Investigating the Quantitative Impact of the Vegetation Indices on the Urban Thermal Comfort Based on Machine Learning: A Case Study of the Qinhuai River Basin, China

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106357 - 106357

Опубликована: Апрель 1, 2025

Язык: Английский

---

An Analysis of the Spatial and Temporal Evolution of the Urban Heat Island in the City of Zhengzhou Using MODIS Data

Applied Sciences, Год журнала: 2023, Номер 13(12), С. 7013 - 7013

Опубликована: Июнь 10, 2023

A rapid increase in urbanization has caused severe urban heat island (UHI) effects China over the past few years. Zhengzhou is one of emerging cities where residents are facing strong impact UHI. By utilizing MODIS data on land surface temperature (LST) and employing 3S technology, this study investigates UHI phenomenon a 10-year period (2012–2021), aiming to analyze spatio-temporal evolution characteristics effect associated cover changes. To best our knowledge, represents first attempt investigate annual seasonal changes different areas Zhengzhou. It noted that night-time, intensity stronger than daytime, which moderate weak areas. Seasonal variation showed autumn, intensity, followed by summer, lowest winter spring. The analysis reveals built-up (construction) exhibit highest LST, whereas forested water bodies have levels. findings can serve as reference for reducing increasing thermal comfort cities.

Язык: Английский

---

Impacts of coordinated development policies on urban heat islands in the Beijing-Tianjin-Hebei urban agglomeration, China

Sustainable Cities and Society, Год журнала: 2024, Номер 112, С. 105614 - 105614

Опубликована: Июль 2, 2024

Язык: Английский

---

A review of climatic impacts on water main deterioration

Urban Climate, Год журнала: 2023, Номер 49, С. 101552 - 101552

Опубликована: Май 1, 2023

Язык: Английский

---

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

Land, Год журнала: 2024, Номер 13(8), С. 1273 - 1273

Опубликована: Авг. 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.

Язык: Английский

---

Incorporating environmental considerations into infrastructure inequality evaluation using interpretable machine learning

Computers Environment and Urban Systems, Год журнала: 2025, Номер 120, С. 102301 - 102301

Опубликована: Май 3, 2025

Язык: Английский

---

Integrating multiple environmental variables to identify potential urban heat island risk areas based on the maxent model

Geo-spatial Information Science, Год журнала: 2025, Номер unknown, С. 1 - 15

Опубликована: Фев. 28, 2025

Язык: Английский

---

Identification of ventilation corridors through a simulation scenario of forest canopy density in the metropolitan area

Sustainable Cities and Society, Год журнала: 2023, Номер 95, С. 104595 - 104595

Опубликована: Апрель 20, 2023

Язык: Английский

---

Investigating the neighborhood effect of urban morphological metrics on summertime land surface temperature variations in Istanbul, Turkey

International Journal of Environmental Science and Technology, Год журнала: 2024, Номер 21(15), С. 9459 - 9480

Опубликована: Апрель 8, 2024

Язык: Английский

---

Implementation of a microclimate design model in the early design of new building projects – Case study Ecohof Noorderveer in the Netherlands

Urban Climate, Год журнала: 2024, Номер 55, С. 101956 - 101956

Опубликована: Май 1, 2024

Given the ongoing global urbanization and rise of heat, flooding, drought in cities, integration climate adaptive measures based on "ecosystem functions services" becomes imperative design. This study details implementation process a microclimate design model retrofitting housing project Ecohof Noorderveer Wormerveer, Netherlands. The model, which quantifies local urban heat mitigating through ecosystem functionalities, was incorporated into program requirements. followed research-by-design trajectory, involving iterative creative collaboration among all stakeholders, including future residents, municipality, water board, architect. research employed CFIR method to compare anticipated outcomes with actual results. findings suggest that introducing requirements proved beneficial for early stage. approach also deemed helpful, contingent careful involvement participants knowledge-sharing process. demonstrates significant potential scaling up standard development projects.

Язык: Английский

---