Exploring links between juvenile offenders and social disorganization at a large map scale: a Bayesian spatial modeling approach

This paper adopts a Bayesian spatial modeling approach to investigate the distribution of young offender residences in York Region, Southern Ontario, Canada, at the census dissemination area level. Few geographic researches have analyzed offender (as opposed to offense) data at a large map scale (i.e., using a relatively small areal unit of analysis) to minimize aggregation effects. Providing context is the social disorganization theory, which hypothesizes that areas with economic deprivation, high population turnover, and high ethnic heterogeneity exhibit social disorganization and are expected to facilitate higher instances of young offenders. Non-spatial and spatial Poisson models indicate that spatial methods are superior to non-spatial models with respect to model fit and that index of ethnic heterogeneity, residential mobility (1 year moving rate), and percentage of residents receiving government transfer payments are, respectively, the most significant explanatory variables related to young offender location. These findings provide overwhelming support for social disorganization theory as it applies to offender location in York Region, Ontario. Targeting areas where prevalence of young offenders could or could not be explained by social disorganization through decomposing the estimated risk map are helpful for dealing with juvenile offenders in the region. Results prompt discussion into geographically targeted police services and young offender placement pertaining to risk of recidivism. We discuss possible reasons for differences and similarities between the previous findings (that analyzed offense data and/or were conducted at a smaller map scale) and our findings, limitations of our study, and practical outcomes of this research from a law enforcement perspective.     

The need for psychiatric care in England: a spatial factor methodology

To ensure health resources are equitably distributed, composite indices of population morbidity or “health need” are often used. Measures of the dimensions of population morbidity (e.g. socioeconomic deprivation) relevant to health need are typically not directly available but indirectly measured through census or other sources. This paper considers measurement of latent population morbidity constructs using both health outcomes (e.g. hospital admissions, mortality) and observed area social and demographic indicators (e.g. census data). The constructs are allowed to be spatially correlated between areas, as well as correlated with one another within areas. The health outcomes may depend both on the latent constructs and on other relevant covariates (e.g. bed supply), with some covariates possibly measured only at higher (regional) scales. A case study considers variations in psychiatric admissions in 354 English local authority areas in relation to two latent constructs: area deprivation and social fragmentation.      

A GIS Analysis of the Relationship between Criminal Offenses and Parks in Kansas City,Kansas

Most urban green space research focuses on the social benefits of parks and recreational areas. However, in areas with high levels of resource deprivation and physical disorder, parks may function as criminal marketplaces. Parks in such areas may cease to provide net benefits to the surrounding community and instead serve as a vector for criminal activity. Parks in eastern Kansas City, Kansas, are examined in terms of the probability of criminal marketplaces and beneficial social contribution. Variables for resource deprivation and social disorder are calculated for the study area and compared to national aggregates to identify which parks may behave as criminal marketplaces. In such cases, parks should exhibit an inverse relationship between distance from a park and number of criminal offenses per acre. Evaluating the incidence of crime near parks using geographic information systems (GIS) buffer analysis, proximity analysis, and spatial statistics demonstrates that parks in areas of extreme resource deprivation do not serve beneficial social roles, and some parks contradict conventional criminal justice and urban economic theory.     

陕北干旱区景观生态风险空间分异特征及驱动因素分析

陕北黄土高原属于生态脆弱区,是国家生态修复重点项目区。本文以陕北榆林市2000—2020年3期土地利用数据为数据源,用网格法构建基于景观格局的综合生态风险指数模型,定量分析了榆林市景观生态风险时空分布,并采用地理探测器、R和Origin软件等工具定量分析了土地利用与生态风险的耦合关系。结果表明:2000—2020年该地区生态风险整体趋于下降,低生态风险区面积增加、高生态风险区面积逐渐较少且向西北方向偏移;中风险区域面积逐年增加,该区域仍存在较强潜在生态风险;在人类活动影响下的林地、草地面积变化,以及自然胁迫是驱动景观生态风险变化的主要因素。     

Coupling of remote sensing data and environmental-related parameters for dengue transmission risk assessment in Subang Jaya,Malaysia

In Malaysia, the endemic level of dengue fever (DF) has already changed morbidity indicators, and the magnitude of these incidences in the last few years has surpassed the incidences of all other diseases of compulsory notification. The reasons for the dramatic emergence of DF are complex and not well understood. There are many factors that contribute to the epidemiological conditions that favour viral transmission by the main mosquito vector. This study, therefore, is filling this gap by analysing the impact of dengue incidence at a local (Subang Jaya) scale using environmental factors. Meteorological data and land-use pattern were consolidated using geographic information system (GIS) and its components as an analytical tool. We have shown that weather variables (relative humidity, temperature and precipitation) have significant correlation with DF incidence with seasonal variation. Besides land-use pattern, DF incidence shows the higher distribution in the residential area, followed by commercial and industrial area. This is due to the higher population density in residential area as well as favourable places for the breeding of dengue-carrying Aedes mosquitos created by humans in the residential area, especially one-storey houses. The analysis on the trends of DF incidence towards various housing types indicate that most of the victims’ houses fall into interconnection houses and mixed houses types compared to the independent houses area. The outcome driven from this analysis suggested that each character of the environmental factors has their own risk towards dengue incidence. In line with that, it is possible to develop a dynamic model of DF transmission using the knowledge produced by this comprehensive time series data and the results provided by the different analyses.     

Employing Internet GIS Surveys to Characterize Recreational Boating Travel Patterns

Spatial factors are fundamental features of the tourism and recreation phenomenon. In terms of recreational boating, scholars are interested both in boaters' spatial distribution and movement patterns and in the factors associated with their movements, e.g. travel costs, environmental impacts, and social impacts of the movements. Spatial factors are also key to policymakers' decisions about where to establish new boating facilities, how protected areas are used by boaters and in crafting policy that minimizes conflict between recreational boating and other waterway uses. However, systematic studies regarding the recreationist movement are scant, especially at the fine geographic level. One reason for the lack of research is that gathering spatial data presents significant practical problems. In the Florida Saltwater Fishing Study, we integrated Google Map APIs into the online survey instrument to collect spatially‐referenced data regarding boaters' movement on water. Results appear to be accurate, highly cost effective, and easily integrated with other survey information such as angler catch, effort, expenditures and attitudes.     

地类扩散模型在徐州市火灾风险评价中的应用

城市区域火灾风险评价是城市消防资源优化配置的基础,本文在研究火灾风险影响因素与空间及地类关系的基础之上,将GIS技术引入城市火灾风险评价领域,构建了基于地理网格的地类火灾风险扩散模型。并以徐州市区为例,通过对各影响因素的空间地类阻隔扩散分析与叠加分析,得出任意分辨率网格的火灾风险等级,为未来城市的火灾预警与资源优化提供一种新的思路。     

长江中下游地区自然灾害社会脆弱性及其影响因素研究

面对日益严峻的气候变化形势,开展区域社会脆弱性的研究有利于更好地应对极端气候事件及相关灾害。为研究长江中下游地区社会脆弱性的空间分布及其社会经济文化驱动因素,参考So VI模型的指标体系选取36个指标对我国长江中下游的65个研究单元进行评价,采用因子分析法得到社会脆弱性的7个主要影响因子,据此得到最终的社会脆弱性指数及其分布。结果表明:长江中下游各地社会脆弱性差异明显,总体上呈现西高东低的态势。     

Flood prediction and assessment of vulnerability risk in the southern coasts of the Caspian Sea

Abstract

The southern part of the Caspian Sea shoreline in Iran with a length of 813 km has different topographic conditions. Owing to sea fluctuation, these zones have various dimensions in different times. During the last years, the Caspian Sea experienced enormous destructive rises. The historical information and tidal gauge measurements showed different ranges of sea rise from ?30 m to ?22 m from the mean sea level. On the other hand, the probable flooding zone is related to slope gradient of coasts. To help the determination of the probable flooding area owing to sea level rises, the coastal zones can be modelled using geographic information system (GIS) environment as vulnerability risk rates. These rates would be useful for making decisions in coastal management programs. This study examined different scenarios of sea rise to determine hazard-flooding rates in the coastal cities of the Mazandaran province and classified them based on vulnerability risk rates. The 1:2000 scale topographic maps of the coastal zones were prepared to extract topographic information and construct the coastal digital elevation model. With the presumption of half-metre sea rise scenarios, the digital elevation models classified eight scenarios from ?26 to ?22 m. The flooding areas in each scenario computed for 11 cities respectively. The vulnerability risk rate in each rise scenario was computed by dividing the flooded area of each scenario to city area. The results showed that in the first four scenarios, from ?26 to ?24 m, the Behshahr, Joibar, Neka and Babolsar cites would be more vulnerable than other cites. Moreover, for the second four scenarios from ?24 to ?22 m sea level rise scenario, only the coastal area of Chalous city would be vulnerable. It was also observed that the coastal region of Behshahr would be critical in total scenarios. Further studies would be necessary to complete this assessment by considering social-economic and land use information to estimate the exact hazardous and vulnerable zones.     

黑龙江省地理国情普查成果应用于市县经济建设的研究

地理国情普查是我国一项重要的测绘地理信息工程,其目的在于摸清国情家底,并将成果应用服务于政府、企业和公众。黑龙江第二测绘工程院与宁安市人民政府建立战略合作伙伴关系,以全省第一次地理国情普查成果数据为基础制作了测绘地理信息成果图集等数据,有效地提高了地理国情数据的应用,能够更加直观地了解特定区域内的交通、水系、植被、居民地等分布情况,为宁安市的经济建设和社会发展合理决策提供了新依据。     

融合地理探测器和地理加权回归的太原市建设用地变化因素研究

准确地识别城市化进程中建设用地的变化情况及其背后的驱动力,对城市后续的可持续发展具有重要意义。本文首先以2000—2020年遥感影像为基础,对太原市建设用地空间分布变化进行研究,然后结合地理探测器模型和地理加权回归模型,对研究区建设用地的空间分布影响驱动力因子进行研究,得到以下结论:除政策因素外,现有的城市建设用地空间分布变化还受到高程、交通、GDP、人口等因素的显著作用。太原市城市建设用地变化的布局不单是GDP变化、人口变化、海拔高度、公路网密度4个显著性因子均匀、独立、直接作用的结果,而是具有空间异质性的各因子两两交互作用后增效的产物。本文成果有望为城市建设用地驱动力研究提供一种新思路。     

基于GIS的智慧地名解决方案

地名是一个地方的文化索引,是社会发展的基础地理信息和社会公共信息,在国防建设、社会管理、公众服务等方面都发挥着重要作用.因此,在城市发展进程中,需要不断提升地名的管理水平以及地名的公共服务能力.本文基于GIS建设地名公共服务平台,通过建设城市地名"一张图"整合区划地名相关的数据,进而支撑对地名全生命周期的管理,并面向社会提供标准全面的地名信息服务,充分发挥地名在政务管理、公众服务中的价值.     

Visualizing spatiotemporal trajectories of mobile social media users using space–time cube

The implementation of social network applications on mobile platforms has significantly elevated the activity of mobile social networking. Mobile social networking offers a channel for recording an individual’s spatiotemporal behaviors when location-detecting capabilities of devices are enabled. It also facilitates the study of time geography on an individual level, which has previously suffered from a scarcity of georeferenced movement data. In this paper, we report on the use of georeferenced tweets to display and analyze the spatiotemporal patterns of daily user trajectories. For georeferenced tweets having both location information in longitude and latitude values and recorded creation time, we apply a space–time cube approach for visualization. Compared to the traditional methodologies for time geography studies such as the travel diary-based approach, the analytics using social media data present challenges broadly associated with those of Big Data, including the characteristics of high velocity, large volume, and heterogeneity. For this study, a batch processing system has been developed for extracting spatiotemporal information from each tweet and then creating trajectories of each individual mobile Twitter user. Using social media data in time geographic research has the benefits of study area flexibility, continuous observation and non-involvement with contributors. For example, during every 30-minute cycle, we collected tweets created by about 50,000 Twitter users living in a geographic region covering New York City to Washington, DC. Each tweet can indicate the exact location of its creator when the tweet was posted. Thus, the linked tweets show a Twitter users’ movement trajectory in space and time. This study explores using data intensive computing for processing Twitter data to generate spatiotemporal information that can recreate the space–time trajectories of their creators.     

"数字衡阳"市县一体化大数据与地理信息公共服务云平台建设的技术创新

“数字衡阳”市县一体化大数据与地理信息公共服务云平台建设项目,实现了市县地理信息一体化管理、共享和协同服务,制定了完整的市县一体化标准体系,创新了基础地理信息数据生产和管理机制,创建了基于标准体系的“一键成图”技术。大幅提升了地理信息共享应用的效益,降低了县级地理信息应用技术门槛,为全国其他地区数字城市建设提供了可借鉴、推广的经验。今后将进一步实现数据成果在各行各业的快速应用,产生更好的经济效益和社会效益。     

These lit areas are undeveloped: Delimiting China’s urban extents from thresholded nighttime light imagery

Nighttime light imagery is a powerful tool to study urbanization because it can provide a uniform metric, lit area, to delimit urban extents. However, lit area is much larger than actual urban area, so thresholds of digital number (DN) values are usually needed to reduce the lit area. The threshold varies greatly among different regions, but at present it is still not very clear what factors impact the changes of the threshold. In this study, urban extent by province for China is mapped using official statistical data and four intercalibrated and geometrically corrected nighttime light images between 2004 and 2010. Lit area in the imagery for most provinces is at least 94% greater than the official amount of urban area. Regression analyses show a significant correlation between optimal thresholds and GDP per capita, and larger thresholds more commonly indicate higher economic level. Size and environmental condition may explain a province’s threshold that is disproportionate to GDP. Findings indicate one threshold DN is not appropriate for multiple (adjacent) province urban extent mapping, and optimal thresholds for one year may be notably different than the next. Province-level derived thresholds are not appropriate for other geographic levels. Brightness of nighttime lights is an advantage over imagery that relies on daylight reflection, and decreases in brightness indicate faster growth in the horizontal direction than the vertical. A province’s optimal threshold does not always maintain an increase with population and economic growth. In the economically developed eastern provinces, urban population densities decreased (and this is seen in the brightness data), while urban population increased.     

GIS与Voronoi多边形在医疗服务设施地理可达性分析中的应用

地理可达性是研究评价各种服务设施布局及其服务域的重要指标之一,空间距离、交通便捷性、出行成本等是可达性测度的重要因子。由于医疗设施等公共设施通常以服务的公平性和覆盖性为目标,因此可定义居民点到最邻近医院的距离为地理可达性的测度。在此基础上,作者提出了基于GIS与Voronoi多边形的地理可达性计算方法。这一方法不仅将地理可达性分析中的空间点对之间的距离计算简化为空间查询,方便了GIS应用,而且计算的Voronoi多边形在本质上就是最邻近意义上医院的服务域,即服务域内各居民点到该医院的距离就是最邻近距离。此外结合人口分布等属性数据,还可深入分析各医院的服务承载力,本方法为医疗设施等公共服务设施的规划决策提供了重要的工具。     

Los Angeles as a digital place: The geographies of user‐generated content

Online representations of places are becoming pivotal in informing our understanding of urban life. Content production on online platforms is grounded in the geography of their users and their digital infrastructure. These constraints shape place representation, that is, the amount, quality, and type of digital information available in a geographic area. In this article we study the place representation of user‐generated content (UGC) in Los Angeles County, relating the spatial distribution of the data to its geo‐demographic context. Adopting a comparative and multi‐platform approach, this quantitative analysis investigates the spatial relationship between four diverse UGC datasets and their context at the census tract level (about 685,000 geo‐located tweets, 9,700 Wikipedia pages, 4 million OpenStreetMap objects, and 180,000 Foursquare venues). The context includes the ethnicity, age, income, education, and deprivation of residents, as well as public infrastructure. An exploratory spatial analysis and regression‐based models indicate that the four UGC platforms possess distinct geographies of place representation. To a moderate extent, the presence of Twitter, OpenStreetMap, and Foursquare data is influenced by population density, ethnicity, education, and income. However, each platform responds to different socio‐economic factors and clusters emerge in disparate hotspots. Unexpectedly, Twitter data tend to be located in denser, more deprived areas, and the geography of Wikipedia appears peculiar and harder to explain. These trends are compared with previous findings for the area of Greater London.     

Spatio-temporal Trends of Diarrheal Mortality of Children in Association with Hydrographic Regions of Brazil

In this paper, we analyze trends in average annual peak timing values (MPT) of pediatric mortality attributed to diarrheal disease in Brazil for the period 1979-1989 using a novel approach for environmental health risk studies, that is using natural boundaries instead of politically derived boundaries to define the unit of analysis (UOA). We evaluate the approach at varying spatial scales: (1) Country-wide based on observed Municipal level mortality data aggregated to Census Micro Regions (CMR); (2) Country-wide based on a grid of 20 Km2 raster cells generated by geostatistical modeling of MPT values; (3) Within eight officially designated Hydrographic Regions of Brazil based on results from the geostatistical models, and (4) Along longitudinal “vectors” of 1 km raster cells defining the stream network (hydrologic regime) within each Hydrographic Region.

At the country level, we found evidence of a trend west to east of increasing MPT over an annual cycle (May to April) using the CMR-level estimates. However, when we examined the model results at finer scales i.e., Hydrographic Regions, we discovered greater geographic heterogeneity in MPT across units. At the spatial scale of the stream network within the Hydrographic Regions, we observed consistent trends of increasing MPT from the source areas (upper watersheds) to downstream locations in some Hydrographic Regions, especially those composed of a single river basin.

Here, trends were no longer predominantly east to west as at the country level, but oriented in the direction of flow of the major river draining the basin. Our study results indicate substantial spatial variation in peak timing of pediatric mortality attributed to diarrheal disease in Brazil over our study period. This could have important ramifications in studies concerning known or suspected risk factors with significant temporal variation over an annual cycle. We found the geographic orientation of trend in mortality peak timing to be highly dependent on the geographic extent and derivation of the UOA. We demonstrate that a UOA based on natural boundaries, e.g., stream segments or watershed boundaries can result in more consistent and robust prediction of trends in mortality peak timing attributed to diarrhea.     

利用位置签到数据探索城市热点与商圈

众源地理数据（Crowd Sourcing Geographic Data）是指由大众采集并向大众开放共享的地理空间数据。众源位置签到数据作为众源地理数据的一种,客观真实的反映了大众日常生活行为,包含大量丰富的社会化属性信息。本文提出了一种基于众源位置签到数据的城市热点探测与商圈挖掘方法,首先对位置签到数据时空分布特性进行了研究,设计并提出了众源位置签到数据时空数据库模型;其次,提出了位置签到数据探索性空间分析方法,通过对众源位置签到数据的空间聚类分析,实现基于位置签到数据的商圈热点探测;最后,以武汉市为例,对街旁网截止2011年9月30日的众源位置签到数据进行了城市热点探测与商圈挖掘分析实验,结果表明,基于众源位置签到数据挖掘的武汉市商圈分布与城市规划商圈具有强相关性,可用于城市社会经济发展预测与区域经济规划。     

地理国情普查基本统计的探索与实践

泗阳县是江苏省开展地理国情普查的一个试点县。本文结合国家关于地理国情普查基本统计的技术规定与方法,考虑泗阳县地理环境、经济社会发展需求、政策因素、行业需求、已有基础条件等因素,在地理国情普查基本统计方面进行了一系列的探索和实践。最后从统计内容的扩充、可视化技术的应用、相关部门合作的加强、评价预测机制的构建等方面提出了一些意见和看法。