How Officers Create Guardianship: An Agent‐based Model of Policing

Crime is a complex phenomenon, emerging from the interactions of offenders, victims, and their environment, and in particular from the presence or absence of capable guardians. Researchers have historically struggled to understand how police officers create guardianship. This presents a challenge because, in order to understand how to advise the police, researchers must have an understanding of how the current system works. The work presents an agent‐based model that simulates the movement of police vehicles, using a record of real calls for service and real levels of police staffing in spatially explicit environments to emulate the demands on the police force. The GPS traces of the simulated officers are compared with real officer movement GPS data in order to assess the quality of the generated movement patterns. The model represents an improvement on existing standards of police simulation, and points the way toward more nuanced understandings of how police officers influence the criminological environment.     

Analyzing Animal Movement Characteristics From Location Data

When individuals of a species utilize an environment, they generate movement patterns at a variety of spatial and temporal scales. Field observations coupled with location technologies (e.g. GPS tags) enable the capture of detailed spatio‐temporal data regarding these movement patterns. These patterns contain information about species‐specific preferences regarding individual decision‐making, locational choices and the characteristics of the habitat in which the animal resides. Spatial Data Mining approaches can be used to extract repeated spatio‐temporal patterns and additional habitat preferences hidden within large spatially explicit movement datasets. We describe a method to determine the periodicity and directionality in movement exhibited by a migratory bird species. Results using a High Arctic‐nesting Svalbard Barnacle Goose movement data yielded undetected patterns that were secondarily corroborated with expert field knowledge. Individual revisits by the geese to specific locations in the breeding and wintering grounds of Svalbard, Norway and Solway, Scotland, occurred with a periodicity of 334 days . Further, the orientation of this movement was detected to be mostly north‐south. During long‐range migration the geese use the north‐south oriented Norwegian islands as “stepping stones”, Short‐range movement between mudbank roosts to feeding fields in Solway also retained a north‐south orientation.     

GPS历书计算与卫星星座预报仿真

利用Matlab软件解算GPS历书信息，对GPS卫星星座进行预报仿真。给出了计算仿真的整体流程和部分主要实现代码，最后通过实际接收卫星数据的计算，得出了预报仿真结果。此方法既能直观理解星座运动分布，也能满足工程实践中快速捕获卫星的需求。     

Volunteered Geographic Information: A Bicycling Enthusiast Perspective

Mapping technologies have made considerable strides in recent decades. Global positioning systems (GPS), remote sensing satellites, Web-based mapping services, and geographic information systems (GIS) have facilitated the collection, distribution, analysis, and ultimately interaction with geospatial information. In particular, portable GPS have altered how individuals participate in mapping. Individuals can use GPS to collect tracings of their personal interactions with the environment. These interactions can then be uploaded to one of many available Web-based mapping services. Once uploaded, the geospatial data can be mapped and shared among the broader community of users. Such volunteered geographic information (VGI) exemplifies the conceptualization of an individual collecting, mapping, and sharing personal geographic information. This paper focuses on challenges surrounding VGI. To help place these challenges in a broader context, specialized Web services and GPS technologies developed for the bicycling community will serve as examples of the current status and future prospects of VGI.     

利用GPS垂直位移反演云南省陆地水储量变化

地表质量的重分布会引起固体地球的弹性形变,GPS连续运行观测站能够精确测定地表负荷引起的地壳形变。本文通过模拟数据对利用云南省及其周边47个中国大陆构造环境监测网（陆态网）台站反演云南地区陆地水储量的可行性进行分析：以水文模型周年振幅为真值,计算47个台站点的负荷形变,同时加入随机误差构成模拟观测数据,最后采用模型反演陆地水储量变化;1000次的随机模拟试验表明利用当前GPS台站数据可有效地反演云南地区陆地水储量变化。基于上述结论,笔者反演了云南省2010—2014年陆地水储量变化,GPS反演结果表明：云南省陆地水变化呈现明显的地域分布特征,西南部高山地区的水储量周年变化高于东部平原地区;在时间尺度上,云南省大部分地区水储量在10月（夏季末）达到最大值,在4月（冬季末）达到最小值;云南省2010—2014年陆地水呈缓慢增长趋势,约为20 mm/a。通过GPS陆地水储量反演结果与GRACE、GLDAS以及TRMM数据综合对比分析,表明利用云南地区当前GPS台站可以作为独立观测量用于GRACE与GRACE Follow-on衔接期间的陆地水储量变化监测。     

A Methodology for Monitoring Vertical Dynamic Sub-Centimeter Displacments with GPS

This article describes a methodology to monitor dynamic vertical sub-centimeter displacement, of a GPS antenna. The dynamic movement of an antenna is determined by choosing the appropriate reference satellite for measurement differencing and by applying a FFT filter on the double-difference phase residuals. The validity of the method depends on the time variations of the GPS residuals and errors, such as, receiver noise, atmospheric contribution, multipath effects, and the antenna movement. This research is under development and results for simulated motion are presented here. ? 2002 Wiley Periodicals, Inc.     

'Situating' Simulation to Model Human Spatio-Temporal Interactions: An Example Using Crime Events

Many social phenomena have a spatio‐temporal dimension and involve dynamic decisions made by individuals. In the past, researchers have often turned to geographic information systems (GIS) to model these interactions. Although GIS provide a powerful tool for examining the spatial aspects of these interactions, they are unable to model the dynamic, individual‐level interactions across time and space. In an attempt to address these issues, some researchers have begun to use simulation models. But these models rely on artificial landscapes that do not take into account the environment in which humans move and interact. This research presents the methodology for ‘situating’ simulation through the use of a new modeling tool, Agent Analyst, which integrates agent‐based modeling (ABM) and GIS. Three versions of a model of street robbery are presented to illustrate the importance of using ‘real’ data to inform agent activity spaces and movement. The successful implementation of this model demonstrates that: (1) agents can move along existing street networks; (2) land use patterns can be used to realistically distribute agent's homes and activities across a city; and (3) the incidence and pattern of street robberies is significantly different when ‘real’ data are used.     

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records

Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.     

Simulating Complex Adaptive Geographic Systems: A Geographically Aware Intelligent Agent Approach

The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information, knowledge structures, and learning processes are needed for modeling intelligent agents situated within geographic systems. The representation of these agents requires the integration of agent-based models, machine learning, and GIS. Existing software packages for agent-based modeling, however, often provide insufficient support for this integration. The agent-based simulation package presented here is specifically designed to achieve such integration by assisting the development of agent-based models from the simulation framework. Object-oriented modeling techniques were used to implement this simulation package, which includes four modules: simulation, visualization, learning, and geoprocessing. In particular, the learning and geoprocessing modules facilitate the representation of adaptive behavior in agents within spatially explicit environments. The utility of the agent-based simulation package is illustrated using two simulation models: one of adaptive elk behavior and another of pedestrian movement. The successful design of the simulation models suggests that the modeling framework with the supporting software package is well suited to the resolution of complex adaptive geographic problems.     

Towards a Better Understanding of Dynamic Interaction Metrics for Wildlife: a Null Model Approach

The ability to measure dynamic interactions, such as attraction or avoidance, is crucial to understanding socio‐spatial behaviors related to territoriality and mating as well as for exploring resource use and the potential spread of infectious epizootic diseases. In spite of the importance of measuring dynamic interactions, it has not been a main research focus in movement pattern analysis. With very few exceptions (see Benhamou et al. 2014), no new metrics have been developed in the past 20 years to accommodate the fundamental shift in the type of animal movement data now being collected and there have been few comparison or otherwise critical studies of existing dynamic interaction metrics (but see Long et al. 2014; Miller 2012). This research borrows from the null model approach commonly used in community ecology to compare six currently used dynamic interaction metrics using data on five brown hyena dyads in Northern Botswana. There was disconcerting variation among the dynamic interaction results depending on which metric and which null model was used, and these results highlight the need for more extensive research on measuring and interpreting dynamic interactions in order to avoid making potentially misleading inferences about socio‐spatial behaviors.     

Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011

Detailed information on the spatiotemporal dynamic in surface water bodies is important for quantifying the effects of a drying climate, increased water abstraction and rapid urbanization on wetlands. The Swan Coastal Plain (SCP) with over 1500 wetlands is a global biodiversity hotspot located in the southwest of Western Australia, where more than 70% of the wetlands have been lost since European settlement. SCP is located in an area affected by recent climate change that also experiences rapid urban development and ground water abstraction. Landsat TM and ETM+ imagery from 1999 to 2011 has been used to automatically derive a spatially and temporally explicit time-series of surface water body extent on the SCP. A mapping method based on the Landsat data and a decision tree classification algorithm is described. Two generic classifiers were derived for the Landsat 5 and Landsat 7 data. Several landscape metrics were computed to summarize the intra and interannual patterns of surface water dynamic. Top of the atmosphere (TOA) reflectance of band 5 followed by TOA reflectance of bands 4 and 3 were the explanatory variables most important for mapping surface water bodies. Accuracy assessment yielded an overall classification accuracy of 96%, with 89% producer’s accuracy and 93% user’s accuracy of surface water bodies. The number, mean size, and total area of water bodies showed high seasonal variability with highest numbers in winter and lowest numbers in summer. The number of water bodies in winter increased until 2005 after which a decline can be noted. The lowest numbers occurred in 2010 which coincided with one of the years with the lowest rainfall in the area. Understanding the spatiotemporal dynamic of surface water bodies on the SCP constitutes the basis for understanding the effect of rainfall, water abstraction and urban development on water bodies in a spatially explicit way.     

GPS监测网数据处理方案研究

处理大尺度ＧＰＳ监测网多期复测成果的时期,数据处理方案是一个重要问题。作者在处理首都圈ＧＰＳ地形变监测网数据的过程中,经过长期探索和大量试算,提出了制定数据处理方案的基本原则：要采用一个自洽的地球参考框架和常数系统;要采用精度最高的同一种粗密星历和相应的地球自转参数;要采用最先进的同一种数据处理软件以及采用同一的参考基准和约束条件。由于地壳处于运动之中,大尺度ＧＰＳ监测网的参考基准应是动态基准。研     

Measuring Dynamic Interaction in Movement Data

The emergence of technologies capable of storing detailed records of object locations has presented scientists and researchers with a wealth of data on object movement. Yet analytical methods for investigating more advanced research questions from such detailed movement datasets remain limited in scope and sophistication. Recent advances in the study of movement data has focused on characterizing types of dynamic interactions, such as single‐file motion, while little progress has been made on quantifying the degree of such interactions. In this article, we introduce a new method for measuring dynamic interactions (termed DI) between pairs of moving objects. Simulated movement datasets are used to compare DI with an existing correlation statistic. Two applied examples, team sports and wildlife, are used to further demonstrate the value of the DI approach. The DI method is advantageous in that it measures interaction in both movement direction (termed azimuth) and displacement. Also, the DI approach can be applied at local, interval, episodal, and global levels of analysis. However the DI method is limited to situations where movements of two objects are recorded at simultaneous points in time. In conclusion, DI quantifies the level of dynamic interaction between two moving objects, allowing for more thorough investigation of processes affecting interactive moving objects.     

Geo-questionnaires in urban planning: recruitment methods,participant engagement,and data quality

ABSTRACT

Recent focus on sustainable urban development and livability has increased the demand for new data sourcing techniques to capture experiences and preferences of urban dwellers. At the same time, developments of geospatial technologies and social media have enabled new types of user-generated geographic information and spatially explicit online communication. As a result, new public participation GIS methods for engaging large groups of individuals have emerged. One such method is geo-questionnaire, an online questionnaire with mapping capabilities, which has been used to elicit geographic data in variety of topics and geographical contexts. This article presents two recent cases, in which geo-questionnaires have been used in Polish cities to obtain public input on quality of life and development preferences in local land use planning. The article evaluates participant recruitment methods focusing on sample representativeness, participant engagement, and data quality. Recruitment via social media was found to increase bias towards younger population. Paper questionnaires used along the online version provided for better representation of target population’s age structure, but did not reduce bias related to educational attainment. We discuss how these issues relate to data usability and generalizability in the context of digital divide, and suggest directions for future research.     

Using GIS in Areawide Pest Management: A Case Study in South Dakota

Infestations of corn rootworms (Coleoptera: Chrysomelidae) create economic and environmental concerns in the Corn Belt region of the United States. To supplement the population control tactics of areawide pest management programs, we believe that a better understanding of the spatial relationships between biotic and abiotic or physical factors at the landscape scale is needed. Our research used several geographical information systems (GIS) and spatial analytical techniques to examine relationships between corn rootworm metapopulation dynamics, soil texture, and elevation. Within GIS, several spatially explicit procedures were used that include an interpolation technique, spatial autocorrelation analysis, and contingency analysis. Corn rootworm metapopulation distributions were found to be aggregated and related to soil texture and elevation. We review techniques and discuss our preferences for using particular spatially explicit procedures. The information derived from the spatial analyses demonstrates how GIS can be used in areawide pest management to provide inputs for spatially explicit models to predict future pest populations and formulate more well‐informed pest management decisions. The techniques described in this paper could easily be extended to study the spatial dynamics between other pest populations in agricultural landscapes.     

GPS技术的新进展

ＧＰＳ技术虽然已经比较成熟，但近几年来一方面为了满足高精度实时动态定位的需要和对付美国的‘ＡＳ’及‘ＳＡ’政策，在相应的ＧＰＳ硬件和软件方面有不少新的进展；另一方面ＧＰＳ的优点正不断被人们认识，不断地开拓新的应用领域；第三方面的进展是建立了全球性的ＧＰＳ技术服务机构，它向全世界ＧＰＳ用户提供ＧＰＳ精密星历、星钟差、极移、追踪站的动态坐标和观测数据等资料。     

Plume Tracking with a Mobile Sensor Based on Incomplete and Imprecise Information

Mobile in‐situ sensor platforms such as Unmanned Aerial Vehicles can be used in environmental monitoring. In time‐critical monitoring scenarios as for example in emergency response, and in the exploration of highly dynamic phenomena, obtaining the relevant data with one or few mobile sensors is challenging. It requires an intelligent sampling strategy that integrates prior information and adapts to the dynamics of the observed phenomenon, based on the collected sensor data. Available information about the observed phenomenon may be incomplete or imprecise and therefore insufficient for quantitative modeling. We address this problem by reasoning about the plume movement and size on a qualitative level and present an algorithm for tracking a dynamic plume that integrates this qualitative information with the collected sensor data. We evaluate our algorithm using simulated data sets of three different moving and expanding gas plumes. By means of simulations we show that the qualitative methods can be used to infer new information about the properties of a moving plume and to adapt the sensor movement for tracking the plume. Both can be done with low computational effort, without absolute positioning capability of the sensor, and with less input information than required by quantitative approaches.     

Leveraging similarity analysis to understand variability in movement behavior

The increasingly large volume of trajectories of moving entities obtained through GPS and cellphone tracking, telemetry, and other location-aware technologies motivates researchers to understand the implicit patterns hidden in movement trajectories and understand how movement is influenced by the environmental context. Trajectory similarity serves as an important tool in computational movement analysis and as the foundation of revealing those patterns. However, there are various trajectory similarity measures, each of which has its own strengths and weaknesses. In this article, we present a hierarchical clustering framework that integrates five commonly used similarity measures, including Fréchet distance, dynamic time warping, Hausdorff distance, longest common subsequence, and normalized weighted edit distance, a special kind of edit distance for movement analysis. The framework aims at clustering similar patterns and identifying variability in movement. The optimal number of clusters are first obtained. Then, the clusters are characterized by environmental variables to explore the associations between variability in movement and the environmental conditions. We evaluate the proposed framework using 15 years of tracking data of turkey vultures, tracked at 1- to 3-h sampling intervals, during their fall and spring migration seasons. The results suggest that, at 5% significance level, turkey vultures select their movement paths intentionally and those selections appear to be related to certain environmental context variables, including thermal uplift, vegetation state (observed indirectly through Normalized Difference Vegetation Index), temperature, precipitation, tailwind, and crosswind. And interestingly, there exist preferential differences among individuals. Although the preference of the same turkey vulture is not strictly consistent over different years, each individual tends to preserve a more similar preference over different years, compared with the preferences of other turkey vultures.     

我国高精度GPS陆海垂直运动监测网的数据处理

为了分离海平面与验潮站所在陆地的垂直运动并获得海平面变化的绝对信息 ,对由沿海 5个验潮站组成的高精度 GPS陆海垂直运动监测网的 1998年一期观测数据 ,采用 GAMIT和 GL OBK软件进行了处理 ,并顾及了影响高程因素中由于方位不对称引起的大气延迟及改进的 Niell模型。最终 GPS监测网达到了毫米级的高程精度。     

A Chain-Code-Based Map Matching Algorithm for Wheelchair Navigation

Accurate vehicle tracking is essential for navigation systems to function correctly. Unfortunately, GPS data is still plagued with errors that frequently produce inaccurate trajectories. Research in map matching algorithms focuses on how to efficiently match GPS tracking data to the underlying road network. This article presents an innovative map matching algorithm that considers the trajectory of the data rather than merely the current position as in the typical map matching case. Instead of computing the precise angle which is traditionally used, a discrete eight-direction chain code, to represent a trend of movement, is used. Coupled with distance information, map matching decisions are made by comparing the differences between trajectories representing the road segments and GPS tracking data chain-codes. Moreover, to contrast the performance of the chain-code algorithm, two evaluation strategies, linear and non-linear, are analyzed. The presented chain-code map matching algorithm was evaluated for wheelchair navigation using university campus sidewalk data. The evaluation results indicate that the algorithm is efficient in terms of accuracy and computational time.