Showing 141 - 160 results of 190 for search '"Macao"', query time: 0.05s Refine Results
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    Evaluation of the Production-Education Integration Performance of the High-Tech Industry: An Empirical Comparison between Three Urban Agglomerations in China by Quan Zhang, Zhen Zhang, Zhuomei Li, Sifeng Li, Tianzhen Tang

    Published 2021-01-01
    “…On this basis, the correlation-entropy composite matter-element (CECME) model and coupling coordination degree (CCD) model were introduced to empirically compare the PEI performance of the high-tech industry between Guangdong-Hong Kong-Macao (GHKM) Greater Bay Area, Beijing-Tianjin-Hebei (BTH) Urban Agglomeration, and Yangtze River Delta (YRD) Urban Agglomeration. …”
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  12. 152

    Spatial and Temporal Variation Characteristics of Forests and Analysis of Potential for Reconstruction of Water Conservation Forests in the Dongjiang River Basin from 1980 to 2020 by DAI Miaolin, LU Xiaoqi, ZANG Chuanfu, ZHU Ke, QIU Xintong, LUO Yiwen, ZHANG Weiqiang, GAN Xianhua

    Published 2023-01-01
    “…The Dongjiang River is the most important water source area in the Guangdong-Hong Kong-Macao Greater Bay Area,supplying water for the three mega-cities of Hong Kong,Shenzhen,and Guangzhou.The Dongjiang River Basin has abundant light and heat resources and sufficient rainfall,and it is one of the regions with the highest forest coverage rate in China.Since 1980,the land cover,especially the forest with the largest proportion in the Dongjiang River Basin,has changed significantly in the Dongjiang River Basin under the influence of natural factors,policy,and economic development.Therefore,how to scientifically plan and design afforestation projects and transform water conservation forests according to potential has become a hot social issue.The study was based on 30 m resolution land use and soil data of the Dongjiang River Basin from 1980 to 2020,and it combined with the data of Dongjiang River Source station and socio-economic index data.The study used spatial analysis and factor analysis to explore the spatial-temporal changes and driving mechanisms of forest cover in the Dongjiang River Basin from 1980 to 2020 and analyze the potential of water conservation forest reconstruction in the future.① From 1980 to 2020,the forest decreased continuously in the Dongjiang River Basin,with a total reduction of 998.81 km<sup>2</sup>.The changes were mainly concentrated in the south and north of the Dongjiang River Basin.In the northern part of the basin,a great deal of forest has been transformed into farmland,while in the southern part of the basin,a great deal of forest has been transformed into cities and countrysides or areas for industry,mining,and housing.② In the period of 1980—2020,the main factors affecting the change of forest area were the number of permanent residents,population density,GDP,output value of secondary and tertiary industries,output value of industry,agriculture,and forestry,total retail sales of social consumer goods,investment in fixed assets,and urban registered unemployment rate.③ The area for future reconstruction in the Dongjiang River Basin was 5 365 km<sup>2</sup>.The areas with high potential for reconstruction were mainly in the north and southeast parts of the basin.In the past 40 years,the forest area of the Dongjiang River Basin has continued to decrease and is strongly influenced by human activities.Water conservation forest has great potential to be transformed.…”
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    The spatial association network and driving factors of land use carbon emission efficiency in China: An investigation in the National Major Strategic Regions by LIU Min, CHEN Yinrong, WANG Jue, CHEN Kun, CHEN Yi

    Published 2024-12-01
    “…However, there were obvious differences among regions, Guangdong-Hong Kong-Macao Greater Bay Area have the highest average value of land use carbon emission efficiency, followed by the Yangtze River Delta region, the Yangtze River Economic Belt, Beijing-Tianjin-Hebei region and the Yellow River Basin region. (2) Over time,the structure of the overall networks of land use carbon emission efficiency in the National Major Strategic Regions has generally evolved towards densification, diversification and robustness. …”
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