东山乌礁湾海滩表层沉积物粒度时空变化分析

为了进一步了解海岛岬湾海岸表层沉积物粒度的时空分布特征和形成机制,作者以福建东山岛乌礁湾为典型研究区,通过秋、春、夏3个不同季节海滩表层沉积物的采集和点位测量,综合应用激光法和筛析法进行粒度测定。结果表明,东山乌礁湾海滩表层沉积物以0.16～0.50 mm之间的中、细砂为主,并含有少量的粗砂和细砾,这与区域砂质沉积背景有关;湾内从南到北剖面沉积物粒径由粗砂到细砂逐渐变细,主要受剖面地形、局地物源、季节性风浪作用和近岸往复水动力的影响。时间变化上,各取样站位表现出沉积物粒径粗、细不同程度的多种变化趋势,以秋季为参考,整体上表现为由南到北粒级的变小、增大和稳定,这与东北、南南西季风影响下的浪、潮作用以及沿岸流系格局变化下的水动力环境有关。     

Assessing potential spatial and temporal conflicts in Washington's marine waters

This paper uses spatial, temporal, and use-intensity data for 27 major marine uses in Washington waters to feature a method for assessing potential use conflicts in a variety of scenarios. The study represents a first step towards quantifying potential conflicts within Washington’s Marine Spatial Planning (MSP) study area by using a cumulative analysis to highlight high- and low-use intensity areas and the novel Marine Potential Conflict Index (MPCI), which incorporates space, time, and intensity of use, to quantify pairwise potential conflicts between uses. About 10% of pairs of uses do not overlap spatially and are likely compatible with one another. Temporally, the number of uses peaks in July and August and falls during January and February. Additionally, the MPCI identified three important use types with a substantial degree of potential conflict: commercial fishing, tribal fishing, and shipping. External data were used in three cases to ground-truth the analysis, as a limited test of its utility in managing any potential conflict. This article assesses the extent of Washington’s existing marine uses along spatial, temporal, and intensity axes, and more broadly provides a straightforward way to examine potential conflicts between marine uses.     

基于地理格网分级法提取的中国传统村落空间分布

中国传统村落真实地记录了建筑、民俗民风和较原始的民居空间形态,是千百年来人类与自然和谐共存的生活基础。随着城市化进程加快,传统村落的存续受到了很大的挑战,为了更好地保护利用传统村落,对其进行多视角的研究尤为重要,除了微观层面的具体保护措施外,还应加强宏观层面的空间分布研究。地理格网是表达复杂地理现象、综合分析自然与人文数据、模拟地理系统功能与行为的基本方法。本文从百度影像地图提取村落坐标,并截取遥感影像作为村落点数据的判断补充,在此基础上,运用地理格网的分级法,对国家公布的三批中国传统村落(2555个)数据进行空间格局分析,结果表明：这些村落主要分布在中国东南部,如落在一级格网Ⅰ18、Ⅰ19就分别有586、781个村落,占三批传统村落总数的96.6%。通过对二级和三级格网的村落分布离散性进行分析,使传统村落的空间分布数据结构更加系统和清晰有序,为合理构建其数据库提供了框架基础。     

Effects of demand estimates on the evaluation and optimality of service centre locations

Public service systems, such as emergency health care, police or fire brigades, are critical for day-to-day functioning of the society. To design and operate these systems efficiently much data needs to be collected and properly utilised. Here, we use the OpenStreetMap (OSM) data to model the demand points (DPs), which approximate the geographical location of customers, and the road network, which is used to access or distribute services. We consider all inhabitants as customers, and therefore to estimate the demand, we use the available population grids. People are changing their location in the course of the day and thus the demand for services is changing accordingly. In this paper, we investigate how the used demand estimate affects the optimal design of a public service system. We calculate and compare efficient designs corresponding to two demand models, a night-time demand model when the majority of inhabitants rest at home and the demand model derived from the 24-hour average of the population density. We propose a simple measure to quantify the differences between population grids and we estimate how the size of differences affects the optimal structure of a public service system. Our analyses reveal that the efficiency of the service system is not only dependent on the placement strategy, but an inappropriate demand model has significant effects when designing a system as well as when evaluating its efficiency.     

Interaction between scale and scheduling choices in simulations of spatial agents

Spatial simulations are a valuable tool in understanding dynamic spatial processes. In developing these simulations, it is often required to make decisions about how to represent features in the environment and how events unfold in time. These spatial and temporal choices have been shown to significantly alter model outcomes, yet their interaction is less well understood. In this paper, we make use of a simple group foraging model and systematically vary how features are represented (cell size of the landscape) as well as how events unfold in time (order in which foragers take action) to better understand their interaction. Our results show similar nonlinear responses to changes in spatial representation found in the literature, and an effect of the order in which agents were processed. There was also a clear interaction between how features are represented and how events unfold in time, where, under certain environmental representations results were found to be more sensitive to the order in which individuals were processed. Furthermore, the effects of feature representation, scheduling of agents, and their interaction were all found to be influenced by the heterogeneity of the spatial surface (food), suggesting that the statistical properties of the underlying spatial variable will additionally play a role. We suggest that navigating these interactions can be facilitated through a better understanding of how these choices affect the decision landscape(s) on which agents operate. Specifically, how changes to representation affect aggregation and resolution of the decision surface, and thereby the degree to which agents interact directly or indirectly. We suggest that the challenges of dealing with spatial representation, scheduling, and their interaction, while building models could also present an opportunity. As explicitly including alternate representations and scheduling choices during model selection can aid in identifying optimal agent–environment representations. Potentially leading to improved insights into the relationships between spatial processes and the environments in which they occur.     

Opportunistic natural experiments using digital telemetry: a transit disruption case study

ABSTRACT

In the past decade society has entered a technological period characterized by handheld computing that supports input and processing from numerous sensors. Today’s mobile phones offer the ability to integrate input from sensors monitoring various external and internal sources (e.g., accelerometer, magnetometer, microphone, GPS, wireless Internet, and Bluetooth). Furthermore, these raw inputs can be integrated and processed in ways that can offer novel representations of human behaviour. As a result, new opportunities to examine and better understand human spatial behaviour are available; one such application is the constant monitoring of a group of people over an extended period of time. Such a research setting lends itself to natural experiments that emerge as a result of regular and on-going observations. We report here on the observation of a natural experiment that took place in the context of a month-long monitoring study of 28 participants using mobile phone-based ubiquitous sensor monitoring. The implications for public health and transportation planning are discussed.     

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.