共查询到20条相似文献,搜索用时 15 毫秒
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国内外GIS软件的空间分析功能比较 总被引:1,自引:0,他引:1
通过分析空间分析与空间数据的关系,详细比较了国内外GIS软件的空间分析功能,介绍了国内外成熟的GIS软件在空间分析功能上的优势,对空间分析的发展进行了展望. 相似文献
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基于GIS的烟威地区旅游资源空间分析 总被引:2,自引:0,他引:2
本文应用GIS技术,对烟威地区旅游资源的结构和空间分布进行分析。以烟台、威海、蓬莱三个主要旅游城市为中心,以30km为最大缓冲半径,以5km为间隔距离做缓冲分析,揭示以三市为驻足地进行旅游的旅游景点空间分布信息及距可达景点的空间距离。基于区域内三条主要交通线路,以8km为最大缓冲半径,以2km为间隔距离做缓冲分析,为自驾车旅游者提供可达景点的空间信息。最后总结了该地区旅游资源空间分布的特征,提出了该地区旅游资源的开发理念及旅游发展的整体思路和方向。 相似文献
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基于GIS空间数据库,对山东省108个城镇的综合发展水平进行了空间统计分析。首先选用了反映城市综合发展水平的14项指标,并进行了主成分分析,得出反映城镇综合发展水平的综合指标,并分析了山东省各城镇的综合发展水平与分布状况。然后利用该综合指标,对各个城镇进行了空间统计分析,通过计算全局空间自相关指标,分析认为山东省各城镇综合发展水平总体上未呈现空间相关关系;通过计算局部空间自相关指标,分析认为山东省68.5%的城镇分布存在非相似空间集聚特征。 相似文献
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GIS空间数据的分析与制图一体化策略 总被引:3,自引:0,他引:3
地理信息系统(GIS)是地理学、地图学等在信息化时代发展的新的理论技术体系,其软件系统需要同时具有地理空间分析与地图表达两方面的功能.但是分析与制图对地理空间数据的要求存在一定程度的差异,导致两者间数据无法充分共享.在分析地理空间数据冲突的基础上,初步探讨了在GIS中实现分析与制图功能一体化的数据采集与应用方案,有助于避免数据的重复建设,提高地理空间数据的利用效率. 相似文献
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ABSTRACTThis article attempts to detail time series characteristics of PM2.5 concentration in Guangzhou (China) from 1 June 2012 to 31 May 2013 based on wavelet analysis tools, and discuss its spatial distribution using geographic information system software and a modified land use regression model. In this modified model, an important variable (land use data) is substituted for impervious surface area, which can be obtained conveniently from remote sensing imagery through the linear spectral mixture analysis method. Impervious surface has higher precision than land use data because of its sub-pixel level. Seasonal concentration pattern and day-by-day change feature of PM2.5 in Guangzhou with a micro-perspective are discussed and understood. Results include: (1) the highest concentration of PM2.5 occurs in October and the lowest in July, respectively; (2) average concentration of PM2.5 in winter is higher than in other seasons; and (3) there are two high concentration zones in winter and one zone in spring. 相似文献
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Some thoughts on the integration of spatial analysis and Geographic Information Systems 总被引:5,自引:0,他引:5
Duane F. Marble 《Journal of Geographical Systems》2000,2(1):31-35
It is past time for us to examine the relationship that exists between what we commonly call spatial analysis on the one
hand, and geographic information systems or GIS on the other. GIS technology is widely used but seems to incorporate only
a portion of the tools found in spatial analysis. Spatial analysis can be accused of overly simplistic approaches that severely
limit its practical utility. This paper suggests that discarding myopic views and meeting upon a common ground of increased
knowledge of modern computing concepts and techniques, including object-orientation, can prove extremely fruitful to both
sides. 相似文献
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ABSTRACT Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discretization and spatial scale effects are fundamental issues, but they are generally determined by experience and lack accurate quantitative assessment in previous studies. To address this issue, an optimal parameters-based geographical detector (OPGD) model is developed for more accurate spatial analysis. The optimal parameters are explored as the best combination of spatial data discretization method, break number of spatial strata, and spatial scale parameter. In the study, the OPGD model is applied in three example cases with different types of spatial data, including spatial raster data, spatial point or areal statistical data, and spatial line segment data, and an R “GD” package is developed for computation. Results show that the parameter optimization process can further extract geographical characteristics and information contained in spatial explanatory variables in the geographical detector model. The improved model can be flexibly applied in both global and regional spatial analysis for various types of spatial data. Thus, the OPGD model can improve the overall capacity of spatial stratified heterogeneity analysis. The OPGD model and its diverse solutions can contribute to more accurate, flexible, and efficient spatial heterogeneity analysis, such as spatial patterns investigation and spatial factor explorations. 相似文献
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以滇东南岩溶区独特的地理环境作为研究对象,根据《生态功能区划暂行规定》和国内外已有的土壤侵蚀敏感性的研究成果,选择地形起伏度(LS)、植被覆盖度(C)、土壤质地(K)3个自然因子作为滇东南岩溶区土壤侵蚀敏感性评价的指标,在GIS时空分析功能支持下,以《生态功能区划暂行规定》的敏感性等级标准为依据,分析各个因子对土壤侵蚀敏感性的影响,并结合研究区域实地情况对各个因子分别进行土壤侵蚀敏感性的评价。在各因子单独分析的基础上运用GIS的空间分析功能,根据这些敏感因子对侵蚀敏感性影响程度的不同分配、不同权重,进行综合分析评价,得到不同敏感程度区域的面积和空间分异特征。 相似文献
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Analysis of human spatial behavior in a GIS environment: Recent developments and future prospects 总被引:1,自引:0,他引:1
Mei-Po Kwan 《Journal of Geographical Systems》2000,2(1):85-90
In recent years, comprehensive geographic data sets of metropolitan areas and individual-level, georeferenced data are becoming
more available to social scientists. At the same time, tools for performing spatial analysis in a GIS environment have also
become more available. These developments provide many new opportunities for the analysis and theoretical understanding of
disaggregate human spatial behavior. This paper examines how these developments may enable the researcher to represent complex
urban and cognitive environments more realistically, and to overcome the limitations of aggregate spatial data framework.
It explores their implications for the theoretical and methodological development in geography and other social science disciplines. 相似文献
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Application of integration of spatial statistical analysis with GIS to regional economic analysis 总被引:2,自引:0,他引:2
CHENFei DUDaosheng 《地球空间信息科学学报》2004,7(4):262-267
This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units. 相似文献