烟台市新增亿元GDP用地量的分析探讨          下载免费PDF全文

孙红岩  石晓 《山东国土资源》2012,28(2):60-62

新增亿元GDP用地量是衡量土地节约集约利用的重要指标,在分析烟台市新增亿元GDP用地量现状的基础上,确定烟台市新增亿元GDP用地量,并以此为基础对烟台市未来5年合理新增用地量进行预测,为促进土地节约集约利用提供参考。  相似文献   

城市扩张进程中水环境污染成本响应模拟   总被引：4，自引：0，他引：4  

吴永娇  马海州  董锁成 《地理研究》2009,28(2):311-320

本文旨在建立地表水环境污染对城市扩张的响应模型,以模拟预测城市扩张进程中的社会经济发展、土地效益和生态环境成本的动态变化过程。首先,应用遥感影像解译技术,对城市扩张引起的土地利用变化进行定量分析;其次,基于社会福利最大化和绿色GDP(GGDP)等理论,模拟城市地表水环境污染成本在不同社会经济情景下对城市扩张的响应。以西安为典型研究区域,分析了该区在1996~2006年间城市扩张行为及其对地表水环境污染的影响,结果表明:在不同的社会经济发展条件下,有着不同的城市扩张最优点(均衡点);城市扩张引起的边际生态环境成本小于平均土地效益时,城市扩张会使社会福利变好,城市扩张应继续;技术进步可优化地表水环境污染成本和提高土地利用效率,优化城市扩张均衡点;在现有的经济技术水平发展条件下,理论上西安城市扩张最优点在2024年达到。  相似文献   

基于夜间灯光数据的珠三角地区镇级GDP估算     

柴子为  王帅磊  乔纪纲 《热带地理》2015,35(3):379-385

高精度地表GDP分布数据是开展小尺度区域发展相关研究的关键数据,但通常难以获得完整数据序列。文章比较了DMSP-OLS和NPP-VIRS两种夜间灯光数据在小尺度单元GDP估算工作上的适应性,证实NPP-VIIRS数据在镇级GDP估算中有更好的性能。利用修正后的NPP-VIIRS夜间灯光数据建立珠三角地区镇级GDP估算模型,并通过地区差异系数对估计结果进行校正。对2013年镇级GDP估算的实验结果总体精度达到85%。估算结果能够用于填补珠三角地区部分镇级GDP统计数据缺失,为相关研究获取、对比GDP数据提供技术手段。  相似文献   

基于能值分析的福建省绿色GDP核算   总被引：6，自引：0，他引：6  

张虹  黄民生  胡晓辉 《地理学报》2010,65(11):1421-1428

运用能值分析方法,通过能值转换率,将福建自然、社会经济系统储存和流动的不同种类的能量转化为统一标准--能值,得到能值消耗总量与GDP的比值即能值/货币比率。再将资源耗减与环境损失部分通过能值/货币比率转换为货币价值,并在传统GDP中扣除,即得到绿色GDP。最后运用部分能值评价指标对福建可持续发展状况进行分析。结果表明：2001 年到2006年福建省GDP增长迅速,但绿色GDP增长相对缓慢。福建居民生活水平较高,经济发达,对外贸易中以输出能值为主。但是环境压力大,可持续发展能力下降。内部资源开发不足,需要依赖外部环境,经济风险日渐增大,经济活动的竞争力趋于减弱。福建省经济增长中仍有一部分是不可持续增长,这与福建省的工业化程度有关。  相似文献   

Trend analysis using nonhomogeneous stochastic diffusion processes. Emission of CO<Subscript>2</Subscript>; Kyoto protocol in Spain     

R. Gutiérrez  R. Gutiérrez-Sánchez  A. Nafidi 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(1):57-66

In this study, we propose a methodology to analyse the gradual secular trends present in the time evolution of certain endogenous variables, which are of particular interest in environmental research. This methodology is based on modelling such variables by nonhomogeneous stochastic diffusion processes, the trend functions of which may be made to depend on other, exogenous, variables, which are controllable and which affect and model, in turn, the possible irregularities of such trends. The methodology is applied to analyse the evolution of the emission of CO₂ in Spain, and it is shown that the evolution of the Spanish GDP affects the trend component. These circumstances are considered in the context of Spain’s non-compliance with the Kyoto protocol on controlling the emission of greenhouse gases.  相似文献   

基于Geoda 095i区域经济增长率的空间统计分析研究   总被引：5，自引：0，他引：5  

胡青峰  张子平  何荣  牛遂旺 《测绘与空间地理信息》2007,30(2):53-55

空间统计分析的核心是认识与地理位置相关的数据间的空间依赖、空间关联或空间自相关,通过空间位置建立数据间的统计关系。本文利用空间分析的相关知识,通过对河南省各辖市2006年第一季度GDP增长速度及其相关因素的分析,发现该时期内河南省各辖市GDP增长率水平的空间分布并非表现出完全随机性,而是表现出空间相似值之间的空间聚集。基于对Moran散点图的分析和空间滞后回归模型的回归分析,得出空间统计分析对于分析区域经济发展的空间结构形态以及政策制定具有参考价值。  相似文献   

基于不同尺度的中国运动健身场所空间差异及影响因素研究          下载免费PDF全文

赵海莉  李家亮  李开丽  杜雨涵  王家明 《干旱区地理》2022,45(6):1938-1948

运动健身场所是开展全民健身运动的重要推手,探明运动健身场所的区域差异及影响因素对推动运动健身场所的建设、推进“健康中国”战略有重要作用。从省级、城市群以及地级市3个尺度出发,运用总体分异测度指数(Global differentiation index,GDI)、Moran’s I指数、热点分析探讨运动健身场所的空间差异,采用Pearson相关系数、灰色关联度以及地理探测器等方法分析运动健身场所分布的影响因素。结果表明:(1)运动健身场所数量与每万人拥有运动健身场所数量主要集中分布于东部地区,而西部地区除成都、重庆外,其余省区均分布较少。(2)运动健身场所数量与每万人拥有运动健身场所数量的GDI随着尺度的缩小而扩大,城市群尺度中,优化提升类差异最大,而发展壮大类差异最小。(3)经济总量和人口数量是运动健身场所集中的重要驱动因素,人口数量与城镇人口占比的交互作用最强。在城市群尺度上,受教育程度和城市规模大小是运动场所的重要影响因素。而在地级市尺度上,建成区面积占辖区面积比重对运动健身场所的影响更为显著。  相似文献   

GIS技术在区域经济分析中的应用   总被引：6，自引：0，他引：6  

肖根如  帅菲 《地理空间信息》2007,5(1):75-77

讨论了GIS技术在区域经济分析中的应用,提出了一个基于GIS技术的区域经济分析系统。随后给出了实例分析——应用全国空间数据和统计数据(如GDP等)在ArcView GIS的系统环境下开发了一个区域经济差异特征分析模块,得出了全国各区域的差异情况,并对整个区域进行了经济分区,为区域经济规划的制定与决策提供了一种科学的依据。  相似文献   

Assessment of Global Seismic Loss Based on Macroeconomic Indicators   总被引：5，自引：0，他引：5  

Cha  L. S. 《Natural Hazards》1998,17(3):269-283

Most earthquake loss studies use a probabilistic approach in which predicted damages in various categories of structure and facilities in the region in concern are estimated and added together to obtain a total loss for particular intensity ranges. Such an approach requires a detailed inventory database of the structures and facilities in the region, which is not always readily available in many regions of the world. We have used an alternative means of estimating earthquake losses based on several macroeconomic indices such as the gross domestic product and population. Using published earthquake loss data for 1980–1995, the relations between GDP and earthquake loss have been formulated empirically for several intensity ranges. The world's land surface was divided into unit cells 0.5° lat. × 0.5° long. in size. The GDP of each cell was apportioned based on its population and GDP, and the population of the region to which it belongs. The predicted seismic loss of the cell was then estimated from the seismic hazard probability function, its GDP, and the empirical relation between GDP and seismic loss. A global seismic loss map is then compiled both for the intensity at 10% probability of exceedance and the probable maximum intensity. Employing readily available socioeconomic data as the basis for the vulnerability analysis, the method enables us to obtain seismic loss estimates for regions without the need for a detailed inventory of exposed structures or collateral geological information. Since such statistics are frequently compiled by the world's leading political and financial institutions, the seismic loss estimates can also be upgraded easily for the fast developing areas of the world.  相似文献   

Forecasting China’s GDP at the pixel level using nighttime lights time series and population images   总被引：1，自引：0，他引：1  

Naizhuo Zhao  Ying Liu  Guofeng Cao  Eric L. Samson  Jingqi Zhang 《地理信息系统科学与遥感》2017,54(3):407-425

China’s rapid economic development greatly affected not only the global economy but also the entire environment of the Earth. Forecasting China’s economic growth has become a popular and essential issue but at present, such forecasts are nearly all conducted at the national scale. In this study, we use nighttime light images and the gridded Landscan population dataset to disaggregate gross domestic product (GDP) reported at the province scale on a per pixel level for 2000–2013. Using the disaggregated GDP time series data and the statistical tool of Holt–Winters smoothing, we predict changes of GDP at each 1 km × 1 km grid area from 2014 to 2020 and then aggregate the pixel-level GDP to forecast economic growth in 23 major urban agglomerations of China. We elaborate and demonstrate that lit population (brightness of nighttime lights × population) is a better indicator than brightness of nighttime lights to estimate and disaggregate GDP. We also show that our forecast GDP has high agreement with the National Bureau of Statistics of China’s demographic data and the International Monetary Fund’s predictions. Finally, we display uncertainties and analyze potential errors of this disaggregation and forecast method.  相似文献