Assessing Land Footprint of Urban Agglomeration and Underlying Socioeconomic Drivers

Land, Год журнала: 2025, Номер 14(3), С. 580 - 580

Опубликована: Март 10, 2025

The maintenance of critical natural capital stocks lays a basis for achieving sustainable development across the globe. However, rapid socioeconomic in Yangtze River Delta (YRD) region China has been somewhat conflict with sustainability capital, particularly domain land use. This, however, remains largely underexplored 41 cities partnering YRD. aim this paper is to bring clarity as YRD by using an improved three-dimensional footprint model, well explore underlying drivers spatial econometric models. We find that use most environmentally unsustainable long period time. Cropland recognized major source flows, experiencing low depletion stocks. By contrast, grazing found have poor appropriation suffering from severe Overall, both flows and at aggregate level remain relatively stable but geographically uneven, rich west north YRD, intensive northwest northeast In addition, proportion primary industry added value GDP per capita disposable income are identified YRD’s environmental unsustainability Our findings call renewed policies pinpoint land, fishing grounds cropland enable societal prosperity without accelerating capital.

Язык: Английский

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Spatiotemporal evolution and decoupling effects of sustainable water resources utilization in the Yellow River Basin: Based on three-dimensional water ecological footprint

Journal of Environmental Management, Год журнала: 2024, Номер 366, С. 121846 - 121846

Опубликована: Июль 24, 2024

Язык: Английский

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Coupling coordination evaluation of ecology and economy and development optimization at town-scale

Journal of Cleaner Production, Год журнала: 2024, Номер 447, С. 141581 - 141581

Опубликована: Фев. 29, 2024

Язык: Английский

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Unraveling nonlinear effects of environment features on green view index using multiple data sources and explainable machine learning

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Дек. 4, 2024

Urban greening plays a crucial role in maintaining environmental sustainability and enhancing people's well-being. However, limited by the shortcomings of traditional methods, studying heterogeneity nonlinearity between factors green view index (GVI) still faces many challenges. To address concerns nonlinearity, spatial heterogeneity, interpretability, an interpretable machine learning framework incorporating Geographically Weighted Random Forest (GWRF) model SHapley Additive exPlanation (Shap) is proposed this paper. In paper, we combine multi-source big data, such as Baidu Street View data remote sensing images, utilize semantic segmentation models geographic processing techniques to study global local interpretation Beijing region with GVI key indicator. Our research results show that: (1) Within Sixth Ring Road Beijing, shows significant clustering phenomenon positive correlation linkage, at same time exhibits differences; (2) Among variables, increase coverage rate has most effect on GVI, while building density strong negative GVI; (3) The performance GWRF predicting excellent far exceeds that comparison models.; (4) Whether it rate, urban built environment or socioeconomic factors, their influence non-linear characteristics certain threshold effect. With help these influences explicit effects, quantitative analyses are provided, which can assist planners making more scientific rational decisions when allocating resources.

Язык: Английский

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Assessment of green sustainable development in plateau lakeside cities

Frontiers in Ecology and Evolution, Год журнала: 2024, Номер 12

Опубликована: Июль 15, 2024

Introduction Green sustainable development is an important part of the United Nations Sustainable Development Goals (SDGs) and China’s ecological civilization construction. Methods This paper combines characteristics lakeside cities, gives full play to advantages modern remote sensing technology collect indicators related green adopts Analytic Hierarchy Process (AHP) CRiteria Importance Through Inter-criteria Correlation (CRITIC) subjective objective weighting methods difference coefficient method determine weights indicators, evaluates a typical city Kunming for more than 30 years, analyzes influencing factors using gray degree correlation. Results The results show following: (1) From 1990 2021, level in urban area around Dianchi Lake fluctuated stages, with overall upward trend, index increased from 0.25 0.5 2021. (2) variance determined by optimization model can be better compromise between massive occupation wetlands arable land lake expansion has become major factor city, combined weight 10.30% 8.79%, respectively. (3) population economic scale are currently main drivers correlation 0.843 0.769, Discussion growth plays pivotal role driving while potential impact tourism should also considered.

Язык: Английский

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Unraveling nonlinear effects of environment features on green view index using multiple data sources and explainable machine learning

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Авг. 21, 2024

Urban greening plays a crucial role in maintaining environmental sustainability and enhancing people's well-being. However, limited by the shortcomings of traditional methods, studying heterogeneity nonlinearity between factors green view index (GVI) still faces many challenges. To address concerns nonlinearity, spatial heterogeneity, interpretability, an interpretable machine learning framework incorporating Geographically Weighted Random Forest (GWRF) model SHapley Additive exPlanation (Shap) is proposed this paper. In paper, we combine multi-source big data, such as Google Street View data remote sensing images, utilize semantic segmentation models geographic processing techniques to study global local interpretation Beijing region with GVI key indicator. Our research results show that: (1) Within Sixth Ring Road Beijing, shows significant clustering phenomenon positive correlation linkage, at same time exhibits differences; (2) Among variables, increase vegetation coverage has most effect on GVI, while building density strong negative GVI; (3) Whether it cover rate, urban built environment or socio-economic factors, their influence non-linear characteristics certain threshold effect; (4) The performance GWRF simulating predicting excellent far exceeds that existing models. Based these findings, can provide important reference for planners enhance greening.

Язык: Английский

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SUHI evolution characteristics and influencing mechanism of eight furnace cities in middle and lower reaches of Yangtze River, China

Urban Climate, Год журнала: 2024, Номер 58, С. 102182 - 102182

Опубликована: Окт. 29, 2024

Язык: Английский

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