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Multi-mechanism Orogenic Model of the Su-Jiao Orogenic Belt 总被引：1，自引：0，他引：1
FAN Jintao CHEN Jiongda CHEN Huogen Geological Survey of Jiangsu Province Nanjing Jianesu 《《地质学报》英文版》2000,74(2):201-206
The Su-Jiao orogenic belt is the eastern part of the Central Mountain System of China. Recent studies on its erogenic system indicate that the Su-Jiao erogenic belt is a complex orogenic belt which suffered at least 3 orogenies of different mechanisms in the Mesoproterozoic, Neoproterozoic and Triassic respectively. The Meso-Neoproterozoic orogenies belong to the Wilson cycle on the plate margins. The belt is a part of the Late Mesoproterozoic supercontinent Rodinia. The Triassic orogeny belongs to the re-orogeny of the non-Wilson cycle. Delamina-tion of mountain roots occurred after both the Wilson and non-Wilson cycles in the Su-Jiao erogenic belt. The large-amplitude isostatic uplift of mountains, magmatic activities and basin-forming and mountain-making in the upper crust, all indicate the general significance of delamination in the development of erogenic belts. 相似文献
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采用2010~2015年汶川地区GNSS震后形变资料,利用有限元法建立三维震后粘弹性松弛模型,通过二维格网搜索获得龙门山断裂带上盘最佳弹性层厚度和中下地壳最佳粘滞系数,并分析汶川地震震后2~7 a粘弹性松弛影响下的震后形变特征;然后采用2008~2009年GNSS震后形变资料,根据最佳参数建立粘弹性松弛与余滑组合模型,并与单一余滑模型进行对比,分析汶川地震震后1 a内的形变特征。研究结果表明,根据模拟值计算得到青藏高原东部弹性层的最佳厚度为25 km,中下地壳的最佳粘滞系数为4.0×1018 Pa·s;震后1 a内组合模型的拟合效果优于单一余滑模型,其中余滑形变占主要成分。 相似文献
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This paper investigates regional inequality and development in China's Guangdong province by employing the multi-scale and multi-mechanism framework. The study further examines the relationship between space, scale, and regional inequality by applying a spatial filtering method that eliminates spatial dependence of the data and quantifies the extent to which spatial effects have contributed to regional inequality at multiple scales. The results suggest that over 90% of the divide between the core of the Pearl River Delta (PRD) and the periphery areas of Guangdong province can be explained by the effect of strengthening spatial dependence. By incorporating spatial filters in space-time models, we also reveal the space-time and core-periphery heterogeneities of development mechanisms. Our study confirms that the integration of a multi-scale and multi-mechanism framework and rigorous spatial analysis methods, such as spatial filtering and space-time modeling, helps better understand the complexity of regional development in China. 相似文献
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Global warming has been one of the major concerns behind the world's high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the world's economic and social development, as well as the heated debate of the research at home and abroad in recent years. Based on the energy consumption, integrated with the "Top-Down" life cycle approach and geographically weighted regression(GWR) model, this paper analyzed the spatial differences and multi-mechanism of carbon footprint in provincial China in 2010. Firstly, this study calculated the amount of carbon footprint of each province using "Top-Down" life cycle approach and found that there were significant differences of carbon footprint and per capita carbon footprint in provincial China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scales; the provinces with higher per capita carbon footprint are mainly distributed in central cities such as Beijing, Shanghai and energy-rich regions and heavy chemical bases. Secondly, with the aid of GIS and spatial analysis model(GWR model), this paper had unfolded that the expansion of economic scale is the main driver of the rapid growth of carbon footprint. The growth of population and urbanization also acted as promoting factors for the increase of the carbon footprint. Energy structure had no considerable promoting effect for the increase of the carbon footprint. Improving energy efficiency is the most important factor to inhibit the growing carbon footprint. Thirdly, developing low-carbon economies and low-carbon industries, as well as advocating low-carbon city construction and improving carbon efficiency would be the primary approaches to inhibit the rapid growth of carbon footprint. Moderately controlling the economic scale and population size would also be required to alleviate carbon footprint. Meanwhile, environmental protection and construction of low-carbon cities would evoke extensive attention in the process of urbanization. 相似文献
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东北三省区域经济差异的多尺度与多机制研究 总被引：1，自引：2，他引：1
基于多尺度与多机制分析框架,采用差异测度及尺度分解指数、ESDA及回归分析等方法,从省级、地级、县级3个尺度分析了2003-2016年东北三省经济差异的时空特征及驱动机制。研究表明：① 各尺度区域经济绝对和相对差异均较为明显,呈县级>地级>省级的尺度格局;经济差异总体呈下降趋势,各尺度差异及对总差异贡献率呈市间差异>市内差异>省间差异。② 各尺度区域经济发展呈显著空间集聚特征,关联类型以正相关为主且低-低（LL）型占主导地位,越小的尺度空间依赖性和异质性越明显。③ 区域经济发展空间上呈现“两核两带”的格局,即以辽中南和哈长城市群为核心,以哈大轴和东部沿边轴为发展轴带。④ 地理区位与要素禀赋、战略政策与财政扶持、行政分割与等级体制、开放带动与空间优化等诸多要素综合作用于区域经济差异时空格局的演化。 相似文献
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Spatial differences and multi-mechanism of carbon footprint based on GWR model in provincial China 总被引：9，自引：4，他引：5
Global warming has been one of the major concerns behind the world’s high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the world’s economic and social development, as well as the heated debate of the research at home and abroad in recent years. Based on the energy consumption, integrated with the “Top-Down” life cycle approach and geographically weighted regression (GWR) model, this paper analyzed the spatial differences and multi-mechanism of carbon footprint in provincial China in 2010. Firstly, this study calculated the amount of carbon footprint of each province using “Top-Down” life cycle approach and found that there were significant differences of carbon footprint and per capita carbon footprint in provincial China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scales; the provinces with higher per capita carbon footprint are mainly distributed in central cities such as Beijing, Shanghai and energy-rich regions and heavy chemical bases. Secondly, with the aid of GIS and spatial analysis model (GWR model), this paper had unfolded that the expansion of economic scale is the main driver of the rapid growth of carbon footprint. The growth of population and urbanization also acted as promoting factors for the increase of the carbon footprint. Energy structure had no considerable promoting effect for the increase of the carbon footprint. Improving energy efficiency is the most important factor to inhibit the growing carbon footprint. Thirdly, developing low-carbon economies and low-carbon industries, as well as advocating low-carbon city construction and improving carbon efficiency would be the primary approaches to inhibit the rapid growth of carbon footprint. Moderately controlling the economic scale and population size would also be required to alleviate carbon footprint. Meanwhile, environmental protection and construction of low-carbon cities would evoke extensive attention in the process of urbanization. 相似文献
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广东省区域经济差异的多尺度与多机制研究 总被引：7，自引：3，他引：4
以广东省88个县域为基本单元,基于"多尺度和多机制"框架,综合运用了总体差异指数、空间自相关、空间多水平回归等方法,分析了广东省1990~2010年区域经济差异的时空动态演变。1总体差异指数测度表明,20世纪90年代初期以来,广东省区域经济差异在地区尺度、地级尺度、县级尺度和城乡尺度均表现出不断增大的趋势,地理尺度和空间组织对区域经济差异有很大影响。2基于GIS应用,空间自相关检测发现广东省在经济发展过程中存在空间集聚"俱乐部趋同"现象,潜在地加深了区域经济差异。3空间多水平回归分析表明,全球化、简政放权、固定资产投资是促使区域经济差异加剧的主要原因,而市场化在一定程度上缓和了区域经济差异,城乡分异和地形因素也是区域经济差异的影响因素,但显著性较低。 相似文献
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