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3 results for “urban economic growth”
Dataset of 'Unequal Impacts of Urban Industrial Land Expansion on Economic Growth and Carbon Dioxide Emissions'
<p>This dataset is an integral component of the research presented in 'Unequal Impacts of Urban Industrial Land Expansion on Economic Growth and Carbon Dioxide Emissions' by Yoo et al., 2024. It encompasses:</p> <p><strong>1. Links to two publicly accessible datasets:</strong></p> <ul> <li>Industrial land mapping data derived from Google Earth Engine.</li> <li>Data employed in a longitudinal analysis to evaluate the effects of urban industrial land expansion on CO2 emissions and economic growth.</li> </ul> <p><strong>2. Comprehensive input data </strong>utilized in Mixed Effects Random Forest (MERF) longitudinal modeling to assess the separate impacts on CO2 emissions and economic growth in developing and developed regions.</p> <p><strong>3. Python scripts provided for:</strong></p> <ul> <li>Executing MERF longitudinal modeling.</li> <li>Computing SHAP (SHapley Additive exPlanations) values to interpret the contributions of each predictor variable.</li> <li>Generating figures that visually summarize the findings for both developing and developed regions.</li> </ul> <p> </p> <p><strong>The manuscript is available</strong> at: <a href="https://doi.org/10.1038/s43247-024-01375-x"><span>https://doi.org/10.1038/s43247-024-01375-x</span></a></p> <div> <div> </div> </div>
Data from: The inverted U-shaped effect of urban hotspots spatial compactness on urban economic growth
The compact city, as a sustainable concept, is intended to augment the efficiency of urban function. However, previous studies have concentrated more on morphology than on structure. The present study focuses on urban structural elements, i.e., urban hotspots consisting of high-density and high-intensity socioeconomic zones, and explores the economic performance associated with their spatial structure. We use nighttime luminosity (NTL) data and the Loubar method to identify and extract the hotspot and ultimately draw two conclusions. First, with population increasing, the hotspot number scales sublinearly with an exponent of approximately 0.50~0.55, regardless of the location in China, the EU or the US, while the intersect values are totally different, which is mainly due to different economic developmental level. Secondly, we demonstrate that the compactness of hotspots imposes an inverted U-shaped influence on economic growth, which implies that an optimal compactness coefficient does exist. These findings are helpful for urban planning.
Data from: The inverted U-shaped effect of urban hotspots spatial compactness on urban economic growth
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