Promoting sustainable development by mitigation of natural habitat quality decline through multifunctional urban land use: Insights from a multi-scenario simulation

Sustainable Cities and Society, Год журнала: 2024, Номер 110, С. 105563 - 105563

Опубликована: Май 31, 2024

Язык: Английский

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Remote high-speed rail stations, urban land supply, and the emergence of new economic activities

Transportation Research Part A Policy and Practice, Год журнала: 2024, Номер 189, С. 104226 - 104226

Опубликована: Авг. 29, 2024

Язык: Английский

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Spatiotemporal Evolution and Prediction of Land Use and Carbon Stock in Shanghai

Land, Год журнала: 2024, Номер 13(3), С. 267 - 267

Опубликована: Фев. 21, 2024

Soil organic carbon (SOC) constitutes a critical component of reservoirs within terrestrial ecosystems. The ramifications urban land use transitions on SOC dynamics, particularly in rapidly urbanizing regions such as Shanghai, remain insufficiently elucidated. This investigation synergizes predictive change model (Logistic-CA-Markov) with an ecosystem service quantification framework (InVEST), aiming to delineate the interplay between variability and Land Use Cover Change (LUCC) under natural development ecological protection scenarios. Empirical observations from 2010 2020 reveal contraction Shanghai’s agricultural 34,912.76 hectares, juxtaposed expansion built-up areas 36,048.24 hectares. Projections for 2030 scenario indicate moderated sprawl, reducing area by 13,518 hectares relative scenario. Notably, net sequestration capacity Shanghai is anticipated diminish approximately 0.418 million tons 2030. trend observed both considered scenarios, forecasting cumulative reduction stocks exceeding 1 pathway portends more pronounced accelerated depletion reserves. Although conservation measures show potential decelerate this loss, they appear insufficient reverse ongoing decline stocks. study advocates strategic planning interventions focused constraining growth building densities augmenting preservation management eco-lands. Such are imperative bolstering capacity.

Язык: Английский

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Evaluating urban–rural gradients and urban forms in metropolitan areas: a local climate zone approach with future spatial simulation

Sustainable Cities and Society, Год журнала: 2024, Номер 112, С. 105636 - 105636

Опубликована: Июль 2, 2024

Язык: Английский

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Dissolved Oxygen Concentration Prediction in the Pearl River Estuary with Deep Learning for Driving Factors Identification: Temperature, pH, Conductivity, and Ammonia Nitrogen

Water, Год журнала: 2024, Номер 16(21), С. 3090 - 3090

Опубликована: Окт. 29, 2024

Predicting the dissolved oxygen concentration and identifying its driving factors are essential for improved prevention management of anoxia in estuaries. However, complex hydrodynamic conditions limitations traditional methods result challenges identification low (DO) phenomenon. The objective our study is to develop a robust deep learning model using four-year situ data collected from an automatic water quality monitoring station (AWQMS) estuary, accurate quantification influencing DO levels. Mitigations hypoxia were observed during initial two years, but subsequent decline concentrations was witnessed recently. periodicity Pearl River Estuary reduced with increase hypoxic intensity. Maximal information coefficient (MIC) extreme gradient boosting (XGBoost) employed determine significance input variables, which subsequently validated by long- short-term memory networks (LSTMs). contributing problem shown as temperature, pH, conductivity, NH4+-N concentrations. Notably, evaluation index values hybrid MAPE = 0.0887 R2 0.9208, have been compared LSTM about 99.34% reduction 16.56% improvement, indicating that MixUp-LSTM capable effectively capturing nonlinear relationships between other indicators. Based on existing literature, three statistical four machine models also performed compare proposed model, outperformed terms prediction accuracy robustness. Overall, successful deoxygenation phenomenon would important implications governance regulation

Язык: Английский

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Revealing the dynamic effects of land cover change on land surface temperature in global major bay areas

Building and Environment, Год журнала: 2024, Номер 267, С. 112266 - 112266

Опубликована: Ноя. 4, 2024

Язык: Английский

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Spatial heterogeneity and driving mechanism of urban climbing and its impact on regional environment in varied landform types in the middle reaches of the Yellow River

Journal of Mountain Science, Год журнала: 2024, Номер 21(10), С. 3413 - 3433

Опубликована: Окт. 1, 2024

Язык: Английский

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From global to national: The role of urban agglomerations in China’s new development paradigm

PLoS ONE, Год журнала: 2024, Номер 19(6), С. e0305594 - e0305594

Опубликована: Июнь 17, 2024

Urban agglomerations (UAs), which serve as pivotal hubs for economic and innovative convergence, play a crucial role in enhancing internal circulation strengthening external linkages. This study utilizes the China city-level multi-regional input-output tables, incorporating Dagum Gini coefficient kernel density estimation methods, to perform thorough quantitative analysis. Disparities within national global value chains ("dual chains") of Chinese UAs from 2012 2017 were assessed. Additionally, logarithmic mean Divisia index (LMDI) method was applied disaggregate drivers both intermediate inputs (NII GII). The study’s key findings include following: (1) chain (NVC) exhibits robust growth, contrasting with decline (GVC). (2) inter-UA disparity contribution rate significantly surpasses combined rates intra-UA super-variation density. (3) Distinct evolutionary peak trends are discerned among various "dual chains", highlighting diverse spatial polarization characteristics expansiveness. (4) growth NVC has transitioned negative positive impact on NII, while GVC substantially counteracted GII growth. Economic demographic factors notably drive improvements NII GII, whereas efficiency outflows presents driving effect. Based these findings, this offers strategic recommendations facilitate effective integration into new development paradigm, thereby providing scientific basis related decision-making processes.

Язык: Английский

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Quantitative spatiotemporal evolution of large urban agglomeration expansion based on 1995–2020 nighttime light and spectral data

Ecological Informatics, Год журнала: 2024, Номер unknown, С. 102824 - 102824

Опубликована: Сен. 1, 2024

Язык: Английский

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The Prediction of Urban Growth Boundary based on the ANN-CA Model: An Application to Guangzhou

Heliyon, Год журнала: 2024, Номер 10(19), С. e38052 - e38052

Опубликована: Сен. 20, 2024

Urban growth boundary (UGB) delineation is critical not only for China's urban planning policies, such as the "three control lines" of Ministry Natural Resources, but also addressing global challenges related to sustainable development. This study contributes international discourse on management by developing an innovative artificial neural network-cellular automata (ANN-CA) model, tailored cities experiencing rapid expansion. Using Guangzhou a case study, we constructed impact factor model that incorporates wide range factors, including spatial terrain, natural environment, current land classification, and industrial economic conditions, along with layout modern service networks. The ANN-CA was then employed simulate expansion UGB year 2030 under various constraints, strict protection zones development scenarios. Our findings indicate between 2020 2030, Nansha, Panyu, Zengcheng districts will witness most significant expansion, respective area increases 13.81 km

Язык: Английский

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