Combinatorial analysis on spatial information statistics for the karst water environment in Guiyang,China

The karst groundwater system is extremely vulnerable and easily contaminated by human activities.To understand the spatial distribution of contaminants in the groundwater of karst urban areas and contributors to the contamination,this paper employs the spatial information statistics analysis theory and method to analyze the karst groundwater environment in Guiyang City.Based on the karst ground water quality data detected in 61 detection points of the research area in the last three years,we made Kriging evaluation isoline map with some ions in the karst groundwater,such as SO4 2-,Fe 3+,Mn 2+and F -,analyzed and evaluated the spatial distribution,extension and variation of four types of ions on the basis of this isoline map.The results of the analysis show that the anomaly areas of SO4 2-,Fe 3+,Mn 2+,Fand other ions are mainly located in Baba’ao,Mawangmiao and Sanqiao in northwestern Gui- yang City as well as in its downtown area by reasons of the original non-point source pollution and the contamination caused by human activities(industrial and domestic pollution).

Application of Integration of Spatial Statistical Analysis with GIS to Regional Economic Analysis

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.

Spatial Statistical Analysis and Comprehensive Evaluation of High-Tech Industry Development

After 30 years of economic development, the high-tech industry has played an important role in China’s national economy. The development of high-level technological industry plays a leading role in guiding the transformation of China’s economy from “investment-driven” to “technology-driven”. The high-tech industry represents the future industrial development direction and plays a positive role in promoting the transformation of traditional industries. The rapid development of high-tech industry is the key to social progress. In this paper, the traditional analytical model of statistics is combined with principal component analysis and spatial analysis, and R language is used to express the analytical results intuitively on the map. Finally, a comprehensive evaluation is established.

GIS Analysis of Spatial Distribution of Crop Incidence

Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.

STATISTICAL ANALYSIS ON THE INFLUENCE OF THE LANDFALLING STRONG TROPICAL CYCLONES IN THE CATASTROPHIC MIGRATIONS OF NILAPARVATA LUGENS(STL) IN CHINA

In order to clarify the statistical pattern by which landfalling strong tropical cyclones(LSTCs)influenced the catastrophic migrations of rice brown planthopper(BPH),Nilaparvata lugens(stl)in China,the data of the LSTCs in China and the lighting catches of BPH that covered the main Chinese rice-growing regions from 1979 to 2008 were collected and analyzed in this work with the assistance of ArcGIS9.3,a software of geographic information system.The results were as follows:(1)In China,there were 220 strong tropical cyclones that passed the main rice-growing regions and 466 great events of BPH’s immigration in the 30 years from 1979 to 2008.73 of them resulted in the occurrence of BPH’s catastrphic migration(CM)events directly and 147 of them produced indirect effect on the migrations.(2)The number of the LSTCs was variable in different years during 1979 to 2008 and their influence was not the same in the BPH’s northward and southward migrations in the years.In the 30 years,the LSTCs brought more obvious influence on the migrations in 1980,1981,2005,2006 and 2007.The influence was the most obvious in2007 and all of the 7 LSTCs produced remarkable impact on the CMs of BPH’s populations.The effect of the LSTCs on the northward immigration of BPH’s populations was the most serious in 2006 and the influence on the southward immigration was the most remarkable in 2005.(3)In these years,the most of LSTCs occurred in July,August and September and great events of BPH's immigration occurred most frequently in the same months.The LSTCs played a more important role on the CM of BPH’s populations in the three months than in other months.(4)The analysis on the spatial distribution of the LSTCs and BPH’s immigration events for the different provinces showed that the BPH’s migrations in the main rice-growing regions of the Southeastern China were influenced by the LSTCs and the impact was different with the change of their spatial probability distribution during their passages.The most serious influence of the LSTCs on the BPH’s migrations occurred in Guangdong and Fujian provinces.(5)The statistical results indicated that a suitable insect source is an indispensable condition of the CMs of BPH when a LSTC influenced a rice-growing region.

Spatial autocorrelation analysis of 13 leading malignant neoplasms in Taiwan: a comparison between the 1995-1998 and 2005-2008 periods

Spatial autocorrelation methodologies, including Global Moran’s I and Local Indicators of Spatial Association statistic (LISA), were used to describe and map spatial clusters of 13 leading malignant neoplasms in Taiwan. A logistic regression fit model was also used to identify similar characteristics over time. Two time periods (1995-1998 and 2005-2008) were compared in an attempt to formulate common spatio-temporal risks. Spatial cluster patterns were identified using local spatial autocorrelation analysis. We found a significant spatio-temporal variation between the leading malignant neoplasms and well-documented spatial risk factors. For instance, in Taiwan, cancer of the oral cavity in males was found to be clustered in locations in central Taiwan, with distinct differences between the two time periods. Stomach cancer morbidity clustered in aboriginal townships, where the prevalence of Helicobacter pylori is high and even quite marked differences between the two time periods were found. A method which combines LISA statistics and logistic regression is an effective tool for the detection of space-time patterns with discontinuous data. Spatio-temporal mapping comparison helps to clarify issues such as the spatial aspects of both two time periods for leading malignant neoplasms. This helps planners to assess spatio-temporal risk factors, and to ascertain what would be the most advantageous types of health care policies for the planning and implementation of health care services. These issues can greatly affect the performance and effectiveness of health care services and also provide a clear outline for helping us to better understand the results in depth.

Investigations of Carbon Sequestration and Storage Using Advanced Geospatial Analysis

This research demonstrated quantitative methods of geospatial analysis applicable to carbon sequestration and storage in the conterminous United Sates. We identified national-scale NEP （net ecosystem production） changes for conversions to and from crop, and land in frequent conversion among forest, wetland, pasture and rangeland. The trend showed an increase in the margins of the Corn Belt states and coincided with land conversion from previous non-cropland to cropland in the United States. This research will not only improve the engineering understanding of carbon dioxide removal options involving the terrestrial biosphere, but will also inform decision-making in the carbon emission impacts. Therefore, it will provide a spatio-temporal reference for analyzing the national-level carbon exchange systems in the United States.

Space-Time Cluster Analysis of Tuberculosis Incidence in Beijing, China

Tuberculosis is one of the top killer diseases in the globe. The aim of this study was to explore the geographic distribution patterns and clustering characteristics of the disease incidence in terms of both space and time with high relative risk locations for tuberculosis incidence in Beijing area. A retrospective space-time clustering analysis was conducted at the districts level in Beijing area based on reported cases of sputum smear-positive pulmonary tuberculosis (TB) from 2005 to 2014. Global and local Moran’s I, autocorrelation analysis along with Ord (Gi*) statistics was applied to detect spatial patterns and the hotspot of TB incidence. Furthermore, the Kuldorff’s scan statistics were used to analyze space-time clusters. A total of 40,878 TB cases were reported in Beijing from 2005 to 2014. The annual average incidence rate was 22.11 per 100,000 populations (ranged from 16.55 to 25.71). The seasonal incidence occurred from March to July until late autumn. A higher relative risk area for TB incidence was mainly detected in urban and some rural districts of Beijing. The significant most likely space-time clusters and secondary clusters of TB incidence were scattered diversely in Beijing districts in each study year. The risk population was mainly scattered in urban and dense populated districts, including in few rural districts.

RANDOM SYSTEMS OF HARD PARTICLES:MODELS AND STATISTICS

This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical-statistical investigations, simulations of such structures play an important role. In these simulations various methods and models are applied, namely the RSA model, sedimentation and collective rearrangement algorithms, molecular dynamics, and Monte Carlo methods such as the Metropolis-Hastings algorithm. The statistical description of real and simulated particle systems uses ideas of the mathematical theories of random sets and point processes. This leads to characteristics such as volume fraction or porosity, covariance, contact distribution functions, specific connectivity number from the random set approach and intensity, pair correlation function and mark correlation functions from the point process approach. Some of them can be determined stereologically using planar sections, while others can only be obtained using three-dimensional data and 3D image analysis. They are valuable tools for fitting models to empirical data and, consequently, for understanding various materials, biological structures, porous media and other practically important spatial structures.

淮安市不透水面时空演变及其对生态环境影响

为了探究中小城市不透水面演变对城市生态环境质量的影响,基于2000-2020年Landsat遥感影影像,采用不透水面指数(NDISI)和遥感生态评价指数(RSEI)监测与分析淮安市不透水面对生态环境的影响.结果表明,2000-2020年淮安市不透水面面积显著增加,以蔓延式、跨越式发展模式由城市中心逐渐向周边扩张,年均增长率为8.5%,2008-2012年期间增长最快.不透水面丰度空间上由城市中心向周边逐渐递减,年均值从2000年的0.261增加至2020年的0.330.研究期生态环境质量有所改善,生态环境质量等级中较差和一般的面积减少,而良好和优等级分别增加了1677.01 km^(2)和672.1 km^(2).NDISI丰度与城市生态环境质量负相关,研究期内不透水面与生态环境质量的联系越来越密切.

空间统计法在复杂曲面几何偏差分析中的应用

通过高精度的三坐标测量机(CMM)对数控加工的复杂曲面进行检测,能得到曲面上的几何偏差分布。复杂曲面的几何偏差本质上属于空间数据,采用空间统计法进行研究分析曲面几何偏差的空间自相关性,并且采用热点分析(Getis-Ord Gi*)方法计算得到几何偏差的热点区域和冷点区域。对数控加工的复杂曲面检测获取529个点和1024个点两组几何偏差数据,结果表明两组数据反映的曲面上的几何偏差空间自相关性都为正相关;划分几何偏差热点和冷点区域的范围与测点数量有关。对数控加工的复杂曲面的几何偏差进行数据分析,将有助于对其加工质量进行分析,从而为进一步提高加工质量提供依据。

基于Voronoi图的空间点事件统计聚类方法

挖掘地理空间数据中点事件聚集模式对于揭示流行疾病、犯罪分布热点区域及城市基础设施空间分布格局等具有重要意义。针对不同形状、密度和大小的显著空间点聚集模式的识别,目前以空间扫描统计为代表的方法虽然可以对空间点聚类的显著性进行统计推断,减少虚假聚类结果,但其主要用于识别球形或椭圆形状的聚簇,对于沿着街道或河道分布的任意形状、不同密度的显著空间点聚簇识别还存在局限。因此,本研究提出一种基于Voronoi图的空间点聚集模式统计挖掘方法。首先,采用Voronoi图来度量空间点分布的聚集性,将空间点聚类问题转化为热点区域探测问题;其次,结合局部Gi*统计量探测统计上显著的空间点聚簇;最后,通过模拟数据和真实犯罪事件数据进行实验与对比分析。结果表明:本方法能够有效探测任意形状的空间点聚类,并对空间点簇的显著性进行统计判别,识别显著的空间点簇,减少随机噪声点的干扰;聚类识别结果优于现有代表性方法,如DBSCAN算法、空间扫描统计方法等。

基于时空变源分布式模型的流域洪水复盘分析方法——以海河流域北三河系“23·7”较大洪水为例

海河流域北三河系覆盖北京、天津、河北三省(直辖市),其防洪安全事关当地社会经济发展。为有效应对气候变化影响下极端暴雨频发所带来的洪水防御新挑战,提出了一种时空双维度流域性洪水复盘新思路,以“23·7”北三河系较大洪水为例,通过构建时空变源分布式水文模型结合暴雨时空统计分析对全河系洪水的发生、发展过程进行了模拟。模拟结果的确定性系数均大于0.7,洪峰相对误差均小于5%,所建模型可以较好地表征此次洪水的产流机制变化。分析发现,此次洪水过程中北运河流域产流以蓄满产流机制为主,潮白河流域产流则蓄满及混合产流两种机制均有体现,特别是靠近降雨集中区的山区平原过渡地带表现出明显的混合产流机制。建议在未来进一步完善流域防洪体系,重点提升该区域的水雨情监测能力。所提出的时空双维度下的流域性洪水复盘分析方法可为今后其他流域级洪水模拟复盘提供技术参考。

2000—2019年西北地区云水资源时空特征研究

为认识西北地区的云水资源(Cloud Water Resource,简称CWR)特征以及科学规划人工增雨开发空中水资源作业布局,利用2000—2019年中国1°×1°CWR观测诊断评估数据集,采用线性拟合和经验正交函数分解(EOF)等方法,统计分析了西北地区CWR的分布及演变气候特征。结果表明:(1)从全区整体看,CWR的相关物理量(状态量、平流量、总量和降水效率)主要表现为夏季最高,春、秋季次之,冬季最低的季节变化特征。其中,春季CWR总量约为1736亿t(折合柱水量约为51.2 mm),仅次于夏季;春季水凝物降水效率为48.7%,相较于秋季,春季的CWR开发潜力更大。(2)从区域内1°×1°网格的计算结果得到空间分布,受地势与环流的影响,近20年CWR年总量及水汽年总量、水凝物年总量的多年平均空间分布呈“两高一低”的特征,高值位于西风急流区与季风影响边缘区,低值区主要位于高原气候区。(3)近20年,西北地区格点的CWR年总量平均以23.6 mm/a速率增加,其中春季的增加趋势最显著,增速为8.5 mm/a。季节分布上,CWR夏季最多,春、秋季次之,冬季最少;水凝物降水效率夏季高,秋、春季较低,冬季最低。(4)CWR年总量的EOF分解第一模态(EOF1)贡献率为78.2%,分布特征为区域东部较高,在2008年出现年际转折,开始转变为CWR东部多、西部少的分布格局。(5)在西北地区典型区域中,天山区域年平均及格点平均后的CWR年总量以及水凝物降水效率均高于祁连山区,年际变化上祁连山区的CWR在增多,天山区的在减少。

华北典型区域地下水重金属来源解析及健康风险识别

科学评估地下水重金属健康风险并识别主要风险因子,对保障地下饮用水安全和开展地下水风险管控具有重要意义。选取华北典型区域地下水作为研究对象,根据地势和地下水流向选定了14个采样点,于2017—2019年采集了122个地下水样品,并对样品中的Cr6+、Cd、As、Mn、Fe、Cu、Hg、Pb、Se和Zn进行了检测,以多元统计分析和健康风险评价模型相结合的方式,明晰了地下水重金属的来源和主要风险因子。结果表明:①研究区域地下水中重金属的浓度均值排序为ρ(Fe)>ρ(Zn)>ρ(Mn)>ρ(As)>ρ(Se)>ρ(Cu),其余元素未检出。根据综合污染评价结果,研究区地下水水质整体较好。②就空间分布而言,S12采样点处的As(5.04μg/L)、Mn(4.36μg/L)、Fe(18.52μg/L)和Cu(0.38μg/L)浓度最高,Se在S5采样点(0.52μg/L)处浓度最高,Zn在S4采样点(12.88μg/L)处浓度最高。③多元统计分析结果显示,As、Cu、Fe和Mn可能来源于工业活动,Se可能来源于地质环境。④健康风险评价结果显示,儿童面临的风险高于成人,饮水是主要的重金属暴露途径,潜在风险主要来源于As。为保障居民地下饮用水安全,应当将As作为今后加强地下水保护的优先控制指标。

山区地形起伏度与村落空废关系分析——以理县为例

山区村落空废现象受到地形起伏度的显著影响,分析二者的关系对山区村落的保护及发展具有重要意义。本文以四川省阿坝藏族羌族自治州理县为例,通过田野调查采集219个村民小组的空废数据,基于ASTER GDEM V2数字高程数据,采用窗口分析法和均值变点法确定最佳统计单元,以提取地形起伏度,并进行地貌类型分类,利用回归分析及空间自相关分析方法解析地形起伏度对村落空废的影响。结果表明:理县的平均村落空废率为41.25%,空废率高值区以甘堡乡为核心、呈一主多次的空间结构;理县地形起伏度的最佳统计单元是0.66 km2,地形起伏度介于101~1208 m,呈“东南高、西北低”的空间格局,以占比超四成的中起伏高中山地貌类型为主;地形起伏度在数量上与村落空废率呈显著正相关,对空废率的影响较海拔高度更大,地形起伏度在空间上与村落空废率呈弱空间正相关,在薛城镇呈高高聚集,在朴头镇、古尔沟镇呈高低聚集。

物资集中招标采购成本控制方法研究

集中招标采购提高了大型企业集团的议价能力,有助于降低企业采购成本。文章基于多价值链视角挖掘采购成本的关键性影响因素,以某大型企业集团钢铁类物资集中招标采购为例,通过空间统计分析和构建空间面板模型,分析关键性影响因素对企业集团下属各项目单位采购成本的差异性,并提出该采购模式下的成本控制策略,有助于其他企业集团结合下属各项目单位的区域特性统筹资源调度,进行成本管控。

基于多尺度的吉林省城市国土空间监测数据统计分析方法研究

本研究主要将吉林省作为研究区域,从选取空间尺度、设计指标体系、探究统计方法3个方面,综合分析多尺度下的城市国土空间监测数据统计分析最适方法,深入反映城市国土空间格局优化发展关注的要素情况。结合城市区域间的多尺度统计单元,进行横向比较分析,不仅可以使国土空间资源布局可视化,而且能为城市国土空间多层级结构优化提供指导。

基于GIS的晋城市农村饮用水水质分布规律及成因研究

在晋城地区选取462个农村饮用水水样进行了水质检测,并基于GIS技术对检测数据进行了统计分析,结果显示:饮用水中硫酸盐、氯化物、硝酸盐(N)、镉、氨(N)、锌的空间分布存在显著差异;饮用水中pH值、氟化物、总硬度、溶解性总固体、硫酸盐、硝酸盐N、氯化物、浑浊度、高锰酸盐指数、氨(N)、镉、铬(六价)和锌的分布均具有特定的空间规律。结合该地区的地质构造、岩层土壤组成、气象、水文以及社会条件等因素,分析了农村饮用水呈现这一分布规律的原因。

宁波市休闲渔业空间分布及影响因素分析

休闲渔业经营单位要实现效益最大化,需减少资源调配成本,发挥区位优势,同时要有科学合理的企业空间布局。该研究以宁波市284个休闲渔业经营单位为研究对象,综合运用最近邻指数、变异系数、核密度分析法、聚类和异常值分析法,借助Arcgis空间分析工具,从分布形态、分布均衡程度、分布密度等3个维度对宁波市休闲渔业经营单位的空间分布特征进行分析,并对其空间分布特征的影响因素进行探讨。结果表明,宁波市休闲渔业经营单位整体上呈现集聚型的分布形态,集聚程度由高到低排序依次是鄞州区、海曙区、象山县。宁波市休闲渔业经营单位的空间分布密度具有显著差异性,具有明显的“双中心、大集聚、区域分化明显”的密集性,并以双中心为核心,向周边辐射。宁波市休闲渔业经营单位的空间分布受交通、市场、景区区位因素的影响显著。研究结果可为优化宁波市休闲渔业企业选址,提高企业经营效率提供科学依据。