HQ-Tree： A Distributed Spatial Index Based on Hadoop

In this paper,we propose a novel spatial data index based on Hadoop:HQ-Tree.In HQ-Tree,we use PR QuadTrec to solve the problem of poor efficiency in parallel processing,which is caused by data insertion order and space overlapping.For the problem that HDFS cannot support random write,we propose an updating mechanism,called "Copy Write",to support the index update.Additionally,HQ-Tree employs a two-level index caching mechanism to reduce the cost of network transferring and I/O operations.Finally,we develop MapReduce-based algorithms,which are able to significantly enhance the efficiency of index creation and query.Experimental results demonstrate the effectiveness of our methods.

2-Level R-tree Index Based on Spatial Grids and Hilbert R-tree

Multi-level spatial index techniques are always used in large spatial databases. After a general survey of R-tree relevant techniques, this paper presents a novel 2-level index structure, which is based on the schemas of spatial grids, Hilbert R-tree and common R-tree. This structure is named H2R-tree, and it is specifically suitable for the indexing highly skewed, distributed, and large spatial database. Algorithms and a sample are given subsequently.

HPSIN: a new hybrid P2P spatial indexing network

Geographic information system （GIS） is increasingly managing very large sets of data, hence a centralized data index may not always provide the most scalable solution. Recently, the peer to peer （P2P） networks have become very popular for sharing information in a totally decentralized manner. In this paper, a new hybrid P2P spatial indexing network （HPSIN） is proposed, which combines distributed quad-tree with distributed Hash table （DHT） based Chord network to maintain both query efficiency and system load balance. In addition, a simple theoretical model based on opened queueing network for HPSIN is established. Assuming each peer as M/M/1 queueing processor in the model, fundamental characteristics of the system is captured, and expression of average query delay is obtained in close form. The theoretical analysis and numerical computing results show that there exists an optimum point of tradeoff between efficiency and load balance. By setting a proper value of start index level ls for different network scale and query rate, HPSIN will achieve the minimum overall query delay, therefore, can adapt to different P2P application environments.

ANALYSIS OF HABITAT PATTERN CHANGE OF RED-CROWNED CRANES IN THE LIAO HE DELTA USING SPATIAL DIVERSITY INDEX

Habitat pattern change of red-crowned cranes (Grus japonensis) in t he Liaohe Delta between 1988 and 1998 was analyzed with the help of Spatial Dive rsity Index based on remote sensing data and field investigation. The result sho wed that the influence from human activities on the wetland habitat of red-crow ned cranes was prominent with the development of oil and agricultural exploitati on, and the habitat pattern of red-crowned cranes had been obviously changed by the human disturbance during the ten years. The areas with high Spatial Diversi ty values (SD≥0.65) and that with mid-high values (0.5≤SD< 0.65), which const ituted the main part of suitable habitat of red-crowned cranes,had reduced to 9142ha and 5576ha respectively, with the shrinking of natural land cover, such a s reed and Suaeda community. The habitat pattern became more fragmented, which w as caused by roads and wells during oil exploration. It was indicated that the s uitability and quality of habitat for red-crowned cranes in the Liaohe Delta we re degraded in the last decade. The results also showed that diversity index cou ld reflect the habitat suitability of red-crowned cranes quantitatively and des cribe the spatial pattern of the habitat explicitly. This study will provide a s cientific basis for habitat protection of red-crowned cranes and other rare spe cies in wetlands.

Spatial-temporal Analysis of Daily Air Quality Index in the Yangtze River Delta Region of China During 2014 and 2016

Urban air pollution is a prominent problem related to the urban development in China, especially in the densely populated urban agglomerations. Therefore, scientific examination of regional variation of air quality and its dominant factors is of great importance to regional environmental management. In contrast to traditional air pollution researches which only concentrate on a single year or a single pollutant, this paper analyses spatiotemporal patterns and determinants of air quality in disparate regions based on the air quality index(AQI) of the Yangtze River Delta region(YRD) of China from 2014 to 2016. Results show that the annual average value of the AQI in the YRD region decreases from 2014 to 2016 and exhibit a basic characteristic of ‘higher in winter, lower in summer and slightly high in spring and autumn'. The attainment rate of the AQI shows an apparently spatial stratified heterogeneity, Hefei metropolitan area and Nanjing metropolitan area keeping the worst air quality. The frequency of air pollution occurring in large regions was gradually decreasing during the study period. Drawing from entropy method analysis, industrialization and urbanization represented by per capita GDP and total energy consumption were the most important factors. Furthermore, population agglomeration is a factor that cannot be ignored especially in some mega-cities. Limited to data collection, more research is needed to gain insight into the spatiotemporal pattern and influence mechanism in the future.

A Novel Hybrid Method for Measuring the Spatial Autocorrelation of Vehicular Crashes: Combining Moran’s Index and Getis-Ord G_i<sup style='margin-left:-7px;'>*</sup>Statistic

Spatial autocorrelation is a measure of the correlation of an observation with other observations through space. Most statistical analyses are based on the assumption that the values of observations are independent of one another. Spatial autocorrelation violates this assumption, because observations at near-by locations are related to each other, and hence, the consideration of spatial autocorrelations has been gaining attention in crash data modeling in recent years, and research have shown that ignoring this factor may lead to a biased estimation of the modeling parameters. This paper examines two spatial autocorrelation indices: Moran’s Index;and Getis-Ord Gi* statistic to measure the spatial autocorrelation of vehicle crashes occurred in Boone County roads in the state of Missouri, USA for the years 2013-2015. Since each index can identify different clustering patterns of crashes, therefore this paper introduces a new hybrid method to identify the crash clustering patterns by combining both Moran’s Index and Gi*?statistic. Results show that the new method can effectively improve the number, extent, and type of crash clustering along roadways.

Prediction method for risks of coal and gas outbursts based on spatial chaos theory using gas desorption index of drill cuttings

Based on the evolution of geological dynamics and spatial chaos theory, we proposed the advanced prediction an advanced prediction method of a gas desorption index of drill cuttings to predict coal and gas outbursts. We investigated and verified the prediction method by a spatial series data of a gas desorption index of drill cuttings obtained from the 113112 coal roadway at the Shitai Mine. Our experimental results show that the spatial distribution of the gas desorption index of drill cuttings has some chaotic charac- teristics, which implies that the risk of coal and gas outbursts can be predicted by spatial chaos theory. We also found that a proper amount of sample data needs to be chosen in order to ensure the accuracy and practical maneuverability of prediction. The relative prediction error is small when the prediction pace is chosen carefully. In our experiments, it turned out that the optimum number of sample points is 80 and the optimum prediction pace 30. The corresponding advanced prediction pace basically meets the requirements of engineering applications.

Integration of Geological, Geophysical and Seismological Data for Seismic Hazard Assessment Using Spatial Matching Index

Probabilistic seismic hazard assessment (PSHA) takes into account as much data as possible for defining the initial seismic source zone model. In response to this, an algorithm has been developed for integration of geological, geophysical and seismological data through a spatial index showing the presence or absence of a potential seismic source feature in the input data. The spatial matching index (SMI) is calculated to define the coincidence of independent data showing any indications for existence of a fault structure. It is applied for hazard assessment of Bulgaria through quantification of the seismic potential of 416 square blocks, 20 × 20 km in size covering the entire territory of Bulgaria and extended by 20 km outside of the country borders. All operations are carried out in GIS environment using its capabilities to work with different types of georeferenced spatial data. Results show that the highest seismic potential (largest SMI) is observed in 56 block elements (13% of the territory) clearly delineating cores of the source zones. Partial match is registered in 98 block elements when one of the features is missing. Not any evidence for earthquake occurrence is predicted by our calculation in 117 elements, comprising 28% of the examined area. The quantitative parameter for spatial data integration which is obtained in the present research may be used to analyze information regardless of its type and purpose.

河南省水资源利用效益的时空演化及障碍因子分析

为了促进水资源可持续利用,采用综合指数法测算了河南省水资源利用效益,运用ArcGIS 10.8软件分析了重心演变趋势,并运用障碍度模型探讨了障碍因子。结果表明:1)河南省各市水资源综合利用效益指数均呈波动上升趋势,其中安阳生态效益指数增幅最大、商丘降幅最大,商丘经济效益指数增幅最大、平顶山增幅最小,濮阳社会效益指数增幅最大、鹤壁降幅最大;2)河南省水资源利用效益指数重心分布于郑州和许昌,呈现向东北迁移趋势,其中生态效益指数、经济效益指数和社会效益指数重心分别呈现向东南、东和东北迁移趋势;3)河南省水资源利用效益主要障碍因子区域差异明显,其中污水处理率、万元工业增加值用水量、亿元农业总产值用水量、城市建成区供水管道密度、自来水普及率分别是鹤壁、漯河、周口3个地级市,洛阳、平顶山2个地级市,安阳、新乡、焦作、濮阳、济源5个地级市,许昌、三门峡2个地级市,南阳、商丘、驻马店3个地级市第一大障碍因子;城市建成区绿化覆盖率、万元GDP用水量、人均日生活用水量分别是开封、信阳、郑州的第一大障碍因子。基于研究结果,提出了提升河南省水资源利用效益的建议。

青年发展型城市环境指数测度及空间差异分析

基于国家45个青年发展型试点城市的宏观数据,构建青年发展型城市环境指数测度指标体系。采用EM-TOPSIS模型测度各城市的维度得分以及综合水平,使用变异系数法测量四大地区内城市的环境指数差异,结合地理探测器来探测七大环境因子的空间分异解释和驱动能力。结果显示:生活环境的评价均分最高,其次是规划环境,就业环境评价均分最低;四大地区内部城市在各维度表现上具有一定的差异性,其中西部和东部地区差异性最大,部分城市在各环境指数间具有明显的不平衡性;通过计算,将45个城市划分为高水平、中等水平、低水平等级;在因子与交互探测上,健康环境因子和就业环境因子的解释能力最强,其次是规划环境因子和经济环境因子,且两因子间的交互驱动力都强于各个单因子的驱动力。

Oracle Spatial在GIS中的应用

本文介绍了Oracle数据库系统中对空间数据存储的解决方案,并针对对象关系模式下空间数据的存储和管理,结合自己的实际工作体会提出了一些具体的解决方法。

基于SQL Server Spatial的空间数据的组织与查询

论述了SQL Server Spatial技术理论,探讨了空间数据导入、索引的创建以及空间数据的查询方法。并以3维激光扫描获取的点云数据为例,采用C#连接SQL Server数据库,对点云数据进行了组织及查询,并在MapOb-ject组件下进行可视化。试验证明,建立空间索引后点云数据的检索效率较高。

基于Oracle Spatial的空间数据索引

本文介绍了地理信息系统(GIS)中的属性数据和空间数据,详细阐述了基于OracleSpatial的空间数据索引的分类,R树索引和四叉树索引的特点,以及创建索引时应注意的细节,还进一步比较了这两类索引各自的优缺点和适用条件,为应用时选择何种类型的索引提供了参考标准。

基于Oracle Spatial的GIS数据组织及查询

G IS的一个难点是实现空间数据和属性数据的一体化存储和管理,研究用Oracle Spatial技术来解决这个问题。在确定了采用对象—关系模型来存储G IS数据后,比较了空间数据的两种导入方式,在此基础上,选用EasyLoader工具将G IS数据导入到Oracle数据库中,再用四元树索引为其建立索引。最后,选择Java作为开发工具,采用JDBC方式与Oracle数据库相连并实现了对G IS数据的查询。

中国内地鸟类物种多样性特征及影响因素

中国鸟类物种多样性的研究存在空间尺度的局限性。以中国省级行政区划为地理统计单元,采用eBird公民科学数据,引入G-F指数来量化评价鸟类物种多样性特征。在此基础上,利用空间自相关分析方法探究鸟类物种多样性的空间分布特征,并建立地理加权回归模型分析鸟类物种多样性影响因子的空间异质性。研究结果表明:(1)中国鸟类物种多样性总体呈现由东南沿海向西北内陆逐渐减少的空间分布趋势,并呈现经度条带分异的空间规律;(2)各影响因子对鸟类物种多样性的影响程度存在明显的空间差异:气温因子呈现北高南低的空间分布特征,降雪因子对鸟类物种多样性的影响主要局限于东北省份,水文因子对鸟类物种多样性的影响程度呈现从南北两侧向中部省份逐级递减的空间分布特征,植被因子对鸟类物种多样性的影响程度则呈现由西南省份向东北省份逐渐减弱的趋势,人类活动因子对鸟类物种多样性影响表现出纬度方向集聚相连的空间分布特征。研究结果有助于丰富鸟类物种多样性的研究,并为鸟类资源保护和生物多样性维持提供科学依据。

中国西部地区生态用地稳定性及空间格局分析

中国西部地区是维护全国生态安全的重要屏障,西部大开发战略实施20多年以来,一系列重大生态建设工程使西部地区的生态状况和生态服务发生了重要变化,西部地区生态稳定性格局的探索对宏观生态用地管理具有重要意义。本文基于西部地区土地利用/土地覆盖遥感监测数据对2000—2020年西部地区生态用地稳定性指数的时空动态变化进行分析。结果表明:1)2000—2020年西部地区生态用地总量呈先下降后增加的趋势,在2000—2010年生态用地面积减少2232.71万hm^(2),2010—2020年面积增加102.56万hm^(2)。两个时段的稳定性生态用地空间分布变化不大,稳定性生态用地以草地与森林为主。2)2000—2010年和2010—2020年西部地区整体生态用地稳定性指数分别为48.46%和53.68%。2000—2020年生态稳定性指数存在显著聚集,生态用地稳定性格局以高-高聚集区和低-低聚集区为主,两种类型生态稳定性空间前后期分别占总面积的48.17%和46.70%;高-高聚集区、高-低异常值区面积呈增加趋势,低-低聚集区、低-高异常值区呈下降的趋势。3)冷点区域总面积减少1026万hm^(2),热点区域总面积增加206万hm^(2),表明西部地区生态稳定性指数在缓慢提升的同时,稳定性生态用地的集聚效应也有所提高。

兴义市近二十年耕地时空演变分析

贵州省兴义市岩溶地貌占71.5%,丘陵占20.5%,平坝占7.2%,耕地属稀缺资源。因此,探明其耕地时空演变历程,可为发展和保护该地区农业资源提供重要参考。以兴义市2000—2020年期间每隔五年选一期,共五期耕地空间变化为研究对象,运用耕地丰度指数法、核密度分析法、空间自相关解析法等方法,构建耕地时空演变研究体系。研究结果表明:①兴义市耕地时空分布密集程度不均衡。在空间上,主要分布于东北和东南部,其中鲁屯镇和丰都街道分布最密集。在时间上,耕地面积2000—2005年增加,2005—2010年减少,2010—2015年增加,2015—2020年减少,时间分布变化幅度大,其中2015—2020年的变化幅度最大。②兴义市耕地地块集散中心变化较稳定,但地块数整体呈逐年递减趋势,其间由东北和中部向西北、南部递减。③兴义市耕地在空间中存在正相关性,即耕地空间分布呈集聚状态,体现在耕地面积比重的全局Moran's I值逐年增加。

Analysis on the Spatial Pattern of Land Use in Urban Rural Fringe Zone——A Case Study of Xigu District in Lanzhou City

This study aimed to provide theoretical basis for an optimized land use of Xigu District in Lanzhou City,Gansu Province.With the support of GIS platform,structural characteristics of 11 land use types in Xigu District were analyzed by utilizing fragmentation degree,shape index,fractal dimension,diversity and such landscape pattern indices.

农村相对贫困时空格局与驱动因素分析——以临沂市为例

采用全局Moran’s I指数、空间扫描统计和地理探测器分析了2016—2020年临沂市乡镇贫困发生率的时空格局特征及其驱动因子。结果表明:①全局Moran’s I指数分析发现,贫困地区贫困人口空间分布的集聚性特征有所减弱,但仍具有显著的空间正相关性;②相对贫困聚集区内相对贫困人口在逐步减少,但减少趋势在时间上存在差异;③地理探测器结果显示,对相对贫困空间分异的解释能力存在显著差异,在不同分区中以人均耕地解释力最显著,交互作用结果表现为双因子增强和非线性增强,其中农业生产条件变量和区域社会资源作用最显著。

基于Oracle Spatial的地质空间数据管理系统的研究与实现

从地质空间数据组织与管理的发展历程出发,在研究Oracle Spatial理论的基础上,分析了地质空间数据在Oracle Spatial中的组织、存储方式和空间索引机制;应用Oracle Spatial的开发接口和JBuilder集成开发环境,开发实现了地质空间数据库管理系统,提供了管理与检索地质空间数据功能;介绍了系统部署与运行方案。