An event-based conceptual model for context-aware movement analysis

Current tracking technologies enable collection of data, describing movements of various kinds of objects, including people, animals, icebergs, vehicles, containers with goods and so on. Analysis of movement data is now a hot research topic. However, most of the suggested analysis methods deal with movement data alone. Little has been done to support the analysis of movement in its spatio-temporal context, which includes various spatial and temporal objects as well as diverse properties associated with spatial locations and time moments. Comprehensive analysis of movement requires detection and analysis of relations that occur between moving objects and elements of the context in the process of the movement. We suggest a conceptual model in which movement is considered as a combination of spatial events of diverse types and extents in space and time. Spatial and temporal relations occur between movement events and elements of the spatial and temporal contexts. The model gives a ground to a generic approach based on extraction of interesting events from trajectories and treating the events as independent objects. By means of a prototype implementation, we tested the approach on complex real data about movement of wild animals. The testing showed the validity of the approach.     

Towards an integrated science of movement: converging research on animal movement ecology and human mobility science

There is long-standing scientific interest in understanding purposeful movement by animals and humans. Traditionally, collecting data on individual moving entities was difficult and time-consuming, limiting scientific progress. The growth of location-aware and other geospatial technologies for capturing, managing and analyzing moving objects data are shattering these limitations, leading to revolutions in animal movement ecology and human mobility science. Despite parallel transitions towards massive individual-level data collected automatically via sensors, there is little scientific cross-fertilization across the animal and human divide. There are potential synergies from converging these separate domains towards an integrated science of movement. This paper discusses the data-driven revolutions in the animal movement ecology and human mobility science, their contrasting worldviews and, as examples of complementarity, transdisciplinary questions that span both fields. We also identify research challenges that should be met to develop an integrated science of movement trajectories.     

Unusual behavior detection and object ranking from movement trajectories in target regions

Unusual behavior detection has been of interest in video analysis, transportation systems, movement trajectories, and so on. In movement trajectories, only a few works identify unusual behavior of objects around pre-defined points of interest (POI), such as surveillance cameras, commercial buildings, etc., that may be interesting for several application domains, mainly for security. In this article, we define new types of unusual behaviors of moving objects in relation to POI, including surround, escape, and return. Based on these types of unusual behavior, we (i) present an algorithm to compute these behaviors, (ii) define a set of functions to weight the degree of unusual behavior of every moving object in the database, and (iii) rank the moving objects according to the degree of unusual behavior in relation to a set of POIs. We evaluate the proposed method with real trajectory data and show that the closest work does not detect the proposed behaviors and ranks objects considering only one type of unusual movement.     

Visual analytics of delays and interaction in movement data

The analysis of interaction between movement trajectories is of interest for various domains when movement of multiple objects is concerned. Interaction often includes a delayed response, making it difficult to detect interaction with current methods that compare movement at specific time intervals. We propose analyses and visualizations, on a local and global scale, of delayed movement responses, where an action is followed by a reaction over time, on trajectories recorded simultaneously. We developed a novel approach to compute the global delay in subquadratic time using a fast Fourier transform (FFT). Central to our local analysis of delays is the computation of a matching between the trajectories in a so-called delay space. It encodes the similarities between all pairs of points of the trajectories. In the visualization, the edges of the matching are bundled into patches, such that shape and color of a patch help to encode changes in an interaction pattern. To evaluate our approach experimentally, we have implemented it as a prototype visual analytics tool and have applied the tool on three bidimensional data sets. For this we used various measures to compute the delay space, including the directional distance, a new similarity measure, which captures more complex interactions by combining directional and spatial characteristics. We compare matchings of various methods computing similarity between trajectories. We also compare various procedures to compute the matching in the delay space, specifically the Fréchet distance, dynamic time warping (DTW), and edit distance (ED). Finally, we demonstrate how to validate the consistency of pairwise matchings by computing matchings between more than two trajectories.     

Modeling uncertainty of moving objects on road networks via space–time prisms

Moving objects produce trajectories, which are typically observed in a finite sample of time‐stamped locations. Between sample points, we are uncertain about the moving objects's location. When we assume extra information about an object, for instance, a (possibly location‐dependent) speed limit, we can use space–time prisms to model the uncertainty of an object's location.

Until now, space–time prisms have been studied for unconstrained movement in the 2D plane. In this paper, we study space–time prisms for objects that are constrained to travel on a road network. Movement on a road network can be viewed as essentially one‐dimensional. We describe the geometry of a space–time prism on a road network and give an algorithm to compute and visualize space–time prisms. For experiments and illustration, we have implemented this algorithm in MATHEMATICA.

Furthermore, we study the alibi query, which asks whether two moving objects could have possibly met or not. This comes down to deciding if the chains of space–time prisms produced by these moving objects intersect. We give an efficient algorithm to answer the alibi query for moving objects on a road network. This algorithm also determines where and when two moving objects may have met.     

A data model for moving regions of fixed shape in databases

Moving object databases are designed to store and process spatial and temporal object data. An especially useful moving object type is a moving region, which consists of one or more moving polygons suitable for modeling the spread of forest fires, the movement of clouds, spread of diseases and many other real-world phenomena. Previous implementations usually allow a changing shape of the region during the movement; however, the necessary restrictions on this model result in an inaccurate interpolation of rotating objects. In this paper, we present an alternative approach for moving and rotating regions of fixed shape, called Fixed Moving Regions, which provide a significantly better model for a wide range of applications like modeling the movement of oil tankers, icebergs and other rigid structures. Furthermore, we describe and implement several useful operations on this new object type to enable a database system to solve many real-world problems, as for example collision tests, projections and intersections, much more accurate than with other models. Based on this research, we also implemented a library for easy integration into moving objects database systems, as for example the DBMS Secondo (1) (2) developed at the FernUniversität in Hagen.     

From A to B,randomly: a point-to-point random trajectory generator for animal movement

For applications in animal movement, we propose a random trajectory generator (RTG) algorithm that combines the concepts of random walks, space-time prisms, and the Brownian bridge movement model and is capable of efficiently generating random trajectories between a given origin and a destination point, with the least directional bias possible. Since we provide both a planar and a spherical version of the algorithm, it is suitable for simulating trajectories ranging from the local scale up to the (inter-)continental scale, as exemplified by the movement of migrating birds. The algorithm accounts for physical limitations, including maximum speed and maximum movement time, and provides the user with either single or multiple trajectories as a result. Single trajectories generated by the RTG algorithm can be used as a null model to test hypotheses about movement stimuli, while the multiple trajectories can be used to create a probability density surface akin to Brownian bridges.     

Incorporating behavior into animal movement modeling: a constrained agent-based model for estimating visit probabilities in space-time prisms

ABSTRACT

Animal movement is a dynamic spatio-temporal process. While trajectory data reflect the instantaneous animal position in space and time, other factors influence movement decisions between these observed positions. While some methods incorporate environmental (habitat) context into their understanding of the animal movement process, it is often captured in terms of simple parameters or weights influencing model results; primary behavioral data are not used directly to inform these models. Here, a new space-time constrained agent-based model is introduced, capable of producing ordered, behaviorally informed animal potential paths between observed space-time anchors. Potential paths generated by this approach incorporate both observed animal behavior and classical space-time constraints, and are used to construct associated visit probability distributions. Additionally, the notion of a behavioral space-time path is introduced, a variant of the space-time path based on the results of behaviorally aware animal movement simulation. The results of this approach demonstrate a means to better understand the varied movement opportunities within space-time prisms from an animal behavior perspective. From a spatial ecology perspective, not only is the environmental context considered, but the animal’s choice of transition and movement magnitude between contexts is modeled. This approach provides insight into the complex sequence of behaviorally informed actions driving animal movement decision-making.     

人口移动与区域经济格局变动

人口移动是我国近几年发生的重要社会经济现象之一,其机制是东部地区人多地少的推力与西部地区产业结构性空缺的吸力,以及国家对后者特定的工资与粮食政策。它对地域分工格局的变动产生着重大影响。     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.     

多源空间数据无缝集成研究

随着地理信息系统的社会化发展 ,空间数据共享成为一种必然要求 ,然而要真正实现空间数据共享 ,多格式空间数据集成是一个亟待解决的问题。多源空间数据无缝集成( SIMS)技术实现了一种特殊的数据访问机制 ,不仅提供了直接存取多种数据格式的能力 ,而且使 GIS软件具有跨数据源复合分析功能 ,是实现空间数据共享的有效的技术基础。本文阐述了 SIMS技术体系结构 ,并探讨了 SIMS技术在 GIS软件开发中的应用。     

Plain move predicate and its consistency concerning the moving agents in a network

Advances in GIS and databases for dealing with spatiotemporal frameworks are leading to efficient querying, analyzing, and reasoning about moving objects/agents. However, contemporary frameworks on spatiotemporal logics are usually limited to qualitative approaches, such as the numerous studies on spatiotemporal databases that focus on observations, ignoring the intended movements of the agents. Moving object databases, on the other hand, can handle queries about the location, velocity, and time by assuming some agents to be targets. However, reasoning about the plan of moving agents, especially on the network and the achievability of such a plan, still remains a challenge. Studies on vehicle routing are often about the centralized planning of moving agents from scratch and do not deal with intended plans. Based on a plain move predicate, this paper presents a generic framework that can be used for representing and reasoning about plans of moving agents. Concepts from motion, network structure, graph theory, predicate logic, and constraint satisfaction are used to create the framework. We have also provided efficient algorithms for checking the consistency of the movement and extracting compatible plans along with some discussions on computational analysis, logical deduction, and flexibility. Finally, we have demonstrated the application of the methodology by developing NETwork-based Move Atoms Planning System (NETMAPS). The experiments show how NETMAPS can overcome an inconsistent movement plan and deliver advantageous suggestions to an executive agent.     

南通县农村产业结构变化、劳动力转移和城镇化发展

本文以南通县为典型，研究了近年桌我国经济较发达地区农村产业结构变化趋势、农村产业结构类型的形成、劳动力的产业转移和空间转移以及县域城镇化发展，分析了当前存在的问题并提出相应的看法。     

A context-sensitive correlated random walk: a new simulation model for movement

Computational Movement Analysis focuses on the characterization of the trajectory of individuals across space and time. Various analytic techniques, including but not limited to random walks, Brownian motion models, and step selection functions have been used for modeling movement. These fall under the rubric of signal models which are divided into deterministic and stochastic models. The difficulty of applying these models to the movement of dynamic objects (e.g. animals, humans, vehicles) is that the spatiotemporal signal produced by their trajectories a complex composite that is influenced by the Geography through which they move (i.e. the network or the physiography of the terrain), their behavioral state (i.e. hungry, going to work, shopping, tourism, etc.), and their interactions with other individuals. This signal reflects multiple scales of behavior from the local choices to the global objectives that drive movement. In this research, we propose a stochastic simulation model that incorporates contextual factors (i.e. environmental conditions) that affect local choices along its movement trajectory. We show how actual global positioning systems observations can be used to parameterize movement and validate movement models and argue that incorporating context is essential in modeling movement.     

西伯利亚板块旋转漂移运动刍议

西伯利亚板块是世界上古老的地质构造单元之一。根据板块构造理论，该板块当今的地表形态和地理位置，是其经过不断迁移，与其它板块不断发生碰撞的结果。本文试从展现板块的水平运动特点出发，着重揭示西伯利亚板块在各地质时期的运动状态，从而阐述该板块自寒武纪以来的旋转漂移的全过程。     

Detecting outliers in irregularly distributed spatial data sets by locally adaptive and robust statistical analysis and GIS

In this paper, we propose a new method for detecting outliers in an irregularly distributed spatial data set. Our method has two desirable properties. First, it is functionally effective due to the introduction of sensitive outlier indices and locally adaptive and robust statistical criteria. Second, it is computationally efficient because of the use of super-block based spatial data sorting and searching scheme. Our method has been implemented using the C programming language and integrated with the Arc/Info GIS system. The integration leads to a powerful exploratory data analysis tool for checking and analysing anomalous values in a GIS environment. Local outliers can be automatically labeled with our method, subject to some user-defined parameters. Outliers represent anomalous or suspicious values in a statistical sense, which may not necessarily be erroneous values. Instead of being simply discarded, statistical outliers should be investigated further using prior qualitative knowledge or in association with other GIS data layers.     

Providing spatial statistical data analysis functionality for the GIS user: the SAGE project

Geographic representation has become more complex through time as researchers have added new concepts, leading to apparently endless proliferation and creating a need for simplification. We show that many of these concepts can be derived from a single foundation that we term the atomic form of geographic information. The familiar concepts of continuous fields and discrete objects can be derived under suitable rules applied to the properties and values of the atomic form. Fields and objects are further integrated through the concept of phase space, and in the form of field objects. A second atomic concept is introduced, termed the geo‐dipole, and shown to provide a foundation for object fields, metamaps, and the association classes of object‐oriented data modelling. Geographic dynamics are synthesized in a three‐dimensional space defined by static or dynamic object shape, the possibility of movement, and the possibility of dynamic internal structure. The atomic form also provides a tentative argument that discrete objects and continuous fields are the only possible bases for geographic representation.     

Ants in Labyrinths: Lessons for Critical Landscapes

Percolation theory provides a starting point for models for the movement of organisms in fragmented landscapes. We simulated six general rules for movement on three general landscape patterns with different degrees of habitat fragmentation. Fragmentation pattern affects migration success. Organisms moving within habitat patches are restricted by fragmentation, but the response is less abrupt as one moves from random to hierarchical to fractal landscapes, respectively. Success for organisms moving along edges is more strongly differentiated by landscape pattern. Success and speed are usually directly related, but indirect relations may indicate rare but efficient pathways or cul-de-sacs. We propose that general rules can be applied to the identification of landscapes near critical levels of fragmentation that will respond sensitively to increases in fragmentation or efforts at restoration.     

Mid-Jurassic through mid-Cretaceous extension in the Central Graben of the North Sea - part 2: estimates from faulting observed on a seismic reflection line

Abstract We present an interpretation of the structure and faulting of an industry multichannel line across the Central North Sea Graben. We observe substantial faulting between the mid-Jurassic and mid-Cretaceous and on the base Zechstein (salt) reflector. To estimate the extension from these faults we consider movement along both planar and curved faults. We demonstrate that summing the heave (the horizontal displacement) overestimates the time measure of elongation for planar, ‘domino-type’, faulting. However, for high-angle normal faults and up to 70% extension (β= 1.7) the heave only overestimates the extension by 13%. In the absence of other information, summing the heave provides a useful estimate of extension in the case of domino-type faulting. For curved ‘listric’ faults the heave is only a true measure of the elongation if the antithetic faulting which removes the voids is vertical. Antithetic movement along inclined shear planes implies significantly more extension. We used the two models; of faulting to introduce progressively greater amounts of internal deformation in the crustal rocks and sediments to attempt to reconcile the estimate of extension necessary to give the observed subsidence and that given by analysing the faults visible on the seismic line. Estimates of extension obtained by allowing antithetic faulting along inclined shear planes are consistent with the range of estimates necessary to account for the post-mid-Jurassic subsidence. The estimates for the prior mid-Jurassic faulting are still substantially less than those necessary to explain the subsidence. However, this is not of major concern as there are many reasons as to why analysis of the faulting should underestimate the pre mid-Jurassic extension. Our interpretation of the seismic line implies curved faults bottoming in the lithologically weak Zechstein salt. These faults are decoupled from the region below and, hence, do not reflect the geometry of the faulting in the basement.