Evaluation of Thermal Comfort Conditions in the Working Environments of Seasonal Agricultural Workers in Csa Koppen Climate Type DOI Open Access
Nihat Karakuş, Serdar Selim, Ceren Selim

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(20), P. 8903 - 8903

Published: Oct. 14, 2024

This study focuses on determining the thermal comfort conditions of seasonal agricultural workers during hot periods year when production is intense in Aksu/Türkiye region, which characterized by Csa climate type according to Köppen–Geiger classification. In this study, working open farmlands were evaluated ten-day, monthly, and for 6 months between 5:00 21:00 h using modified Physiological Equivalent Temperature (mPET) index Rayman Pro software their activity energy work. The results reveal that increased leads a decrease workers, mPET values engaged soil cultivation (Group II) are 2.1 2.9 °C higher than plant care harvesting I), Group II exposed more heat stress. I deteriorate 09:00 16:00 with 34.1 35.3 those 08:00 17:00 34.3 37.7 °C. context, daily comfortable time morning afternoon was found be 9 7 II. Overall, hours regions different types future studies will an important resource decision-makers developing strategies protect health increase productivity workers.

Language: Английский

Thermal hazards in urban spaces: A review of climate-resilient planning and design to reduce the heat stress DOI
Aman Gupta, Bhaskar De,

Sutapa Das

et al.

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102296 - 102296

Published: Jan. 25, 2025

Language: Английский

Citations

3
Spatiotemporal heterogeneity of the relationship between urban morphology and land surface temperature at a block scale DOI
Heilili Yelixiati, Luyi Tong,

Su Luo

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 113, P. 105711 - 105711

Published: July 30, 2024

Language: Английский

Citations

10
Investigating the Relationship between Spatial Morphology, Meteorological Factors, and Elderly People Responses in a Traditional Algerian Village DOI

Lilia Mahia,

Djihed Berkouk, Tallal Abdel Karim Bouzir

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106212 - 106212

Published: Feb. 1, 2025

Language: Английский

Citations

1
Assessing Urban Morphology's Impact on Solar Potential of High-Rise Facades in Hong Kong Using Machine Learning: An Application for FIPV Optimization DOI
Lulu Tao, Mengmeng Wang, Changying Xiang

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 117, P. 105978 - 105978

Published: Nov. 13, 2024

Language: Английский

Citations

6
Quantifying the Influence of Different Block Types on the Urban Heat Risk in High-Density Cities DOI Creative Commons

Binwei Zou,

Chengliang Fan, Jianjun Li

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(7), P. 2131 - 2131

Published: July 11, 2024

Urbanization and climate change have led to rising urban temperatures, increasing heat-related health risks. Assessing heat risk is crucial for understanding mitigating these Many studies often overlook the impact of block types on risk, which limits development mitigation strategies during planning. This study aims investigate influence various spatial factors at scale. Firstly, a GIS approach was used generate Local Climate Zones (LCZ) map, represents different types. Secondly, assessment model developed using hazard, exposure, vulnerability indicators. Thirdly, demonstrated in Guangzhou, high-density city China, distribution among An XGBoost analyze risk. Results revealed significant variations susceptibility Specifically, 33.9% LCZ 1–4 areas were classified as being high-risk level, while only 23.8% 6–9 fell into this level. In addition, pervious surface fraction (PSF) had strongest followed by height roughness elements (HRE), building (BSF), sky view factor (SVF). SVF PSF negative HRE BSF positive effect. The provides valuable insights characteristics influenced morphologies. will assist formulating reasonable measures planning level future.

Language: Английский

Citations

5
Decompose-deep-recompose models and genetic algorithm based optimal ensemble method (GAE) to enhance the air temperature forecasting of world’s major urban cities DOI
Vipin Kumar

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: Feb. 1, 2025

Language: Английский

Citations

0
Pix2Pix-Based Modelling of Urban Morphogenesis and Its Linkage to Local Climate Zones and Urban Heat Islands in Chinese Megacities DOI Creative Commons
Mo Wang,

Ziheng Xiong,

Jiayu Zhao

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 755 - 755

Published: April 1, 2025

Accelerated urbanization in China poses significant challenges for developing urban planning strategies that are responsive to diverse climatic conditions. This demands a sophisticated understanding of the complex interactions between 3D forms and local climate dynamics. study employed Conditional Generative Adversarial Network (cGAN) Pix2Pix algorithm as predictive model simulate morphologies aligned with Local Climate Zone (LCZ) classifications. The research framework comprises four key components: (1) acquisition LCZ maps form samples from selected Chinese megacities training, utilizing datasets such World Cover database, RiverMap’s building outlines, integrated satellite data Landsat 8, Sentinel-1, Sentinel-2; (2) evaluation algorithm’s performance simulating environments; (3) generation models demonstrate model’s capability automated morphology construction, specific potential examining heat island effects; (4) examination adaptability contexts projecting morphological transformations. By integrating inputs eight representative metropolises, efficacy was assessed both qualitatively quantitatively, achieving an RMSE 0.187, R2 0.78, PSNR 14.592. In generalized test prediction through classification, exemplified by case Zhuhai, results indicated effectiveness categorizing types. conclusion, integration metropolises further confirmed climate-adaptive planning. findings this underscore generative algorithms based on types accurately forecasting development, thereby making contributions sustainable climate-responsive

Language: Английский

Citations

0
A Data-Driven Approach for Urban Heat Island Predictions: Rethinking the Evaluation Metrics and Data Preprocessing DOI Creative Commons

Berk Kıvılcım,

Patrick Erik Bradley

Urban Science, Journal Year: 2025, Volume and Issue: 9(5), P. 151 - 151

Published: May 6, 2025

A 2D raster data representing building volumes of each grids are derived from 3D vector-format urban for use in machine learning applications. Since the task is to explore patterns, i.e., heat islands, Gaussian blurring implemented on these generated before training process. This strengthens visual capturing spatial relationships, and as a result correlation rate between air temperature volume also increased. After model training, prediction results not simply evaluated with most widely used shallow metrics like Mean Square Error (MSE), but thanks format input output results, some image similarity such Structural Similarity Index Measure (SSIM) Learned Perceptual Image Patch (LPIPS) that able detect consider relations during evaluation interpretation process, because their higher usefulness mimicking human judgements. The trained models Random Forest XGBoost methods which capable predicting distribution by using information compared. By doing so, this research aims assist planners incorporating environmental parameters into planning strategies, thereby facilitating more sustainable inhabitable environments.

Language: Английский

Citations

0
Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification DOI Open Access

Binwei Zou,

Yuanyue Nie,

Rude Liu

et al.

Water, Journal Year: 2024, Volume and Issue: 16(17), P. 2464 - 2464

Published: Aug. 30, 2024

Rapid urbanization has altered the natural surface properties and spatial patterns, increasing risk of urban waterlogging. Assessing probability waterlogging is crucial for preventing mitigating environmental risks associated with This study aims to evaluate impact different morphologies on risk. The proposed assessment framework was demonstrated in Guangzhou, a high-density city China. Firstly, weight naive Bayes model employed map Guangzhou. Secondly, World Urban Database Access Portal Tools (WUDAPT)-based method used create local climate zone (LCZ) Then, range proportion levels were analyzed across LCZs. Finally, Theil index measure disparity exposure among residents. results indicate that 16.29% area Guangzhou at Specifically, 13.06% LCZ 2 classified as high risk, followed by 1, 8, 10, proportions 11.42%, 8.37%, 6.26%, respectively. Liwan District highest flood level 0.975, Haizhu, Yuexiu, Baiyun. overall 0.30, difference between administrative districts (0.13) being smaller than within (0.17). These findings provide valuable insights future mitigation help adopting effective reduction strategies planning level.

Language: Английский

Citations

3
Impact of green space patterns on PM2.5 levels: A local climate zone perspective DOI
Ming Chen,

Z.F. Ren,

Shibo Bi

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 143975 - 143975

Published: Oct. 1, 2024

Language: Английский

Citations

2