Development of an Active Transportation Framework Model for Sustainable Urban Development DOI Open Access
George Papageorgiou, Elena Tsappi

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7546 - 7546

Published: Aug. 31, 2024

Active transportation, with simple mobility modes such as walking and cycling, could be pivotal in addressing multiple sustainability challenges related to socio-economic, environmental, public health issues. This paper investigates the facilitators for active transportation assesses its impact on health, well-being, urban sustainability. As a result, multidimensional conceptual framework is developed analyze determinants influencing individuals’ propensity engage thereby lead sustainable, high-quality way of life. Through an extensive review relevant literature, key elements accessibility, social inclusion are identified, their potential investigated. Findings suggest that interrelationships between factors enhanced infrastructure, safety measures, improved accessibility would significantly encourage usage. The proposed argues positive association outcomes, contributing sustainable environments. Furthermore, it advocated changing attitudes mindsets achieved by planning policy reforms supporting well effectively communicating benefits individuals, economy, society at large. Comprehensive strategies, which include improvements design increased awareness establish paradigm shift promoting higher quality life through healthy, active, lifestyle.

Language: Английский

Addressing the impact of land use land cover changes on land surface temperature using machine learning algorithms DOI Creative Commons
Sajid Ullah,

Xiuchen Qiao,

Mohsin Abbas

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 13, 2024

Over the past two and a half decades, rapid urbanization has led to significant land use cover (LULC) changes in Kabul province, Afghanistan. To assess impact of LULC on surface temperature (LST), province was divided into four classes applying Support Vector Machine (SVM) algorithm using Landsat satellite images from 1998 2022. The LST assessed data thermal band. Cellular Automata-Logistic Regression (CA-LR) model applied predict future patterns for 2034 2046. Results showed classes, as built-up areas increased about 9.37%, while bare soil vegetation decreased 7.20% 2.35%, respectively, analysis annual revealed that highest mean LST, followed by vegetation. simulation results indicate an expected increase 17.08% 23.10% 2046, compared 11.23% Similarly, indicated area experiencing class (≥ 32 °C) is 27.01% 43.05% 11.21% increases considerably decreases, revealing direct link between rising temperatures.

Language: Английский

Citations

24
Prediction of surface urban heat island based on predicted consequences of urban sprawl using deep learning: A way forward for a sustainable environment DOI Creative Commons

Shun Fu,

L Wang,

Umer Khalil

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2024, Volume and Issue: 135, P. 103682 - 103682

Published: July 23, 2024

Language: Английский

Citations

17
From resources to resilience: Understanding the impact of standard of living and energy consumption on natural resource rent in Asia DOI Creative Commons
Muhammad Imran, Muhammad Tufail, Mo Chen

et al.

Energy Strategy Reviews, Journal Year: 2025, Volume and Issue: 57, P. 101590 - 101590

Published: Jan. 1, 2025

Language: Английский

Citations

5
Evaluation of Land Use Land Cover Changes in Response to Land Surface Temperature With Satellite Indices and Remote Sensing Data DOI
Qun Zhao, Muhammad Haseeb, Xinyao Wang

et al.

Rangeland Ecology & Management, Journal Year: 2024, Volume and Issue: 96, P. 183 - 196

Published: Aug. 2, 2024

Language: Английский

Citations

11
Predicting soil erosion risk using the revised universal soil loss equation (RUSLE) model and geo‐spatial methods DOI
Syed Ali Asad Naqvi, Aqil Tariq,

Mudsar Shahzad

et al.

Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(8)

Published: Aug. 1, 2024

Abstract Anthropogenic activities like overgrazing, deforestation and mismanaged land use accelerate soil erosion (SE), causing nutritional organic matter loss. In this study, we predicted the annual rate of loss in Salt Range, extending south from Pothohar plateau, Pakistan, using Revised Universal Soil Loss Equation (RUSLE). The RUSLE model parameters probability zones were estimated remote sensing Geo‐Spatial methods. average rates calculated by considering five geo‐environmental factors, that is, slope length steepness (LS), rainfall erosivity (R), cover management (C), erodibility (K), conservation practice (P) range 0–559 527, 1404–4431, 0–1, −0.14 to 1.64, 0.2–122 respectively. This research determined yearly SE Range varies over 50 above 350 . distribution area across different reveals a small portion (2.11%) is classified as High, moderate (7.13%) falls under category Moderate, while majority (90.7%) Low terms proneness towards erosion. devoid vegetation characterized steep slopes especially prone SE. highly vulnerable risk due climatic variations improper practices. result provides spatial salt range, utilized for planning processes at policy level among decision‐makers land‐use planners.

Language: Английский

Citations

9
Monitoring and prediction of the LULC change dynamics using time series remote sensing data with Google Earth Engine DOI
Muhammad Farhan, Taixia Wu, Muhammad Amin

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2024, Volume and Issue: 136, P. 103689 - 103689

Published: Aug. 9, 2024

Language: Английский

Citations

8
Changing spatial inclusion of migrants in Chinese cities: How housing matters DOI Creative Commons
Yunzheng Zhang, Fubin Luo, Yilong Dai

et al.

Habitat International, Journal Year: 2025, Volume and Issue: 157, P. 103319 - 103319

Published: Feb. 5, 2025

Language: Английский

Citations

1
Blueprint for progress: Understanding the driving forces of BIM adoption in Kingdom of Saudi Arabia (KSA) construction industry DOI Creative Commons
Muzaffar Iqbal,

Irfan Ullah,

Heba Mohamed Ahmed Abdou

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0313135 - e0313135

Published: Feb. 10, 2025

Building information modeling (BIM) as a virtual and digital mode of representing construction activities gained significant attention facilitated projects. Nevertheless, many driving forces (DFs) trigger the adoption BIM. Different kinds studies have been conducted regarding DFs BIM in developed countries. However, few classified technology developing countries such Kingdom Saudi Arabia (KSA). A range previous literature identified these different context, but there is need to answer two main questions. First, what could influence sector (KSA); second, be possible framework prioritize DFs. Therefore, Fuzzy Delphi Methodology (FDM), Interpretive structural (ISM), MICMAC were applied Study results highlight that ’Reduced cycle time design process’ ’Efficient planning management’, are This study first employ hybrid FDM, ISM, approach evaluate implementation KSA context. informs policymakers industry practitioners (KSA) develop targeted strategies for effective adoption. enhances collaboration communication among stakeholders by understanding their interrelationships.

Language: Английский

Citations

1
Predicting Land Use Land Cover Dynamics and Land Surface Temperature Changes Using CA-Markov-Chain Models in Islamabad, Pakistan (1992–2042) DOI Creative Commons

Muhammad Farhan,

Taixia Wu,

Sahrish Anwar

et al.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2024, Volume and Issue: 17, P. 16255 - 16271

Published: Jan. 1, 2024

Language: Английский

Citations

5
Assessment of Urban Environmental Quality by Socioeconomic and Environmental Variables Using Open‐Source Datasets DOI

Tan Lingye,

Nayyer Saleem, Rana Waqar Aslam

et al.

Transactions in GIS, Journal Year: 2024, Volume and Issue: 28(7), P. 2526 - 2544

Published: Sept. 22, 2024

ABSTRACT In this era of rapid development, environmental quality is an essential aspect sustainable development. A healthy urban environment supports, regulates, and provides livable conditions. areas, considerably affected by socioeconomic factors such as population expansion economic For decision‐making, it also significant for stakeholders policymakers to understand the impact on quality. While previous studies have examined quality, they often focused single cities or limited parameters. This research addresses these limitations conducting a comparative analysis two major Asian with similar demographic features, utilizing comprehensive set variables. Our innovative approach combines open‐source datasets advanced remote sensing techniques provide more holistic assessment over decades. We analyzed last decades selected parameters: surface greenness, moisture, land temperature. Lahore (Pakistan) Wuhan (China) were having approximately same features. Correlation matrix has been used assess relationship between variables social‐economic variables: carbon emission. coefficient indicated that correlates negatively greenness moisture both (−0.67 −0.71) District (−0.5 −0.75), respectively, while had positive relation temperature: 0.65 0.57 District, respectively. These effects are prominent within 10 km distance from city center, where substantial observed during time window.

Language: Английский

Citations

5