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1.
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.  相似文献   

2.
非均质空间随机扩散方程及其在城市基准地价评估中的运用   总被引：14，自引：1，他引：14  
单卫东  包浩生 《地理学报》1995,50(3):215-223
本文通过在非均质空间条件下，革新随机游动扩散模式的理论推导，建立了非均质空间随机扩散方程，并对其参数的确定进行了讨论。同时，将此方程应用于城市基准地价评估，予以实验验证。  相似文献   

3.
Why GPS makes distances bigger than they are   总被引：1，自引：0，他引：1  
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.  相似文献   

4.
This article presents an algorithm for decentralized (in-network) data mining of the movement pattern flock among mobile geosensor nodes. The algorithm DDIG (Deferred Decentralized Information Grazing) allows roaming sensor nodes to ‘graze’ over time more information than they could access through their spatially limited perception range alone. The algorithm requires an intrinsic temporal deferral for pattern mining, as sensor nodes must be enabled to collect, memorize, exchange, and integrate their own and their neighbors' most current movement history before reasoning about patterns. A first set of experiments with trajectories of simulated agents showed that the algorithm accuracy increases with growing deferral. A second set of experiments with trajectories of actual tracked livestock reveals some of the shortcomings of the conceptual flocking model underlying DDIG in the context of a smart farming application. Finally, the experiments underline the general conclusion that decentralization in spatial computing can result in imperfect, yet useful knowledge.  相似文献   

5.
A city can be topologically represented as a connectivity graph, consisting of nodes representing individual spaces and links if the corresponding spaces are intersected. It turns out in the space syntax literature that some defined topological metrics can capture human movement rates in individual spaces. In other words, the topological metrics are significantly correlated to human movement rates, and individual spaces can be ranked by the metrics for predicting human movement. However, this correlation has never been well justified. In this paper, we study the same issue by applying the weighted PageRank algorithm to the connectivity graph or space–space topology for ranking the individual spaces, and find surprisingly that: (1) the PageRank scores are better correlated to human movement rates than the space syntax metrics, and (2) the underlying space–space topology demonstrates small world and scale free properties. The findings provide a novel justification as to why space syntax, or topological analysis in general, can be used to predict human movement. We further conjecture that this kind of analysis is no more than predicting a drunkard's walking on a small world and scale free network.  相似文献   

6.
This article describes a novel approach for finding similar trajectories, using trajectory segmentation based on movement parameters (MPs) such as speed, acceleration, or direction. First, a segmentation technique is applied to decompose trajectories into a set of segments with homogeneous characteristics with respect to a particular MP. Each segment is assigned to a movement parameter class (MPC), representing the behavior of the MP. Accordingly, the segmentation procedure transforms a trajectory to a sequence of class labels, that is, a symbolic representation. A modified version of edit distance called normalized weighted edit distance (NWED) is introduced as a similarity measure between different sequences. As an application, we demonstrate how the method can be employed to cluster trajectories. The performance of the approach is assessed in two case studies using real movement datasets from two different application domains, namely, North Atlantic Hurricane trajectories and GPS tracks of couriers in London. Three different experiments have been conducted that respond to different facets of the proposed techniques and that compare our NWED measure to a related method.  相似文献   

7.
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.  相似文献   

8.
ABSTRACT

We present methodological advances to a recently developed framework to study sequential habitat use by animals using a visually-explicit and tree-based Sequence Analysis Method (SAM), derived from molecular biology and more recently used in time geography. Habitat use sequences are expressed as annotations obtained by intersecting GPS movement trajectories with environmental layers. Here, we develop IM-SAM, where we use the individual reference area of use as the reference spatial context. To assess IM-SAM’s applicability, we investigated the sequential use of open and closed habitats across multiple European roe deer populations ranging in landscapes with contrasting structure. Starting from simulated sequences based on a mechanistic movement model, we found that different sequential patterns of habitat use were distinguished as separate, robust clusters, with less variable cluster size when habitats were present in equal proportions within the individual reference area of use. Application on real roe deer sequences showed that our approach effectively captured variation in spatio-temporal patterns of sequential habitat use, and provided evidence for important behavioral processes, such as day-night habitat alternation. By characterizing sequential habitat use patterns of animals, we may better evaluate the temporal trade-offs in animal habitat use and how they are affected by changes in landscapes.  相似文献   

9.
通过相邻图像减法获得了清晰的沙粒运动图像。在此基础上,分别提出了通过人工目视解译与计算机追踪相结合进行跃移颗粒数字轨迹追踪的多帧图像匹配算法以及更适用于计算跃移沙粒群运动瞬时速度场的两帧图像匹配算法。结果表明：与前人研究采用的单纯的人工匹配计算相比,多帧图像匹配算法在保证数据准确性的同时,极大的提高了工作效率。两帧图像匹配算法克服了传统的PTV匹配算法对流场内粒子群运动特征的要求,更加适宜于跃移沙粒群的速度测量,不仅拥有较高的匹配率,而且全过程实现全自动计算,具有较高的计算速度,能够为跃移相整体运动特性研究提供具有代表性的数据。因此,此方法有助于高速摄影技术在研究跃移沙粒运动中的优势更加明显。  相似文献   

10.
Time plays an important role in the analysis of moving object data. For many applications it is not sufficient to only compare objects at exactly the same times, or to consider only the geometry of their trajectories. We show how to leverage between these two approaches by extending a tool from curve analysis, namely the free space diagram. Our approach also allows us to take further attributes of the objects like speed or direction into account. We demonstrate the usefulness of the new tool by applying it to the problem of detecting single file movement. A single file is a set of moving entities, which are following each other, one behind the other. Our algorithm is the first one developed for detecting such movement patterns. For this application, we analyse demonstrate the performance of our tool both theoretically experimentally.  相似文献   

11.
非均质空间动态随机扩散的一般方程及其应用   总被引：1，自引：0，他引：1  
单卫东  包浩生 《地理科学》1997,17(2):127-133
通过非均质空间条件下革新随机游动模式的理论推导，结合实证研究成果，建立了非均质空间动态随机扩散方程。同时，将此方程应用于城市基准地价评估，予以实例验证。  相似文献   

12.
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.  相似文献   

13.
唐锦玥  张维阳  王逸飞 《地理研究》2020,39(5):1166-1181
人口移动是城际要素流动和资源配置的主要载体,是建构区域网络组织的主要形式。本研究关注人口移动的重要组分——短时间尺度48小时内城际日常移动（daily intercity mobility）,基于微博签到大数据,通过分析长三角人口日常移动的城际格局发现,人口流动具有向多核心极化的分布特征,受到省级行政边界阻碍,并存在明显的省际差异。通过重力模型进行反向验证,对影响因素进行系统统计检验发现,移动的时间等成本和产业结构、文化、教育等城市特征补充塑造了由物理距离决定的城际移动模式,且相比于移动成本,城市特征对人口移动有着更大的影响。本文拓展了重力模型检验网络影响机制的方法实践,解析了城际日常移动机理,并从人口日常移动角度为理解长三角一体化的进程与优化策略提供参考。  相似文献   

14.
A better understanding of the current and future distributions of organisms is a critical facet of biodiversity conservation, and species distribution models (SDMs) are an important framework for achieving this. Despite the potential of SDMs to address an array of biogeography questions, they are subject to a number of conceptual and methodological uncertainties, such as the role of animal movement processes in determining geographic ranges. Movement processes have only recently been incorporated in SDMs, predominantly conceptualized as broad-scale movement processes (e.g., dispersal), while finer scale ambulatory movements of mobile animals (e.g., foraging) have been omitted. This research addresses this gap by developing a model that simulates the dynamic relationship between movement and biotic resources (e.g., food sources) for oilbirds (Steatornis caripensis) in Venezuela. This simulation represented the sustainability of an oilbird’s neighborhood, based on the connectivity, accessibility, and viability of its biotic resources. These dynamic variables improved the accuracy and ecological realism of the SDM projection compared to other commonly applied SDM scenarios. Integration of a Lagrangian (individual-level) form of movement in SDM with step-selection functions to parameterize biased-correlated random walks provides a new empirical framework for applying geographic context to simulation.  相似文献   

15.
The growing field of movement ecology uses high resolution movement data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses contribute to various subfields of ecology – inter alia behavioral, disease, landscape, resource, and wildlife – and facilitate novel exploration in fields ranging from conservation planning to public health. Despite the growing availability and general accessibility of animal movement data, much potential remains for the analytical methods of movement ecology to be incorporated in all types of geographic analyses. This review provides for the Geographical Information Sciences (GIS) community an overview of the most common movement metrics and methods of analysis employed by animal ecologists. Through illustrative applications, we emphasize the potential for movement analyses to promote transdisciplinary GIS/wildlife-ecology research.  相似文献   

16.
人群的移动模拟应用广泛,但为不同时空尺度模拟需求开发不同的模拟系统十分困难和繁琐。该文设计了一种人群的空间移动模型(GMPM),GMPM具有多粒度特性,可应用于不同的领域,满足不同空间尺度、时间尺度的人群移动模拟需求;同时,GMPM又是一种通用开发模型原型,基于GMPM可以构造针对不同应用领域的人群空间移动模拟模型。最后,介绍了不同时空尺度人群移动模拟应用案例。  相似文献   

17.
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.  相似文献   

18.
本文提出一种基于随机森林的元胞自动机城市扩展(RF-CA)模型。通过在多个决策树的生成过程中分别对训练样本集和分裂节点的候选空间变量引入随机因素,提取城市扩展元胞自动机的转换规则。该模型便于并行构建,能在运算量没有显著增加的前提下提高预测的精度,对城市扩展中存在的随机因素有较强的容忍度。RF-CA模型可进行袋外误差估计,以快速获取模型参数;也可度量空间变量重要性,解释各空间变量在城市扩展中的作用。将该模型应用于佛山市1988-2012年的城市扩展模拟中,结果表明,与常用的逻辑回归模型相比,RF-CA模型进行模拟和预测分别能够提高1.7%和2.6%的精度,非常适用于复杂非线性特征的城市系统演变模型与扩展研究;通过对影响佛山市城市扩展的空间变量进行重要性度量,发现对佛山城市扩张模拟研究而言,距国道的距离与距城市中心的距离具有最重要的作用。  相似文献   

19.
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.  相似文献   

20.
In this paper, we propose a method for predicting the distributions of people’s trajectories on the road network throughout a city. Specifically, we predict the number of people who will move from one area to another, their probable trajectories, and the corresponding likelihoods of those trajectories in the near future, such as within an hour. With this prediction, we will identify the hot road segments where potential traffic jams might occur and reveal the formation of those traffic jams. Accurate predictions of human trajectories at a city level in real time is challenging due to the uncertainty of people’s spatial and temporal mobility patterns, the complexity of a city level’s road network, and the scale of the data. To address these challenges, this paper proposes a method which includes several major components: (1) a model for predicting movements between neighboring areas, which combines both latent and explicit features that may influence the movements; (2) different methods to estimate corresponding flow trajectory distributions in the road network; (3) a MapReduce-based distributed algorithm to simulate large-scale trajectory distributions under real-time constraints. We conducted two case studies with taxi data collected from Beijing and New York City and systematically evaluated our method.  相似文献   

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