基于社会属性的北京市居民居住与就业空间集聚特征

制度转型期,中国城市居民社会空间发生了新的变化,居民居住和就业空间组织也变得更为复杂,并引起了广泛关注。基于2010 年问卷调查数据,采用缓冲区、最近邻层次聚类和Ripley K函数等空间分析方法对北京城市不同社会属性居民的居住和就业空间分布特征进行实证分析。研究发现：① 总体上,北京城市居民居住和就业空间圈层分异明显。在各圈层内部,不同人群的居住和就业空间分布比例亦存在相对差异;职住空间错位程度表明距市中心15 km左右是城市就业功能和居住功能主导地位转化的分界线;职住平衡度整体上呈现出由内圈层到外圈层递减的趋势,但高收入阶层和年轻白领的职住平衡度相对较低。② 不同人群居住与就业空间集聚特征存在明显差异。一般平民居住和就业均呈散点状集聚;年轻打工族居住和就业集聚区域紧邻,主要集聚在四环以内的城市东部区域;高收入阶层居住呈现“小集中、大分散”集聚特征,就业集聚区多集中在四环以内的城市东部和西北部区域;年轻白领居住集聚区呈现城市西部条带状和东部散点状相结合特征,就业集聚区主要在中关村和CBD为中心的两条轴状区域。③ 不同人群居住和就业空间集聚的尺度特征较为相似,呈现随距离增加“先增后减”变化趋势,但距离阈值存在差异。表现为高收入群体居住空间可选范围较小,一般平民就业空间可选范围较小,而年轻白领居住和就业空间可选范围均较大。     

Gender Differences in Chronic Exposure to Traffic-Related Air Pollution—A Simulation Study of Working Females and Males

The objective of this study was to identify spatial variability in exposure to outdoor traffic-related air pollution with specific emphasis on comparing exposure estimates for working females and males across a metropolitan area. A spatial exposure simulation model was used to estimate annual average exposure to traffic-related nitrogen dioxide for males and females reporting regular work in census tracts other than that of their residence, in Vancouver, British Columbia. The model produced estimates of annual average exposure in six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work, and in-vehicle other) using time-activity patterns and work flow data, for males and females in each of 382 census tracts. This allowed for the identification of spatial variations in exposure estimates for each gender, due to mobility within the study region. Indoor sources of nitrogen dioxide were not included in the simulation. No significant differences in estimated total exposure were found between working females and males in general. Small but observable spatial differences, however, were found between working females and males at the 90th percentile of the exposure distributions associated specifically with the work indoor microenvironment. These were highest in suburban areas (+3 μ g/m³ for females, relative to total exposures in the range of 26 to 37 μ g/m³ annual average hourly nitrogen dioxide). These results identify specific geographic locations in the study area where personal monitoring studies might be warranted and suggest that the inclusion of workplace locations in multivariate modeling could be useful to further understand differences in estimated exposures.     

坡面草被覆盖对坡沟侵蚀产沙过程的影响

By scouring experiments, the changeable process and characteristics of sediment yield in the hillslope-gully side erosion system with different coverage degrees and spatial locations of grass were studied. Five grass coverage degrees of 0, 30%, 50%, 70%, 90%, three spatial locations of grass (upslope, mid-slope, low-slope) and two water inflow rates of 3.2 L/min, 5.2 L/min were applied to a 0.5 by 7 m soil bed in scouring experiments. Results showed that the sediment yield decreased with the increase of grass coverage degree at 3.2 L/min water inflow rate in scouring experiments and the sediment yield with different grass locations on the sloping surface was in the order of upper > middle > lower. At 5.2 L/min water inflow rate, the differences of sediment yield among various grass coverage degrees were increased, whereas the changeable tendency of sediment yield with different grass locations on the whole sloping surface was not very obvious. The proportion of sediment yield from the gully side increased in an exponential relationship with the increase of grass coverage degree. When the grass was located on the lower position of hillslope, the influence for accelerating gully erosion is the greatest. Foundation: National Basic Research Program of China, No.2007CB407201; National Key Technology R&D Program, No.2006BAB06B01-06; Science and Technique Development Foundation of YRIHR, No.200603 Author: Li Mian (1968–), Ph.D and Senior Engineer, specialized in soil erosion.     

Modeling the criminal''s location choices in urban areas

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UK-based terrorists' antecedent behavior: A spatial and temporal analysis

Background and purposeTerrorism is a real and present danger. The build-up to an attack includes planning, travel, and reconnaissance which necessarily require the offender to move through their environment. Whilst research has examined patterns of terrorist attack locations, with a few exceptions (e.g. Rossmo & Harries, 2011), it has not examined the spatial behavior of the terrorists themselves. In this paper, we investigate whether the spatial mobility patterns of terrorists resemble those of criminals (and the wider population) and if these change in the run up to their attacks.MethodUsing mobile phone data records for the ringleaders of four different UK-based terrorist plots in the months leading up to their attacks, we examine the frequency with which terrorists visit different locations, how far they travel from key anchor points such as their home, the distance between sequential cell-site hits and how their range of movement varies as the planned time to attack approaches.ConclusionsLike the wider population (and criminals), the sample of terrorists examined exhibited predictable patterns of spatial behavior. Most movements were close to their home location or safe house, and they visited a relatively small number of locations most of the time. Disaggregating these patterns over time provided mixed evidence regarding the way in which their spatial activity changed as the time to the planned attack approached. The findings are interpreted in terms of how they inform criminological understanding of the spatial behavior of terrorists, and the implications for law enforcement.     

KBGIS-II A knowledge-based geographical information system

Abstract

This paper describes the architecture and working of a recently implemented knowledge-based GIS (KBGIS-II) that was designed to satisfy several general criteria for GIS. The system has four major functions, query-answering, learning, editing and training. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multi-layered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is currently performing all its designated tasks successfully, although currently implemented on inadequate hardware.     

Multistop-based measurements of accessibility in a GTS environment

Abstract

The opportunities available at a demand location are usually measured as the costs of reaching a specified critical number of facilities from that location. This method does not however, account for multistop trips nor for differences in the diversity of supply at the level of individual facilities. In this paper we introduce an alternative measurement method that overcomes these shortcomings. In this method the probability of successfully visiting a specific facility is assumed to be a function of the diversity of supply provided. Trip routes are constructed that have an acceptable probability of success. Then, the expected costs of travelling the optimum route are determined as an indicator of spatial opportunities. The proposed method has been implemented in a GIS environment, using typical GIS data and GIS tools for spatial analysis and display. The results of a case study indicate that the new method, compared to current methods, may lead to different evaluations of the level of opportunities at demand locations.     

Geographical Research about African Americans: A Survey of Journals, 1911–1995

This paper surveys research about African Americans in six geography journals between 1911 and 1995. 176 journal articles about African Americans were identified. A chronological analysis of a subset of these articles shows that it was not until the 1960s that African Americans were studied to any appreciable degree by geographers. Since that time, geographers have continued this research, but unevenly; annual output varies widely. Popular topics have included considerations of spatial distributions, social problems, political participation, the development of black residence areas, and historical and cultural studies of African Americans. Recent research in this area has problematized the concept of “race” and investigated the mutual constitution of racial identity and place.     

Modelling uncertainty and spatial dependence: Stochastic imaging

Abstract

The most vibrant area of research in geostatistics is stochastic imaging, that is, the modelling of spatial uncertainty through alternative, equiprobable, numerical representations (maps) of spatially distributed phenomena. These stochastic images are conditioned to a variety of data accounting for their specific measurement scale and reliability.

Any geostatistical prediction is built on a prior model of spatial correlation that ties data to unsampled values and, equally importantly, unsampled values at different locations together. Since a major goal in the exercise of mapping is to display organization in space, spatial correlation is a necessity. As for uncertainty it is so pervasive that it is imperative to account for it.     

A MULTINOMIAL LOGIT MODEL OF RACE AND URBAN STRUCTURE

This paper examines the influence of race on urban spatial structure in a multinomial logit model of residential and workplace location choice. A unique data set that provides the residence and workplace census tract of workers in the Dallas-Fort Worth CMSA, and their demographic characteristics, makes it possible to explore the joint choice of residence and workplace for workers of different race and ethnicity. The results support established hypotheses in urban economics and urban ecology regarding the disutility of commuting; residential and workplace suburbanization; spatial job search; housing-commuting tradeoff; residential clustering by race, stage of life cycle, and income; and housing tenure choice. With separate models for whites, blacks, and Hispanics, we find evidence of both residential and workplace avoidance of blacks by whites, with less white avoidance of Hispanics. Both Hispanics and blacks are found to seek integrated locations as their incomes rise.     

上海职住优化效应的代际差异

城市的职住关系一直为研究者广泛关注。过剩通勤概念以实际通勤与理论最短通勤的差距反映城市职住关系与通勤状态,是衡量通勤效率和优化潜力的常用指标。国内的过剩通勤研究数量有限,且鲜有从年龄视角考察。本文利用2017年9月上海市手机网格数据,分析不同年龄段居民的职住与通勤状态,采用模拟个人换居的方法测度过剩通勤,并探讨职住关系优化效应的代际差异。结果表明：上海居民的职住关系存在明显的代际差异,青年人是劣势群体,老年人是优势群体,中年人介于其间;上海全市过剩通勤率为69%,职住关系优化的潜力和效应巨大,可使得通勤距离显著减少,代际分异缓和,青年人的获得感最大,城市年龄空间结构更加均衡。提出上海的空间规划和政策应以理想的城市年龄空间结构为目标,以提高人的居住和就业空间的流动性、青年化城市中心、中老年化城市外围为途径。     

Residential Location and White Attitudes Toward Mixed-Race Neighborhoods in Kalamazoo,Michigan

Abstract

Past studies have suggested that white attitudes toward mixed-race neighborhoods in northern metropolises vary spatially. Nonetheless, conflicting hypotheses exist in regard to the nature of these spatial patterns and explanations for them. Data gathered within the Kalamazoo Urbanized Area indicate that white attitudes are significantly related to both: 1) the level of interaction between whites and blacks, and 2) the distance between residence and the Negro neighborhood. Attitudes tend to be more favorable with higher interaction levels, and they tend to be less favorable as distance from the Negro neighborhood increases. When control is made for interaction, the relationship between attitude and distance is greatly weakened, indicating that interaction is the dominant variable. That does not eliminate the spatial component, however, because the racial interaction patterns in Kalamazoo are strongly related to distance from the black residential areas.     

Activity patterns,socioeconomic status and urban spatial structure: what can social media data tell us?

ABSTRACT

Individual activity patterns are influenced by a wide variety of factors. The more important ones include socioeconomic status (SES) and urban spatial structure. While most previous studies relied heavily on the expensive travel-diary type data, the feasibility of using social media data to support activity pattern analysis has not been evaluated. Despite the various appealing aspects of social media data, including low acquisition cost and relatively wide geographical and international coverage, these data also have many limitations, including the lack of background information of users, such as home locations and SES. A major objective of this study is to explore the extent that Twitter data can be used to support activity pattern analysis. We introduce an approach to determine users’ home and work locations in order to examine the activity patterns of individuals. To infer the SES of individuals, we incorporate the American Community Survey (ACS) data. Using Twitter data for Washington, DC, we analyzed the activity patterns of Twitter users with different SESs. The study clearly demonstrates that while SES is highly important, the urban spatial structure, particularly where jobs are mainly found and the geographical layout of the region, plays a critical role in affecting the variation in activity patterns between users from different communities.     

A Review of: “Fractals in Geoscience and Remote Sensing: Proceedings of Joint JRC/EARSel Expert Meeting,Ispra, Italy, 14–15 April 1994. Report EUR 16092 EN,Image Understanding Research Series Vol I. Edited by G. G. Wilkinson,I. Kanellopoulos and J. Megier”

Geographic information systems (GIS) and spatial regression modeling techniques were used to evaluate the spatially prioritized relationships between grave density and various spatial parameters for a total of 5549 grave locations. Solar radiation was the most important predictor of grave density in the Feng‐Shui locations. Similarly, spatial clustering technology identified the fact that high concentrations of grave necessarily accompany the significantly increasing trends of solar radiation. The results of the regression analyses indicate that the grave density could be explained by the four landform parameters alone yielding R ² values of 0.751. In contrast to the typical theory, slope and aspect were not a dominant determining factor upon the dependent variable of grave density. Also, the significantly increasing trends of grave density were not observed in line with a southern direction. A clear verification has been made for the hidden assumptions in Feng‐Shui's long history that its approach is found to be more appropriate in avoiding shadow conditions, rather than exploring the ideal landform location.     

Same space – different perspectives: comparative analysis of geographic context through sketch maps and spatial video geonarratives

ABSTRACT

The importance of including a contextual underpinning to the spatial analysis of social data is gaining traction in the spatial science community. The challenge, though, is how to capture these data in a rigorous manner that is translational. One method that has shown promise in achieving this aim is the spatial video geonarrative (SVG), and in this paper we pose questions that advance the science of geonarratives through a case study of criminal ex-offenders. Eleven ex-offenders provided sketch maps and SVGs identifying high-crime areas of their community. Wordmapper software was used to map and classify the SVG content; its spatial filter extension was used for hot spot mapping with statistical significance tested using Monte Carlo simulations. Then, each subject’s sketch map and SVG were compared. Results reveal that SVGs consistently produce finer spatial-scale data and more locations of relevance than the sketch maps. SVGs also provide explanation of spatial-temporal processes and causal mechanisms linked to specific places, which are not evident in the sketch maps. SVG can be a rigorous translational method for collecting data on the geographic context of many phenomena. Therefore, this paper makes an important advance in understanding how environmentally immersive methods contribute to the understanding of geographic context.     

GENDER DIFFERENCES IN THE JOURNEY TO WORK

It is now well established in geographic research that women commute shorter distances to work than men. This paper attempts to explore the common features that have emerged from the last two decades of research in various places within a metropolitan context. Three main sets of factors that may cause women to commute shorter distances are recognized: residence, employment, and transportation—each containing both social and spatial aspects. The analysis is centered around the spatial aspect. Most research on employed women seems to be characterized by distinguishing between the central city and the suburbs and thus the conclusions focus mostly upon this. An international comparison of different places shows that gender differences in commuting almost always are greater in the suburbs, from the point of view of both residential and employment dispersions. Directions for future research are suggested. Comparable methodologies will enable the inclusion of additional cities and will broaden the comparison. The examination of gender differences from the perspective of the dispersion of workplaces in metropolitan space should be further developed and analyzed according to a finer spatial scale than that used in looking at the central city vs. the suburbs. It also is suggested that factors of employment and residence should be analyzed differently so that qualitative methods may generate a greater significance for the factors associated with the domestic context. Finally, the investigation of gender differences in commuting and in the location of both residence and employment could lead to consideration of new conceptual frameworks for possible interaction between land used for both purposes within urban space.     

Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning

ABSTRACT

With large amounts of digital map archives becoming available, automatically extracting information from scanned historical maps is needed for many domains that require long-term historical geographic data. Convolutional Neural Networks (CNN) are powerful techniques that can be used for extracting locations of geographic features from scanned maps if sufficient representative training data are available. Existing spatial data can provide the approximate locations of corresponding geographic features in historical maps and thus be useful to annotate training data automatically. However, the feature representations, publication date, production scales, and spatial reference systems of contemporary vector data are typically very different from those of historical maps. Hence, such auxiliary data cannot be directly used for annotation of the precise locations of the features of interest in the scanned historical maps. This research introduces an automatic vector-to-raster alignment algorithm based on reinforcement learning to annotate precise locations of geographic features on scanned maps. This paper models the alignment problem using the reinforcement learning framework, which enables informed, efficient searches for matching features without pre-processing steps, such as extracting specific feature signatures (e.g. road intersections). The experimental results show that our algorithm can be applied to various features (roads, water lines, and railroads) and achieve high accuracy.     

Exploring spatiotemporal heterogeneity in online travel searches: a local spatial model approach

ABSTRACT

Online travel searches are important forms of travel virtual spaces. Previous studies have neglected to analyze the spatial features of the travel searches themselves, and the spatial heterogeneity of their influencing factors. In this study, a travel search index based on the Baidu index was established for analyzing travel searches. Meanwhile, a local spatial model was created for the linear features in order to discuss the spatiotemporal heterogeneity of the influencing factors. The results of this study indicated that travel searches have obvious spatial inequality, and economically developed regions had displayed advantages in the travel search network. The fitting results of the local model were found to be superior to global model. The number of attractions and the GDP of the origin were found to have promoting effects on the travel searches, whereas distances had shown inhibiting effects. These effects presented significant spatiotemporal heterogeneity. It was also found that within the travel search virtual space, the distance effects still existed, but the intensity was weaker than in the real space. The local spatial model for the linear features provided a new spatial analysis method for understanding the travel search network, as well as other types of networks (flow patterns).     

Regularities in Spatial Information Processing: Implications for Modeling Destination Choice

This paper investigates the determinants of spatial knowledge and how our knowledge of space varies according to geographic location. By using data on U.S. city names recalled at 22 test locations, a multivariate model of the information surface specific to each test location is calibrated. This model links the probability of a city being recalled from memory to its distance from the test site, its population size, its location with respect to other cities, and whether or not it is a state capital. The paper then suggests that these recall data provide information on spatial knowledge surfaces from which large-scale spatial choices, such as migration destinations, are made. Results from the analysis lend further evidence to the idea that spatial knowledge is stored and processed hierarchically and that individuals underrepresent information in large clusters. Consequently, the results have important implications for modeling any spatial behavior based on individuals' spatial information surfaces. In particular, the results cast further doubt on the validity of traditional large-scale spatial choice frameworks and lend support to the competing destinations hypothesis.     

ZG市街头抢劫者作案地选择及其影响因素研究

以往关于作案地选择的研究,缺乏考虑不同属性群体间的空间差异。以中国ZG市为例,利用离散空间选择模型,基于不同年龄属性的视角,进行街头抢劫者作案地选择及影响因素的对比分析,并据此提出犯罪防控建议。研究发现：① 不同年龄的街头抢劫者作案地选择存在显著的空间差异。即少年抢劫者趋向在劳动密集型产业集聚区和中小学密集区作案,而年轻的成年抢劫者仅趋向于劳动密集型产业集聚区,但成年抢劫者的作案地却偏向于客运站所在社区及其周边地区。② 年龄相关的活动节点、周围人口的监护作用和青少年人口比例是形成这种空间差异的主要因素。研究结果对犯罪防控与社会治理具有重要的参考意义,如：① 在青少年抢劫者频繁作案的劳动密集型产业集聚区,调控网吧、酒吧等年龄相关活动节点的数量。② 在成年抢劫者作案密集的客运站及其周边社区,规划一定数量周围人口的持续存在,以发挥出更好的监护作用。③ 在青少年人口比例较高的社区,通过问题青少年的摸底调查,加强精准引导与帮扶。论文首次验证了不同年龄的街头抢劫者作案地选择差异及成因,并在理论上弥补了犯罪者作案地选择缺乏细分人群的不足。