Estimating spatial efficiency using cyber search,GIS, and spatial optimization: a case study of fire service deployment in Los Angeles County

ABSTRACT

The efficiency of public investments and services has been of interest to geographic researchers for several decades. While in the private sector inefficiency often leads to higher prices, loss of competitiveness, and loss of business, in the public sector inefficiency in service provision does not necessarily lead to immediate changes. In many cases, it is not an entirely easy task to analyze a particular service as appropriate data may be difficult to obtain and hidden in detailed budgets. In this paper, we develop an integrative approach that uses cyber search, Geographic Information System (GIS), and spatial optimization to estimate the spatial efficiency of fire protection services in Los Angeles (LA) County. We develop a cyber-search process to identify current deployment patterns of fire stations across the major urban region of LA County. We compare the results of our search to existing databases. Using spatial optimization, we estimate the level of deployment that is needed to meet desired coverage levels based upon the location of an ideal fire station pattern, and then compare this ideal level of deployment to the existing system as a means of estimating spatial efficiency. GIS is adopted throughout the paper to simulate the demand locations, to conduct location-based spatial analysis, to visualize fire station data, and to map model simulation results. Finally, we show that the existing system in LA County has considerable room for improvement. The methodology presented in this paper is both novel and groundbreaking, and the automated assessments are readily transferable to other counties and jurisdictions.     

中国省际人口迁移的多边效应机制分析

区际人口迁移不仅与迁出地和目的地的要素特征以及距离有关,而且还受到周边迁移流的影响.基于网络自相关理论,利用"六普"省际人口迁移数据和相关统计资料,在重力模型的基础上考虑迁移流之间可能存在的几种空间依赖形式,构建中国省际迁移流的空间OD模型,初步揭示区域经济社会等因素及其空间溢出效应对省际人口迁移的影响,并就区域要素变化对整个省际人口迁移系统产生的"连锁反应"进行了模拟.结果表明:① 中国省际迁移流之间存在显著的网络自相关效应.目的地和迁出地的自相关效应皆为正,导致迁入和迁出流的空间效仿行为;迁出地和目的地周边则出现负的自相关效应,导致迁移流的空间竞争行为;② 区域经济社会等因素通过网络空间关系对周边地区产生的多边溢出效应导致迁移流在空间上集聚.其中,距离衰减效应位居各要素之首,其溢出效应进一步加剧距离的摩擦作用;对目的地而言,区域工资水平和迁移存量超过GDP的影响并产生正的溢出效应,促进周边地区吸引更多的外来人口;对迁出地而言,人口规模和迁移存量产生正的溢出效应,推动周边地区人口外迁;③ 区域要素变化潜在地对整个省际人口迁移系统产生一系列"连锁反应",震荡中心及其周边区域的迁移流波动较大.江苏省GDP增长5%的模拟结果表明,江苏迁往全国其他省份的人口数量都有不同程度地减少,而其他省份入迁人口均有所增加.相对而言,江苏周边省份的迁入或迁出流受到的波动较大,偏远省份波及较小,这是传统的重力模型所无法解释的.     

中国装备制造业产学研合作创新网络初探

产学研合作是区域创新的主要途径和重要来源.以中国装备制造产业为例,基于中国知识产权局1985-2012年间的合作发明专利数据,借助SPSS,UCINET,ArcGIS等定量分析工具,对中国装备制造产业合作网络的创新主体结构,空间结构及其演变,创新合作的空间尺度的影响因素进行了分析.研究发现,民营企业,高校在中国装备制造产业创新网络中的地位不断上升,数量不断增加,且已经成为重要的创新源泉;市域空间合作成为发达地区城市产学研创新合作最重要的空间单元,国家空间是欠发达地区城市产学研创新合作的主要空间载体;理工科高校等科技资源的空间集聚态势是导致创新网络层级特征的主要因子,科技资源富集的行政中心如直辖市,省会城市等发达城市成为最重要的资源集聚地,创新源泉和创新合作对象.     

中国“四纵四横”高铁网络可达性综合评估与对比

传统测算可达性的方法较为单一,缺乏多层面、多角度的综合研究和对比分析。基于时间、经济与重心视角利用可达性模型并结合ArcGIS 空间分析手段探究高铁通车前后沿线城市可达性的动态变化;利用综合变异系数、层级分析法和改进的哈夫模型分析高铁可达性空间演变特征及规律,构建高铁可达性评价体系并结合熵权法定量评估各高铁可达综合实力。研究表明：京广、京沪可达综合实力最强,沪昆、杭福深次之,沪汉蓉、哈大、青太再次之,郑西、兰新可达实力最弱;全国高铁可达性强弱变化呈明显地带性规律,东、中部高铁可达性强于东北,东北强于西部,纵向高铁强于横向;经济潜力的增加率明显高于加权平均旅行时间的减少率,可达性重心偏移驱使不同等时圈蔓延交叠;高铁以“核心—核心”逐步向“核心—网络”空间链接模式过渡,产生上海、北京、广州、深圳4 个高铁“国家服务中心”,天津、武汉、重庆等6 个“大区域服务中心”,形成“多中心”高铁服务格局以及日益庞大而复杂的高铁特质空间集群;高铁网络影响下的中国区域空间格局的渐变与重塑日趋复杂,“T”型轴带呈现出由空间极化向空间均衡转变,跨城流动性特征突显,加速空间对接与同城化进程。     

中国城市流动人口户籍迁移意愿的空间格局及影响因素——基于2012年全国流动人口动态监测调查数据

基于2012年全国流动人口动态监测调查数据和相关统计年鉴数据,对中国地级以上城市流动人口的户籍迁移意愿、空间格局及影响因素进行了系统分析。研究发现,中国城市流动人口户籍迁移意愿的整体水平并不高;等级高、规模大的城市流动人口的户籍迁移意愿高,而等级低、规模小的城市流动人口的户籍迁移意愿低;沿海城市群流动人口的户籍迁移意愿高,其他城市流动人口的户籍迁移意愿低,但内陆部分省会城市和交通区位与资源禀赋较好的中小城市也已经形成了一批流动人口的户籍迁移意愿高值区。中国城市流动人口户籍迁移意愿的空间分布特征受到流入城市和流动人口自身双重力量的影响,流入城市因素的正向影响作用大于流动人口自身因素。其中,流入城市的社会、经济发展水平和流动人口在流入城市的社会融合程度是核心要素,对城市流动人口户籍迁移意愿的提升具有正向的促进作用,而流动人口过于集中在次级劳动力市场的就业特征和较高的家庭财富与收入对户籍迁移意愿的提升却具有显著的抑制作用。最后,提出了相关政策启示。     

一种开源软件集成的空间矢量数据在线采集方法

空间数据是GIS应用的基础,经济高效地从网络获取空间数据具有重要意义。文章主要研究了网络地图环境下利用Web GIS技术和开源软件实现空间矢量数据在线采集和数据库存储的方法和技术。并且使用Google Map API、Ajax技术和Apache、My SQL开源软件开发一个基于Web平台的原型系统,实现了基于网络地图的矢量数据的在线获取、数据库存储、在线显示和数据库访问服务接口等功能,为获取空间数据提供了一种新方法。     

Vulnerability of Kuwait coast to sea level rise

Assessing coastal vulnerability to sea level rise (SLR) at local and regional scales is a fundamental step for designing successful long-term coastal management plans. This study was thus designed to assess Kuwait coastal vulnerability to SLR at four scenarios (.5, 1, 1.5 and 2 m). Potential inundated areas and the number of people at risk were estimated based on these SLR scenarios. A coastal vulnerability index (CVI) map of Kuwait was then computed based on the lowest scenario using eight parameters: elevation, coastal slope, geomorphology, distance to 20-m isobath, population, land use, cultural heritage and transportation. The geographic distribution of inundated areas at an SLR of .5 m revealed that the northern islands of Kuwait and coastal areas along Kuwait Bay would be highly impacted, whereas the coastal area near Shuaibah Port was the most influenced among the southern coasts. Most of the coastal area exhibited a moderate vulnerability to SLR, especially the northern islands. This study presented an initial vulnerability assessment for Kuwait coasts to SLR, which can be extended with more variables. The integrated remote sensing and geographic information system methodology demonstrated in this study can be applied in similar studies elsewhere.     

Diagnosis of earth-fill dams by synthesised approach of sounding and surface wave method

The spatial distribution of the strength inside the earth-fill is identified by the sounding tests. In this research, the Swedish weight sounding (SWS) is employed, and the spatial high-density test is performed to identify the spatial correlation structure. Furthermore, the synthesised approach of the SWS and surface wave method, which is one of the geophysical method, is proposed to compensate the shortage of each approach. Consequently, the correlation structure of an earth-fill could be identified accurately, and the high resolution of the spatial distribution could be visualised based on the survey results.     

Exploring the spatial distribution patterns of South African Cape hakes using generalised additive models

We developed delta generalised additive models (GAMs) to predict the spatial distribution of different size classes of South African hakes, Merluccius capensis and M. paradoxus, using demersal trawl survey data and geographical (latitude and longitude) and environmental features (depth, temperature, bottom dissolved oxygen and sediment type). Our approach consists of fitting, for each hake size class, two independent models, a binomial GAM and a quasi-Poisson GAM, whose predictions are then combined using the delta method. Delta GAMs were validated using an iterative cross-validation procedure, and their predictions were then employed to produce distribution maps for the southern Benguela. Delta GAM predictions confirmed existing knowledge about the spatial distribution patterns of South African hakes, and brought new insights into the factors influencing the presence/absence and abundance of these species. Our GAM approach can be used to produce distribution maps for spatially explicit ecosystem models of the southern Benguela in a rigorous and objective way. Ecosystem models are critical features of the ecosystem approach to fisheries, and distribution maps constructed using our GAM approach will enable a reliable allocation of species biomasses in spatially explicit ecosystem models, which will increase trust in the spatial overlaps and, therefore, the trophic interactions predicted by these models.