Leveraging parallel spatio-temporal computing for crime analysis in large datasets: analyzing trends in near-repeat phenomenon of crime in cities

ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.     

The application of GIS for flood defence in the Anglian Region: developing for the future

The spatio‐temporal relationship between unusual sightings of dead birds and human West Nile virus infections has been observed in many studies and has been proposed as an indicator of an intense amplification cycle between birds and mosquitoes. However, to date, no single study has provided quantitative evidence that the amplification cycle occurs at the local level and that it operates within certain temporal parameters. Here, we use a novel geostatistical and spatial analytic methodology and present the first evidence that the localized unusual space–time correspondence of dead birds models the amplification cycle and that this cycle peaks 15–16 days prior to human onset of West Nile virus infections. During the process of establishing this relationship, we extend the traditional Knox space–time interaction measure to overcome pair‐dependency limitations and use a novel implementation of the kappa non‐chance agreement measure to identify the temporal characteristics of the association of bird deaths to human West Nile infections.     

Temporal stability of model parameters in crime rate analysis: An empirical examination

Two common practices in modeling of crime when crime data is available for multiple years are using single-year crime data corresponding to census data and taking the average of crime rate (or count) over multiple years. Current theoretical and empirical literature provides little, if any, rationale in support of either practice. Averaging multiple years is purported to reduce heterogeneity and minimize the measurement error in the year-to-year emergence of crime. However, it is unclear how useful the analysis of averaged and smoothed data is for revealing the relationship between crimes and socio-demographic and economic characteristics of every single year. In order to more clearly understand these two approaches, this paper applies a seemingly unrelated regression model to assess the temporal stability of model parameters. The model accounts for spatial autocorrelation among crime rates and social disorganization variables at the block group level.     

Automated geographic context analysis for volunteered information

Several studies show the impacts of (geo)social media and Volunteered Geographic Information (VGI) during crisis events, and have found intrinsic value for rescue teams, relief workers and humanitarian assistance coordinators, as well as the affected population. The main challenge is how emergency management and the public can capitalize on the abundance of this new source of information by reducing the volume to credible and relevant content.In this paper, we present the GeoCONAVI (Geographic CONtext Analysis for Volunteered Information) approach and a prototype system, designed to retrieve, process, analyze and evaluate social media content on forest fires, producing relevant, credible and actionable VGI usable for crisis events. The novelty of the approach lies in the enrichment of the content with additional geographic context information, and use of spatio-temporal clustering to support scoring and validation. Thus, the system is focusing on integrating authoritative data sources with VGI. Evaluation in case studies shows that the prototype system can handle large amounts of data with common-off-the-shelf hardware, produces valuable results, and is adaptable to other types of crisis events.     

Street profile analysis: A new method for mapping crime on major roadways

Street profile analysis is a new method for analyzing temporal and spatial crime patterns along major roadways in metropolitan areas. This crime mapping technique allows for the identification of crime patterns along these street segments. These are linear spaces where aggregate crime patterns merge with crime attractors/generators and human movement to demonstrate how directionality is embedded in city infrastructures. Visually presenting the interplay between these criminological concepts and land use can improve police crime management strategies. This research presents how this crime mapping technique can be applied to a major roadway in Burnaby, Canada. This technique is contrasted with other crime mapping methods to demonstrate the utility of this approach when analyzing the rate and velocity of crime patterns overtime and in space.     

Spatio-temporal features and the dynamic mechanism of shopping center expansion in Shanghai

Since the first modern shopping centre was built in the United States in the 1920s, shopping centres have gradually become representative patterns of economic growth and consumerism in the United States, and these patterns are now trending globally. Shopping centres have demonstrated tremendous development potential since their initial entry into China in the 1990s. Shanghai is the most economically prosperous city in China, and the development and evolution of its shopping centres reflect the trend in China's commercial real estate development. Therefore, based on the central-place and agglomeration economy theory, this paper quantitatively measures and analyses the spatial gravity, extending direction, agglomeration characteristics and hierarchical structure of Shanghai's shopping centres using GIS (Geographic Information Systems) and spatial analysis. Moreover, this paper analyses the dynamic mechanism of urban development and its patterns of centripetal and centrifugal movement. The results demonstrate the following. (1) The spatial gravity points are located in the districts of Huangpu, Luwan and Xuhui in the city centre and within the inner ring. In addition, there is a trend to be gradually near the middle ring, exhibiting an obvious tendency from the northeast to the southwest. (2) Shopping centres in Shanghai exhibit a clustered distribution in the centres of urban areas, which form numerous business districts that extend in the same direction. (3) The hot spot analysis is a very effective method for identifying the hierarchy of business circles. (4) Planning by the government is the most important external impetus, and commercial agglomeration is the internal force determining the spatial expansion of shopping centres. Additionally, urban transportation patterns have an obvious influence on the spatial morphology of shopping centres. (5) Over the last two decades, the spatial development of Shanghai's shopping centres has reached a balance between the centripetal and centrifugal forces. In other words, we have not observed a tendency towards suburbanization, which indicates that Shanghai's shopping centres are still in the early stages of development. Therefore, future shopping centres may be primarily located in the stretch or peripheral zones of the city.     

Spatial conjunctive analysis of (crime) case configurations: Using Monte Carlo methods for significance testing

While research has repeatedly demonstrated how spatial distributions of crime can be shaped by the presence of facilities such as bars and public transport hubs, the joint influence of different facility types has rarely been explored. Spatial conjunctive analysis of case configurations (also known as qualitative comparative analysis) offers a means to identify the combinations of facility types that are most commonly found around crime events, and has been used in a small number of studies focusing on street robbery. This study extends this limited evidence base by implementing a significance test based on the Monte Carlo method using street robbery data for Austin, Texas. The results show that some of the top-ranking facility type combinations had observed frequencies that were not significantly greater than chance expectations. The accurate identification of the highest-risk environments has important implications for crime prevention.     

Spatio-temporal analysis of territorial changes from a multi-scale perspective

The full integration of time dimensions in GIS still represents a research challenge. A number of systems provide ways to visualise harmonised timestamped geographical data onto maps, with interpolated curves representing how these data have changed over time. However, these systems frequently mask the concerns linked to changes in territorial organisations and the harmonisation of data. In fact, the development of a territory should be considered in connection with its neighbourhood, governance and genealogy relationships. This article focuses on the difficulties linked with the ‘change of support problem’, which can arise when conducting spatio-temporal analysis of data. First, we present a data model handling the changing relationships between territories. Then, we illustrate how this model can be instantiated using examples that have taken place in Europe. We show how the model can address questions such as that of change blindness. Finally, we explain how hierarchical and genealogical relationships can be used inside an interactive cartographic tool for spatio-temporal analysis. It provides various views of the same phenomena at multiple scales, through an approach that takes into account the changes in territorial organisation.     

环印度洋区域国家地缘经济格局分析

环印度洋区域不仅关乎中国贸易与能源安全,同时也涵盖“一带一路”倡议合作的部分区域.为便于中国更好地开展与环印度洋区域国家之间的贸易合作,需要定量考察环印度洋区域的地缘经济格局,掌握域内外大国在该区域的地缘经济竞争情况.首先基于有序聚类方法将1992-2017年环印度洋区域国家的商品贸易数据划分为4个阶段,然后探究环印度...     

STLP-GSM: a method to predict future locations of individuals based on geotagged social media data

ABSTRACT

An increasing number of social media users are becoming used to disseminate activities through geotagged posts. The massive available geotagged posts enable collections of users’ footprints over time and offer effective opportunities for mobility prediction. Using geotagged posts for spatio-temporal prediction of future location, however, is challenging. Previous studies either focus on next-place prediction or rely on dense data sources such as GPS data. Introduced in this article is a novel method for future location prediction of individuals based on geotagged social media data. This method employs the hierarchical density-based clustering algorithm with adaptive parameter selection to identify the regions frequently visited by a social media user. A multi-feature weighted Bayesian model is then developed to forecast users’ spatio-temporal locations by combining multiple factors affecting human mobility patterns. Further, an updating strategy is designed to efficiently adjust, over time, the proposed model to the dynamics in users’ mobility patterns. Based on two real-life datasets, the proposed approach outperforms a state-of-the-art method in prediction accuracy by up to 5.34% and 3.30%. Tests show prediction reliability is high with quality predictions, but low in the identification of erroneous locations.     

Image analysis as a method to quantify sediment components

Varved lake sediments, with their annual to seasonal resolution, have a high potential for inferring past environmental and climatic conditions. To fully utilize the information present in varved records, high-resolution analyses, which often are time-consuming and difficult to perform, are desirable. The investigation reported here aims at (i) developing image analysis as a method for estimating annual accumulation rates of sediment components such as minerogenic matter, organic matter and biogenic silica, and (ii) assessing the relative importance of these components for changes in varve thickness. Image analysis was used to digitize the grey-scale variations and to measure the varve thickness of 540 varves (476-1015 AD) from Lake Kassjön in northern Sweden. From the 35 cm long digitized sediment sequence, 108 consecutive five-year samples were cut out quantitatively, and relationships between grey-scale variations and sediment dry mass and individual sediment components were assessed. There is a strong correlation between corrected grey-scale (i.e. the product of grey-scale and varve thickness) and the dry mass accumulation rate (r = 0.90, p < 0.001). With a stepwise multiple regression a significant model (R² = 0.81) between corrected grey-scale and the accumulation rates of minerogenic matter (r = 0.90, p < 0.001) and biogenic silica (r 0.26, p < 0.012) was obtained. Considering the minor contribution and weak significance of biogenic silica, image analysis can be used as a fast and non-destructive method to infer past annual accumulation rates of dry mass and minerogenic matter in Kassibn. The model of the relationship between changes in varve thickness, and water content and accumulation rates of sediment components has little predictive power (R² = 0.45). The result shows that the varve thickness in Kassjön, at least during the period 476-1015 AD, is not determined by a single sediment component but partly depends on interactions between the major sediment components.     

北京市长安街沿线的扒窃案件高发区分析及防控对策

本文利用空间分析方法,对北京市长安街沿线的扒窃类案件的空间分布特征进行了研究。首先分析了长安街沿线的犯罪分布状况,发现该长安街沿线共存在3个异常明显的犯罪高发区域,分别对应于西单商业圈(A)、建国门路段(B)和大望路—四惠路段(C),通过将长安街沿线的常住人口与兴趣点(Point of Interest, POI)分布进行比较,发现案件与POI密度较高的区域存在较高的相关性。随后,利用核密度估计方法和时空热点矩阵方法分析了3个异常明显的案件高发区域内的犯罪活动时空分布模式,结果表明：高发区域A的犯罪高发时段为上午10时至下午18时,其中峰值出现在正午12时,犯罪活动主要集中在区域内的一些大型购物场所内;高发区域B和C的犯罪高发时间均为上午6时和下午18时前后,与早晚交通高峰时间比较一致,犯罪活动主要集中在区域内比较重要的公共交通站点附近。最后,根据长安街沿线案件高发区域内犯罪活动的时空规律性特征,提出了犯罪防控措施与建议。     

Factor analysis to detect the causes of land degradation in Maduo County, northeastern Qinghai-Tibet Plateau

The area of desertified land has increased by 27.3% from 1987 to 2000 in Maduo County,northeastern Qinghai-Tibet Plateau.Driving forces of land degradation has been extensively studied in the region.Using Factor Analysis (FA),we evaluate contribution of human activity and natural environmental change to land degradation.Four common factors were extracted in this study.The result shows that climate related other than human-related factors,are the major inducing factors of land degradation in Maduo County.Climate change and consequent change of permafrost account for 70% to the land degradation.Increasing evaporation and declining precipitation in the beginning of the growing season hamper seedling establishment.Decreasing frozen days and rising active layer lower bound make surface soil loose and less soil moisture available for plant.     

Spatio-temporal analysis of the geographical centroids for three major crops in China from 1949 to 2014

Spatial distribution changes in major crops can reveal important information about cropping systems. Here, a new centroid method that applies physics and mathematics to spatial pattern analysis in agriculture is proposed to quantitatively describe the historical centroids of rice, maize and wheat in China from 1949 to 2014. The geographical centroids of the rice area moved 413.39 km in a 34.32° northeasterly (latitude 3.08°N, longitude 2.10°E) direction at a speed of 6.36 km/year from central Hunan province to Hubei province, while the geographical centroids of rice production moved 509.26 km in the direction of 45.44° northeasterly (latitude 3.22°N, longitude 3.27°E) at a speed of 7.83 km/year from central Hunan province to Henan province. The geographical centroids of the maize area and production moved 307.15 km in the direction of 34.33° northeasterly (latitude 2.29°N, longitude 1.56°E) and 308.16 km in the direction of 30.79° northeasterly (latitude 2.39°N, longitude 1.42°E), respectively. However, the geographical centroids of the wheat area and production were randomly distributed along the border of Shanxi and Henan provinces. We divided the wheat into spring wheat and winter wheat and found that the geographical centroids of the spring wheat area and production were distributed within Inner Mongolia, while the geographical centroids of winter wheat were distributed in Shanxi and Henan provinces. We found that the hotspots of crop cultivation area and production do not always change concordantly at a larger, regional scale, suggesting that the changing amplitude and rate of each crops’ yield differ between different regions in China. Thus, relevant adaptation measures should be taken at a regional level to prevent production damage in those with increasing area but decreasing production.     

Metropolitan land-use patterns by economic function: a spatial analysis of firm headquarters and branch office locations in Australian cities

This paper develops a comparative means by which to understand metropolitan spatial structure through the dynamics of economic activities. Clustering and suburbanization have been key processes within the contemporary urban landscape, but few scholarly accounts have systematically merged the two to explain the geographies of economic activity. Using firm location as a variable to discern sector- and industry-based locational requirements, we explore land-use and economic activity in Australia’s five largest metropolitan areas. Drawing upon the respective headquarters and branch office locations of a set of publically traded firms, we seek to establish general spatial patterns across Australian cities using two proxy measures for clustering and suburbanization, being well-established drivers of firm locational choice. Despite the complexity that post-industrial and suburbanizing processes add to metropolitan land-use patterns, we contend that certain patterns exist that can be generalized from one context to another across urban space, and that certain emerging trends such as the development of CBD-fringe precincts merit greater attention.     

三江源地区1961-2010年降水时空变化(英文)

Based on a monthly dataset of precipitation time series (1961-2010) from 12 meteorological stations across the Three-River Headwater Region (THRHR) of Qinghai Province, China, the spatio-temporal variation and abrupt change analysis of precipitation were examined by using moving average, linear regression, spline interpolation, the Mann-Kendall test and so on. Major conclusions were as follows. (1) The long-term annual and seasonal precipitation in the study area indicated an increasing trend with some oscillations during 1961-2010; however, the summer precipitation in the Lantsang (Lancang) River Headwater Region (LARHR), and the autumn precipitation in the Yangtze River Headwater Region (YERHR) of the THRHR decreased in the same period. (2) The amount of annual precipitation in the THRHR and its three sub-headwater regions was greater in the 1980s and 2000s. The springs were fairly wet after the 1970s, while the summers were relatively wet in the 1960s, 1980s and 2000s. In addition, the amount of precipitation in the autumn was greater in the 1970s and 1980s, but it was relatively less for the winter precipitation, except in the 1990s. (3) The normal values of spring, summer, winter and annual precipitation in the THRHR and its three sub-headwater regions all increased, but the normal value of summer precipitation in the LARHR had a negative trend and the normal value of winter precipitation declined in general. (4) The spring and winter precipitation increased in most of the THRHR. The summer, autumn and annual precipitation increased mainly in the marginal area of the west and north and decreased in the regions of Yushu, Zaduo, Jiuzhi and Banma. (5) The spring and winter precipitation in the THRHR and its three sub-headwater regions showed an abrupt change, except for the spring precipitation in the YARHR. The abrupt changes of spring precipitation were mainly in the late 1980s and early 1990s, while the abrupt changes of winter precipitation were primary in the mid-to late 1970s. This research would be helpful for further understanding the trends and periodicity of precipitation and for watershed-based water resource management in the THRHR.     

近几十年我国极端气温变化特征分区方法探讨

采用聚类统计检验分析和旋转主分量分析相结合确定中心站的方法,利用我国多年极端气温资料,对我国最高和最低气温年际变化型态进行区划。结果表明,这两种方法结合可以互相补充,使分区结果更具客观性。中国极端高温和极端低温年际变化分别可划为12和11个不同类型的区域,分别计算了各区域第一主成分的方差贡献率以及各区域之间的两两相关系数,检验证明分区是合理的。