Land surface temperature responses to land use dynamics in urban areas of Doha, Qatar

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 104, P. 105273 - 105273

Published: Feb. 13, 2024

Rapid urbanization primarily converts naturally vegetated areas and pervious surfaces into impervious built-up areas, significantly transforming microclimates ecological dynamics. The surfaces, marked by their higher thermal conductivity, disrupt surface energy balance accumulate solar heat, subsequently elevating the land temperatures (LSTs). This study investigates impact of use cover changes on summer winter LSTs in Doha Al Dayeen municipalities Qatar, spanning from years 2000 to 2023, using remote sensing techniques Geographic Information Systems (GIS). analysis reveals a remarkable 343.16% increase area at expense previously existing desert lands water bodies. While Qatar's has high temperature, substituting such with exhibits notable rise temperatures. Additionally, reclamation also results elevated LSTs. LST data derived sources demonstrates an upward trend for contrasting winter. Specifically, mean increases 7.64°C (0.34°C annually), decreases 4.87°C (0.22°C annually). Notably, consistently recorded highest both seasons all observed years. A strong correlation was between patterns Normalized Difference Vegetation Index (NDVI), Water (NDWI), Built-up index (NDBI) Barrenness (NDBal). imply negative influence climate change urgent need urban planning mitigation measures counteract adverse effects increasing LSTs, particularly months, ensure human well-being resilience environments.

Language: Английский

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Assessment of flood susceptibility in Cachar district of Assam, India using GIS-based multi-criteria decision-making and analytical hierarchy process

Natural Hazards, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

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Dynamicity of Land Use/Land Cover (LULC) An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation (DMC) in India

Regional Sustainability, Journal Year: 2023, Volume and Issue: 4(2), P. 150 - 172

Published: May 18, 2023

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate peri-urban rural neighbourhoods, changing the landscape regions outside city fostering growth physical infrastructure. Using multi-temporal satellite images, dynamics Land Use/Land Cover (LULC) changes, impact urban on LULC regional environmental implications were investigated in neighbourhoods Durgapur Municipal Corporation India. study used different case studies highlight area's heterogeneity, as phenomenon change is not consistent. Landsat TM OLI-TIRS images 1991, 2001, 2011, 2021 analyze changes types. We relative deviation (RD), annual intensity (ACI), uniform (UI) show dynamicity types (agriculture land; built-up fallow vegetated mining area; water bodies) during 1991–2021. This also applied Decision-Making Trial Evaluation Laboratory (DEMATEL) measure sensitivity zones find out causes changes. According statistics, agriculture land, area increased by 51.7, 95.46, 24.79 ​km2, respectively, feom 1991 2021. results suggested that land had greatest surface temperature, whereas bodies showed lowest LST. Moreover, this looked at relationships among LST, spectral indices (Normalized Differenced Built-up Index (NDBI), Normalized Difference Vegetation (NDVI), Water (NDWI)), sensitivity. all have strongest association with indicating a far stronger influence indicated decreasing trends 4.26 0.43 km2/a, In summary, can help policy-makers predict increasing rate temperature for increase rapid expansion thus making effective planning decisions.

Language: Английский

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Dynamics of land use land cover and its impact on land surface temperature: a study of Faridabad District, India

GeoJournal, Journal Year: 2024, Volume and Issue: 89(1)

Published: Jan. 30, 2024

Language: Английский

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Characterizing urban growth and land surface temperature in the western himalayan cities of India using remote sensing and spatial metrics

Frontiers in Environmental Science, Journal Year: 2023, Volume and Issue: 11

Published: Jan. 19, 2023

Urban heat islands (UHI) are developing due to increasing urbanization and loss of vegetation in major cities India. Increased modifies the urban microclimate that leads significant land-use changes resulting surface conversion release, which poses serious risks human health, environment ecosystem Himalayan ecosystem. Hence, mitigating UHI becomes important requires a better understanding underlying associated biophysical processes. In study an attempt has been made demonstrate impact on land temperature (LST) Shimla Dehradun, capitals Western states, India using satellite data spatial metrics. The process was analyzed coverage patterns obtained from Landsat 5, 7, 8 corresponding sensors TM, ETM + , OLI. Built-up Non-Built-up areas were extracted parameters NDVI, NDBI, NDWI LST calculated capture different features growth. result indicated, built-up area increased 32.19 km 2 (2000) 68.37 (2016) Dehradun 12.38 29.47 during period, increase NDBI Reduction NDVI NDWI. Results showed hotspots largest areas, followed by water bodies. A correlation ( p < 0.05) observed between -NDVI, Spatial metrics at class landscape levels show growth 2000 2016 fragmented more heterogeneous. Identified trends their heterogeneous suggest is feasible estimate LST, with reasonable accuracy will likely have influence policy interventions.

Language: Английский

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Spatiotemporal dynamics of land use/land cover (LULC) changes and its impact on land surface temperature: A case study in New Town Kolkata, eastern India

Regional Sustainability, Journal Year: 2024, Volume and Issue: 5(2), P. 100138 - 100138

Published: June 1, 2024

Rapid urbanization creates complexity, results in dynamic changes land and environment, influences the surface temperature (LST) fast-developing cities. In this study, we examined impact of use/land cover (LULC) on LST determined intensity urban heat island (UHI) New Town Kolkata (a smart city), eastern India, from 1991 to 2021 at 10-a intervals using various series Landsat multi-spectral thermal bands. This study used maximum likelihood algorithm for image classification other methods like correlation analysis hotspot (Getis–Ord Gi* method) examine LULC environment. noticed that area percentage built-up increased rapidly 21.91% 45.63% during 1991–2021, with a positive change negative sparse vegetation. The mean significantly period (1991–2021), 16.31°C 22.48°C winter, 29.18°C 34.61°C summer, 19.18°C 27.11°C autumn. result showed impervious surfaces contribute higher LST, whereas vegetation helps decrease it. Poor ecological status has been found land, excellent water body. hot spot cold areas shifted their locations every decade due random changes. Even after became city, high observed. Overall, indicated patterns can influence appropriate planning is needed reduce LST. help policy-makers create sustainable

Language: Английский

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Harnessing Machine Learning Algorithms to Model the Association between Land Use/Land Cover Change and Heatwave Dynamics for Enhanced Environmental Management

Land, Journal Year: 2024, Volume and Issue: 13(8), P. 1273 - 1273

Published: Aug. 12, 2024

As we navigate the fast-paced era of urban expansion, integration machine learning (ML) and remote sensing (RS) has become a cornerstone in environmental management. This research, focusing on Silchar City, non-attainment city under National Clean Air Program (NCAP), leverages these advanced technologies to understand microclimate its implications health, resilience, sustainability built environment. The rise land surface temperature (LST) changes use cover (LULC) have been identified as key contributors thermal dynamics, particularly development heat islands (UHIs). Urban Thermal Field Variance Index (UTFVI) can assess influence UHIs, which is considered parameter for ecological quality assessment. research examines interlinkages among LST, dynamics City due substantial air temperature, poor quality, particulate matter PM2.5. Using Landsat satellite imagery, LULC maps were derived 2000, 2010, 2020 by applying supervised classification approach. LST was calculated converting band spectral radiance into brightness temperature. We utilized Cellular Automata (CA) Artificial Neural Networks (ANNs) project potential scenarios up year 2040. Over two-decade period from 2000 2020, observed 21% expansion built-up areas, primarily at expense vegetation agricultural lands. transformation contributed increased with over 10% area exceeding 25 °C compared just 1% 2000. CA model predicts areas will grow an additional 26% 2040, causing 4 °C. UTFVI analysis reveals declining comfort, worst affected zone projected expand 7 km2. increase PM2.5 aerosol optical depth past two decades further indicates deteriorating quality. study underscores ML RS management, providing valuable insights that guide policy formulation sustainable planning.

Language: Английский

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The Rohingya refugee crisis in Bangladesh: assessing the impact on land use patterns and land surface temperature using machine learning

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(6)

Published: May 18, 2024

Language: Английский

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Metropolitan expansion and rural change in the peri-urban edge Medellín - Rionegro (Colombia)

Journal of Urban Management, Journal Year: 2024, Volume and Issue: 13(3), P. 521 - 540

Published: June 13, 2024

This paper addresses the way in which expansion zones of metropolitan areas Medellín and Rionegro are currently moving from communal relations that marked their rural life to anonymous notions neighborliness gradually disappearing. Understanding urban as a social condition not only physical expression territory, but is also no longer opposite rural, nor it synonymous with city. The constitutes phenomenon where anonymity individuality privileged space. process takes place space part its heritage landscape unneighborly relations. We assume notion peri-urban limit undefinition extends periphery Aburrá Valley some hamlets Territorial Subsystem: Alto Grande - La Ramada, San Nicolas Valley; places disappearing give new dynamics. article theoretical contribution interpretation realities observed fringes many contemporary metropolises, because debate opens on ways understanding current urban-rural problems, suggests other perspectives for territorial planning based readings established there.

Language: Английский

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Factors influencing spatiotemporal variability of NO2 concentration in urban area: a GIS and remote sensing–based approach

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(2)

Published: Jan. 13, 2025

Language: Английский

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