetation Index (NDVI) to provide information on the vegetation quality in the area. The regional climate and surface land uses were analyzed to determine the intensity of urban development. Regional Climate in spatial analysis can be computed with Land Surface Temperature (LST), whereas the surface conditions can be computed using Land Use Classification. The results showed that from 1990 to 2021, the NDVI trend continued to increase, whereas LST decreased. Furthermore, a positive and negative correlation was found between LST and NDVI in the Tama River Basin. This shows that changes in LST and NDVI are also influenced by other factors, such as seasonal change and socioeconomic factors. The overall vegetation trend shows an increasing trend in all seasons. This study's findings prove that the Tama River environmental management plan is a good example of a functional river rehabilitation plan. Thus, it is important to understand the spatial and temporal development of vegetation coverage and anticipate future patterns while comprehending climate shifts. This study will also provide recommendation recommendations for effective urban planning alongside rivers.

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“…Maps of the urban thermal field variance index (UTFVI) reveal a positive UHI phenomena, with the highest UTFVI zones occurring over developed area and none over the adjacent rural territory. The strongest UTFVI zone in the urban region expands during the forecasted years, especially during the warmer months (Mohammad and Goswami 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…The NDVI is widely considered to be the main remote-sensing index regulating the change in LST (Chen et al 2006 ; Mohammad and Goswami 2022 ; Saha et al 2022 ). The improvement in air pollution and the increase in humidity mainly reinforce the strength of the relationship between LST and NDVI (Govil et al 2019 , 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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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Predicting the impacts of urban development on seasonal urban thermal environment in Guwahati city, northeast India

Cited by 18 publications

References 31 publications

Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)

Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)

Impact of Urbanization on the Vegetation Dynamic in Tama River Basin

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

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