中国国家自然地图集Internet版的设计和研制

本文系统阐述了国家自然地图集Ｉｎｔｅｒｎｅｔ版的设计和研制过程中的若干问题,包括系统的概念设计、系统开发中的ＷｅｂＧＩＳ技术和策略,系统的主要功能和特色,以及系统维护和更新方案等。本系统从概念设计来看分为服务器端软件模块、浏览器端软件模块、国家自然地图集数据库支持等几个部分。系统开发中采取的ＷｅｂＧＩＳ技术和策略有:兼顾服务器端和客户端的综合型ＷｅｂＧＩＳ策略,基于Ｊａｖａ Ａｐｐｌｅｔ的 ＷｅｂＧＩＳ浏览器开发技术,基于Ｍａｐ Ｏｂｊｅｃｔ(ＭＯ)的ＷｅｂＧＩＳ服务器开发技术等３个方面。在系统的主要功能特色方面,本文从以下５个方面进行了论述:科学有序的内容结构、清晰精练并带导航的界面、富有特色的信息查询功能、多重表达的地图可视化效果、一定的空间信息分析和制图功能。在系统维护和更新方案上,本文从网络技术、数据更新、功能开发３个方面介绍了计划,并对今后的发展趋势进行了展望。     

An exploratory spatial data analysis of low birth weight prevalence in Georgia

Low birth weight (LBW), defined as a live birth weighing less than 2500 g, is a significant public health problem in the United States, but the complex nature of the etiology of this problem is not fully understood. Moreover, significant disparities in LBW prevalence are well documented among certain populations, particularly in minority and underserved communities. The identification of spatial patterns of LBW prevalence is a critical first step in a more complete understanding of the epidemiology of this public health challenge and these techniques are instrumental in designing valid observational and analytical studies to more fully study the problem. This paper examines the spatial patterns of LBW prevalence, as well as the presence of spatial clusters in the State of Georgia at both the county and census tract levels. Unadjusted and empirical Bayes smoothed LBW rates were mapped to visualize the spatial variation of LBW rates, and the Moran’s I statistic and the Local Indicator of Spatial Association (LISA) statistic were computed to assess the degree of spatial dependence in the LBW rates. Results revealed marked geographical variation in LBW prevalence in Georgia in 2000. In addition, these data validate the significant disparity (two-fold difference) between white and black racial subgroups as documented in the literature. Trends associated with positive and negative spatial autocorrelations illustrated variation with respect to race. Limitations of data and methods, as well as plans for utility of the results of this study for further investigation were discussed.     

Sensitivity of disease cluster detection to spatial scales: an analysis with the spatial scan statistic method

ABSTRACT

The spatial scan statistic method has been widely used for detecting disease clusters. Its results may be affected by scales, including the aggregation level of the input data and the population threshold used in the detection. Previous studies offered inconsistent findings, and few had considered both types of scales at the same time. Using 24 simulated datasets and two real disease datasets, we investigated the method’s sensitivity to the two types of scales. We aggregated the individual-level data into areal units of three levels, including county, town, and a 900 m grid. We detected clusters with three population thresholds, including 10%, 25%, and 50%. We used two measurements, distance between cluster centres and the Jaccard index, to quantify the consistency of clusters detected with different scale settings. We find: (1) the method is not greatly sensitive to the data aggregation level when the cluster is strong and in a place with high population density; (2) the method’s sensitivity to the population threshold is determined by the actual size of the true cluster; and (3) a regular grid with fine resolution is advantageous over the subjectively defined areal units. The process and findings may have broader meanings to similar spatial analyses.     

Using spatial analysis and Bayesian network to model the vulnerability and make insurance pricing of catastrophic risk

Vulnerability refers to the degree of an individual subject to the damage arising from a catastrophic disaster. It is affected by multiple indicators that include hazard intensity, environment, and individual characteristics. The traditional area aggregate approach does not differentiate the individuals exposed to the disaster. In this article, we propose a new solution of modeling vulnerability. Our strategy is to use spatial analysis and Bayesian network (BN) to model vulnerability and make insurance pricing in a spatially explicit manner. Spatial analysis is employed to preprocess the data, for example kernel density analysis (KDA) is employed to quantify the influence of geo-features on catastrophic risk and relate such influence to spatial distance. BN provides a consistent platform to integrate a variety of indicators including those extracted by spatial analysis techniques to model uncertainty of vulnerability. Our approach can differentiate attributes of different individuals at a finer scale, integrate quantitative indicators from multiple-sources, and evaluate the vulnerability even with missing data. In the pilot study case of seismic risk, our approach obtains a spatially located result of vulnerability and makes an insurance price at a finer scale for the insured buildings. The result obtained with our method is informative for decision-makers to make a spatially located planning of buildings and allocation of resources before, during, and after the disasters.     

基于ESDA的西北地区公路网分布空间差异分析

利用探索式空间数据分析（ESDA）方法分析了2004-2010年西北地区市域尺度的公路网空间分布差异及其变化特征,并结合定性分析和空间计量模型探讨了公路分布差异的驱动机制。结果表明:（1）西北地区公路网空间分布具有显著的全局正相关关系,存在明显的集聚特征,公路网空间差异趋势愈加明显,公路网集聚模式发生明显变化的区域集中在陕甘宁交界地带,“陕南-关中-陇东-青东”地区形成公路网“高-高”集聚类型分布的连绵区域,“低-低”集聚类型区域分布在河西走廊、新疆、青海地区;（2）公路网密度水平高于全国平均水平的区域规模数量呈增长态势,其中“西安-兰州-西宁”地区的公路网密度水平高于全国平均水平,该地区已形成具备向外扩张能力的交通带;（3）自然环境状况是约束公路交通基础设施建设运营的基本条件,而区域经济的非均衡发展格局及其空间溢出效应是形成公路网分布差异的重要驱动力。     

中国国内旅游流空间场效应分析

从空间场效应的角度采用因子分析法,利用1999-2003年中国国内旅游抽样调查资料,分析国内旅游流的产生、分配、集聚、扩散的基本特征以及旅游流空间网络的相关性。结果表明:(1)经济是旅游流产生的主要驱动力,旅游资源是旅游流空间分配的主要驱动力; 目前国内已形成4大旅游流产生地和5大旅游流集聚地;(2)旅游集聚场与扩散场的等级结构受市场原则作用,表现为K=3序列的空间模式;(3)旅游集聚场地域结构呈"U"型特征,而旅游扩散场呈"三级阶梯"状格局;(4)β、γ指数揭示旅游流空间网络相关性较差。今后加快长江、黄河流域旅游带以及南部沿海、北部沿海和东北旅游区等"二带三区"的旅游网络化建设,是我国推进区域旅游合作的主要方向和重点区域,是实现旅游流空间流向合理调整与流量结构优化的关键。     

基于粗糙集理论的地学空间关系规则分析及其应用——以珠江三角洲为例

Spatial relations,reflecting the complex association between geographical phenomena and environments,are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization,an important geographical issue,is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter,the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong,located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan,Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan,Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.     

Application of rough set-based analysis to extract spatial relationship indicator rules: An example of land use in Pearl River Delta

Spatial relations, reflecting the complex association between geographical phenomena and environments, are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization, an important geographical issue, is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter, the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong, located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan, Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan, Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.     

长江中上游降水空间分析的SIA方法

1 IntroductionW ith the developm ent of geoscience and interdisciplinary sciences, the precipitation data ofhigher resolution are dem anded by m any studies, especially by the study on the interactionbetw een terrestrial biosphere and atm osphere,and hydr…     

The SIA method for spatial analysis of precipitation in the upper-middle reaches of the Yangtze River

Using geographic information system (GIS) techniques and the newest seasonal and annual average precipitation data of 679 meteorological stations from 1971 to 2000, the multiple regressions equations of the precipitation and topographical variables are established to extract the effect of topography on the annual and seasonal precipitation in the upper-middle reaches of the Yangtze River. Then, this paper uses a successive interpolation approach (SIA), which combines GIS techniques with the multiple regressions, to improve the accuracy of the spatial interpolation of annual and seasonal rainfall. The results are very satisfactory in the case of seasonal rainfall, with the relative error of 6.86%, the absolute error of 13.07 mm, the average coefficient of variation of 0.070, and the correlation coefficient of 0.9675; in the case of annual precipitation, with the relative error of 7.34%, the absolute error of 72.1 mm, the average coefficient of variation of 0.092, and the correlation coefficient of 0.9605. The analyses of annual mean precipitation show that the SIA calculation of 3-5 steps considerably improves the interpolation accuracy, decreasing the absolute error from 211.0 mm to 62.4 mm, the relative error from 20.74% to 5.97%, the coefficient of variation from 0.2312 to 0.0761, and increasing the correlation coefficient from 0.5467 to 0.9619. The SIA iterative results after 50 steps identically converge to the observed precipitation.     

干旱半干旱区城市生态效率时空演变及区域差异分析

研究西北干旱半干旱区城市生态效率,对其经济、资源、环境的协调统一以及生态文明建设的推进具有重要的现实意义。以西北干旱半干旱区38个城市为研究对象,运用三阶段DEA方法客观地测度了各城市2005—2016年生态效率,同时运用ESDA方法全面分析了生态效率的区域差异。结果显示:干旱半干旱区城市生态效率普遍较低,并呈现正向全局空间自相关关系;热点区域主要以乌鲁木齐、克拉玛依等为中心,冷点区域主要以平凉、固原等为中心,热点区域数量呈现先增后减再增的N形变动趋势,冷点区域数量则呈现先减后增再减的倒N形变动趋势。     

城市网络联系对城市群空间体系集聚水平的影响——基于2003—2018年中国12个城市群面板数据的实证

本文分析了2003—2018年中国12个规模较大的城市群的空间体系特征及其变动趋势,并借助城际投资联系数据,分析了各城市群城市网络特征,实证检验了城市网络联系度对城市群空间体系集聚水平的影响。研究发现,2003—2018年城市群空间体系总体呈均衡化发展趋势,且不同城市群城市网络特征差异明显,按发育程度可以分为四种类型：联系紧密-结构均衡-强中心带动型城市网络,联系紧密-弱中心带动-相对开放型城市网络,结构均衡但联系相对较弱型城市网络,以及联系相对较弱且结构极化型城市网络。实证结果证实了城市网络联系的紧密程度和连通度的提高有利于降低城市群空间体系的极化水平,城市网络联系带来的外部性有助于避免城市群空间体系的过度极化及由此带来的集聚负外部性,实现更加均衡的城市群空间结构。但城市网络联系对城市群空间体系均衡化发展的作用依赖于城市网络的结构特征,城市网络结构的极化对城市群空间体系均衡化发展存在抑制作用。