Synergy level of pollution and carbon reduction in the Yangtze River Economic Belt: Spatial-temporal evolution characteristics and driving factors

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 98, P. 104859 - 104859

Published: Aug. 9, 2023

Language: Английский

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Identifying regional eco-environment quality and its influencing factors: A case study of an ecological civilization pilot zone in China

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 435, P. 140308 - 140308

Published: Dec. 19, 2023

Language: Английский

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Exploring non-linear urban vibrancy dynamics in emerging new towns: A case study of the Wuhan metropolitan area

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 112, P. 105580 - 105580

Published: June 12, 2024

Language: Английский

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Revealing disparities in different types of park visits based on cellphone signaling data in Guangzhou, China

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 351, P. 119969 - 119969

Published: Dec. 30, 2023

Language: Английский

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Spatial patterns and driving forces of urban vegetation greenness in China: A case study comprising 289 cities

Geography and sustainability, Journal Year: 2024, Volume and Issue: 5(3), P. 370 - 381

Published: March 22, 2024

Urban vegetation in China has changed substantially recent decades due to rapid urbanization and dramatic climate change. Nevertheless, the spatial differentiation of greenness among major cities its evolution process drivers are still poorly understood. This study examined patterns across 289 2000, 2005, 2010, 2015, 2018 by using autocorrelation analysis on Normalized Difference Vegetation Index (NDVI); then, influencing factors were analyzed optimal parameters-based geographical detector (OPGD) model 18 natural anthropogenic indicators. The findings demonstrated a noticeable rise overall selected during 2000–2018. northwest east exhibited rapidest slowest greening, respectively, six sub-regions. A significant positive correlation was detected between different periods, but strength weakened over time. hot very spots southern eastern gradually shifted southwest. While pattern urban is primarily influenced wind speed (WS) precipitation (PRE), interaction PRE gross domestic product (GDP) highest explanatory power. power most decreased and, conversely, influence generally increased. These emphasize variations multiple pattern, which should be taken into account understand adapt changing ecosystem.

Language: Английский

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Summer electricity consumption and its drivers in urban areas

Applied Geography, Journal Year: 2024, Volume and Issue: 164, P. 103223 - 103223

Published: Feb. 10, 2024

Language: Английский

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Crafting a jogging-friendly city: Harnessing big data to evaluate the runnability of urban streets

Journal of Transport Geography, Journal Year: 2024, Volume and Issue: 121, P. 104015 - 104015

Published: Oct. 1, 2024

Language: Английский

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Utilizing Multi-Source Geospatial Big Data to Examine How Environmental Factors Attract Outdoor Jogging Activities

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(16), P. 3056 - 3056

Published: Aug. 20, 2024

In the post-pandemic era, outdoor jogging has become an increasingly popular form of exercise due to growing emphasis on health. It is essential comprehensively analyze factors influencing spatial distribution activities and propose planning strategies with practical guidance. Using multi-source geospatial big data multiple models, this study constructs a comprehensive analytical framework examine association between environmental variables frequency in Guangzhou. Firstly, trajectory were collected from fitness app, potential selected based perspectives built environment, street perception, natural environment. For example, using street-view imagery, objective elements such as greenery subjective safety perception extracted human-centric perspective. Secondly, included three models: backward stepwise regression, optimal parameters-based geographical detector, geographically weighted regression (GWR) model. These models served, screen significant variables, identify synergistic effects among quantify heterogeneity effects, respectively. Finally, area was clustered results GWR model urban clear positions significance. The indicated following: (1) Factors related environment significantly influence distribution. (2) Public sports facilities, level greenery, identified key activities, representing aspects service (3) Specifically, each factor displayed variation. instance, facilities positively correlated city center. (4) Lastly, divided into four clusters, different local associative characteristics activities. zonal recommendations have implications for planners policymakers aiming create jogging-friendly environments.

Language: Английский

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Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring

Journal of Transport Geography, Journal Year: 2024, Volume and Issue: 118, P. 103930 - 103930

Published: June 1, 2024

Language: Английский

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Diurnal contrast of urban park cooling effects in a “Furnace city” using multi-source geospatial data and optimal parameters-based geographical detector model

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 114, P. 105765 - 105765

Published: Aug. 24, 2024

Language: Английский

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