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  • 1.
    Bin, Jiang
    et al.
    University of Gävle.
    Tao, Jia
    Future Position X.
    Agent-based simulation of human movement shaped by the underlying street structure2011In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 25, no 1, p. 51-64Article in journal (Refereed)
    Abstract [en]

    Relying on random and purposive moving agents, we simulated human movement in large street networks. We found that aggregate flow, assigned to individual streets, is mainly shaped by the underlying street structure, and that human moving behavior (either random or purposive) has little effect on the aggregate flow. This finding implies that given a street network, the movement patterns generated by purposive walkers (mostly human beings) and by random walkers are the same. Based on the simulation and correlation analysis, we further found that the closeness centrality is not a good indicator for human movement, in contrast to a long-standing view held by space syntax researchers. Instead we suggest that Google's PageRank and its modified version (weighted PageRank), betweenness and degree centralities are all better indicators for predicting aggregate flow.

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  • 2.
    Bin, Jiang
    et al.
    University of Gävle.
    Tao, Jia
    Future Position X.
    Zipf’s Law for All the Natural Cities in the United States: A Geospatial Perspective2011In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 25, no 8 (Special issue), p. 1269-1281Article in journal (Refereed)
    Abstract [en]

    This article provides a new geospatial perspective on whether or not Zipf's law holds for all cities or for the largest cities in the United States using a massive dataset and its computing. A major problem around this issue is how to define cities or city boundaries. Most of the investigations of Zipf's law rely on the demarcations of cities imposed by census data, for example, metropolitan areas and census-designated places. These demarcations or definitions (of cities) are criticized for being subjective or even arbitrary. Alternative solutions to defining cities are suggested, but they still rely on census data for their definitions. In this article we demarcate urban agglomerations by clustering street nodes (including intersections and ends), forming what we call natural cities. Based on the demarcation, we found that Zipf's law holds remarkably well for all the natural cities (over 2-4 million in total) across the United States. There is little sensitivity for the holding with respect to the clustering resolution used for demarcating the natural cities. This is a big contrast to urban areas, as defined in the census data, which do not hold stable for Zipf's law.

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  • 3.
    Bin, Jiang
    et al.
    Geomatics, University of Gävle.
    Xintao, Liu
    Automatic generation of the axial lines of urban environments to capture what we perceive2010In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 24, no 4, p. 545-558Article in journal (Refereed)
    Abstract [en]

    Based on the concepts of isovists and medial axes, we developed a set of algorithms that can automatically generate axial lines for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between buildings, where people can freely move around. The generation of the axial lines has been a key aspect of space syntax research, conventionally relying on hand-drawn axial lines of an urban environment, often called axial map, for urban morphological analysis. Although various attempts have been made towards an automatic solution, few of them can produce the axial map that consists of the least number of longest visibility lines, and none of them really works for different urban environments. Our algorithms provide a better solution than existing ones. Throughout this paper, we have also argued and demonstrated that the axial lines constitute a true skeleton, superior to medial axes, in capturing what we perceive about the urban environment. 

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    Automatic Generation of the Axial Lines of Urban Environments to Capture What We Perceive
  • 4.
    Bin, Jiang
    et al.
    Geomatics, University of Gävle.
    Xintao, Liu
    Computing the fewest-turn map directions based on the connectivity of natural roads2011In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 25, no 7, p. 1069-1082Article in journal (Refereed)
    Abstract [en]

    In this paper, we introduced a novel approach to computing the fewest-turn map directions or routes based on the concept of natural roads. Natural roads are joined road segments that perceptually constitute good continuity. This approach relies on the connectivity of natural roads rather than that of road segments for computing routes or map directions. Because of this, the derived routes posses the fewest turns. However, what we intend to achieve are the routes that not only possess the fewest turns, but are also as short as possible. This kind of map direction is more effective and favorable by people, because they bear less cognitive burden. Furthermore, the computation of the routes is more efficient, since it is based on the graph encoding the connectivity of roads, which is significantly smaller than the graph of road segments. We made experiments applied to eight urban street networks from North America and Europe in order to illustrate the above stated advantages. The experimental results indicate that the fewest-turn routes posses fewer turns and shorter distances than the simplest paths and the routes provided by Google Maps. For example, the fewest-turn-and-shortest routes are on average 15% shorter than the routes suggested by Google Maps, while the number of turns is just half as much. This approach is a key technology behind FromToMap.org - a web mapping service using openstreetmap data.

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    Computing the Fewest-turn Map Directions based on the Connectivity of Natural Roads
  • 5.
    Bin, Jiang
    et al.
    Geomatics, University of Gävle.
    Xintao, Liu
    Division of Geomatics, Department of Technology and Built Environment , University of Gavle , Gävle , Sweden.
    Scaling of geographic space from the perspective of city and field blocks and using volunteered geographic information2012In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 26, no 2, p. 215-229Article in journal (Refereed)
    Abstract [en]

    Scaling of geographic space refers to the fact that for a large geographic area its small constituents or units are much more common than the large ones. This paper develops a novel perspective to the scaling of geographic space using large street networks involving both cities and countryside. Given a street network of an entire country, we decompose the street network into individual blocks, each of which forms a minimum ring or cycle such as city blocks and field blocks. The block sizes demonstrate the scaling property, i.e., far more small blocks than large ones. Interestingly, we find that the mean of all the block sizes can easily separate between small and large blocks- a high percentage (e.g., 90%) of smaller ones and a low percentage (e.g., 10%) of larger ones. Based on this regularity, termed as the head/tail division rule, we propose an approach to delineating city boundaries by grouping the smaller blocks. The extracted city sizes for the three largest European countries (France, Germany and UK) exhibit power law distributions. We further define the concept of border number as a topological distance of a block far from the outmost border to map the center(s) of the country and the city. We draw an analogy between a country and a city (or geographic space in general) with a complex organism like the human body or the human brain to further elaborate on the power of this block perspective in reflecting the structure or patterns of geographic space.

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    Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information
  • 6. Huang, Wei
    et al.
    Li, Songnian
    Liu, Xintao
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Predicting human mobility with activity changes2015In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 29, no 9, p. 1569-1587Article in journal (Refereed)
    Abstract [en]

    Human mobility patterns can provide valuable information in understanding the impact of human behavioral regularities in urban systems, usually with a specific focus on traffic prediction, public health or urban planning. While existing studies on human movement have placed huge emphasis on spatial location to predict where people go next, the time dimension component is usually being treated with oversimplification or even being neglected. Time dimension is crucial to understanding and detecting human activity changes, which play a negative role in prediction and thus may affect the predictive accuracy. This study aims to predict human movement from a spatio-temporal perspective by taking into account the impact of activity changes. We analyze and define changes of human activity and propose an algorithm to detect such changes, based on which a Markov chain model is used to predict human movement. The Microsoft GeoLife dataset is used to test our methodology, and the data of two selected users is used to evaluate the performance of the prediction. We compare the predictive accuracy (R-2) derived from the data with and without implementing the activity change detection. The results show that the R-2 is improved from 0.295 to 0.762 for the user with obvious activity changes and from 0.965 to 0.971 for the user without obvious activity changes. The method proposed by this study improves the accuracy in analyzing and predicting human movement and lays the foundation for related urban studies.

  • 7.
    Mao, Bo
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Harrie, Lars
    Department of Physical Geography and Ecosystem Analysis, Lund University.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Fan, Hongchao
    Department of Cartography, Technical University of Munich.
    Real time visualisation of 3D city models in street view based on visual salienceIn: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824Article in journal (Refereed)
    Abstract [en]

    Street level visualization is an important application of the 3D city models. Challenges in the street level visualization are the cluttering of the detailed buildings and the performance. In this paper, a novel method for street level visualization based on visual salience evaluation is proposed. The basic idea of the method is to preserve these salient buildings in a view and remove the non-salient ones. The method is composed by pre-process and real-timevisualization. The pre-process starts by converting 3D building models in higher Levels of Detail (LoDs) into LoD1 with simplified ground plan. Then a number of index view points are created along the streets; these indexes refer both to the positions and the direction of the sights. A visual salience value is computed for each visible simplified building in respective index. The salience of the visible building is calculated based on the visual difference of the original and generalized models. We propose and evaluate three methods for visual salience: local difference, global difference and minimum projection area. The real-time visualization process starts by mapping the observer to its closest indexes. Then the street view is generated based on the building information stored in theindexes. A user study shows that the local visual salience gives better result than the global and area, and the proposed method can reduce the number of loaded building by 90% while still preserve the visual similarity with the original models.

  • 8.
    Murekatete, Rachel Mundeli
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Shirabe, Takeshi
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    A spatial and statistical analysis of the impact of transformation of raster cost surfaces on the variation of least-cost paths2018In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 32, no 11, p. 2169-2188Article in journal (Refereed)
    Abstract [en]

    Planners who are involved in locational decision-making often useraster-based geographic information systems to quantify the valueof land in terms of suitability or cost for a certain use. From acomputational point of view, this process can be seen as a transformationof one or more sets of values associated with a grid ofcells into another set of such values through a function reflectingone or more criteria. While it is generally anticipated that differenttransformations lead to different ‘best’ locations, little has beenknown on how such differences arise (or do not arise). The paperattempts to answer this question in the context of path planningthrough a series of computational experiments using a number ofrandom landscape grids with a variety of spatial and nonspatialstructures. In the experiments, we generated least-cost paths on anumber of cost grids transformed from the landscape grids usinga variety of transformation parameters and analyzed the locationsand (weighted) lengths of those paths. Results show that the samepair of terminal cells may well be connected by different least-costpaths on different cost grids though derived from the same landscapegrid and that the variation among those paths is affected byhow given values are distributed in the landscape grid as well asby how derived values are distributed in the cost grids. Mostsignificantly, the variation tends to be smaller when the landscapegrid contains more distinct patches of cells potentially attractingor distracting cost-saving passage or when the cost grid contains asmaller number of low-cost cells.

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  • 9.
    Murekatete, Rachel Mundeli
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Shirabe, Takeshi
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    An experimental analysis of least-cost path models on ordinal-scaled raster surfaces2020In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824Article in journal (Refereed)
    Abstract [en]

    Selection of optimal paths or sequences of cells from a grid of cells is one of the most basic functions of raster-based geographic information systems. For this function to work, it is often assumed that the optimality of a path can be evaluated by the sum of the weighted lengths of all its segments–weighted, i.e. by the underlying cell values. The validity of this assumption must be questioned, however, if those values are measured on a scale that does not permit arithmetic operations. Through computational experiments with randomly generated artificial landscapes, this paper compares two models, minisum and minimax path models, which aggregate the values of the cells associated with a path using the sum function and the maximum function, respectively. Results suggest that the minisum path model is effective if the path search can be translated into the conventional least-cost path problem, which aims to find a path with the minimum cost-weighted length between two terminuses on a ratio-scaled raster cost surface. On the other hand, the minimax path model is found mathematically sounder if the cost values are measured on an ordinal scale and practically useful if the problem is concerned not with the minimization of cost but with the maximization of some desirable condition such as suitability.

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  • 10.
    Prelipcean, Adrian Corneliu
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Gidofalvi, Gyözö
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Susilo, Yusak Octavius
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
    Measures of transport mode segmentation of trajectories2016In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 30, no 9, p. 1763-1784Article in journal (Refereed)
    Abstract [en]

    Rooted in the philosophy of point- and segment-based approaches for transportation mode segmentation of trajectories, the measures that researchers have adopted to evaluate the quality of the results (1) are incomparable across approaches, hence slowing the progress in the field and (2) do not provide insight about the quality of the continuous transportation mode segmentation. To address these problems, this paper proposes new error measures that can be applied to measure how well a continuous transportation mode segmentation model performs. The error measures introduced are based on aligning multiple inferred continuous intervals to ground truth intervals, and measure the cardinality of the alignment and the spatial and temporal discrepancy between the corresponding aligned segments. The utility of this new way of computing errors is shown by evaluating the segmentation of three generic transportation mode segmentation approaches (implicit, explicit–holistic, and explicit–consensus-based transport mode segmentation), which can be implemented in a thick client architecture. Empirical evaluations on a large real-word data set reveal the superiority of explicit–consensus-based transport mode segmentation, which can be attributed to the explicit modeling of segments and transitions, which allows for a meaningful decomposition of the complex learning task.

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    prelipcean_trajectory_segmentation
  • 11.
    Rui, Yikang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics. Nanjing University, China.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Exploring the relationship between street centrality and land use in Stockholm2014In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 28, no 7, p. 1425-1438Article in journal (Refereed)
    Abstract [en]

    This paper examines the relationship between different street centralities and land-use types in Stockholm. Major centrality measures of closeness, betweenness, and straightness are calculated at both global and local levels in both the primary and dual representations of the urban street network. Adaptive kernel density estimation is adopted to transform all unevenly distributed datasets to one continuous raster framework for further analysis. After computing statistical and spatial distribution of each centrality and land-use density map, we find that the density of each street centrality is highly correlated with one type of land use. Results imply that various centralities representing street properties from different aspects can capture the land development patterns of different land-use types by reflecting human activities, and are consequently important indicators to describe urban structure.

  • 12.
    Seegmiller, Lindsi
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Shirabe, Takeshi
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Tomlin, C. D.
    A method for finding least-cost corridors with reduced distortion in raster space2021In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 35, no 8, p. 1570-1591Article in journal (Refereed)
    Abstract [en]

    Given a grid of cells, each having a value indicating its cost per unit area, a variant of the least-cost path problem is to find a corridor of a specified width connecting two termini such that its cost-weighted area is minimized. A computationally efficient method exists for finding such corridors, but as is the case with conventional raster-based least-cost paths, their incremental orientations are limited to a fixed number of (typically eight orthogonal and diagonal) directions, and therefore, regardless of the grid resolution, they tend to deviate from those conceivable on the Euclidean plane. In this paper, we propose a method for solving the raster-based least-cost corridor problem with reduced distortion by adapting a distortion reduction technique originally designed for least-cost paths and applying it to an efficient but distortion-prone least-cost corridor algorithm. The proposed method is, in theory, guaranteed to generate no less accurate solutions than the existing one in polynomial time and, in practice, expected to generate more accurate solutions, as demonstrated experimentally using synthetic and real-world data.

  • 13.
    Shirabe, Takeshi
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment. Vienna University of Technology, Austria.
    A heuristic for the maximum value region problem in raster space2011In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 25, no 7, p. 1097-1116Article in journal (Refereed)
    Abstract [en]

    From a single-attribute raster layer in which each cell is assigned a numerical value, a connected set of a specified number of cells that has the maximum (or minimum) total value is selected. This is a highly common decision problem in the context of raster-based geographic information systems (GIS) and seems general enough to deserve inclusion in the standard functionality of such systems. Yet it is a computationally difficult optimization problem, for which no efficient exact solution method has been found. This article presents a new dynamic programming-based heuristic method for the problem. Its performance is tested with randomly generated raster layers with various degrees of spatial autocorrelation. Results suggest that the proposed heuristic is a promising alternative to the existing integer programming-based exact method, as it can handle significantly larger raster data with fair accuracy.

  • 14.
    Shirabe, Takeshi
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    A method for finding a least-cost wide path in raster space2016In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 30, no 8, p. 1469-1485Article in journal (Refereed)
    Abstract [en]

    Given a grid of cells each having an associated cost value, a raster version of the least-cost path problem seeks a sequence of cells connecting two specified cells such that its total accumulated cost is minimized. Identifying least-cost paths is one of the most basic functions of raster-based geographic information systems. Existing algorithms are useful if the path width is assumed to be zero or negligible compared to the cell size. This assumption, however, may not be valid in many real-world applications ranging from wildlife corridor planning to highway alignment. This paper presents a method to solve a raster-based least-cost path problem whose solution is a path having a specified width in terms of Euclidean distance (rather than by number of cells). Assuming that all cell values are positive, it does so by transforming the given grid into a graph such that each node represents a neighborhood of a certain form determined by the specified path width, and each arc represents a possible transition from one neighborhood to another. An existing shortest path algorithm is then applied to the graph. This method is highly efficient, as the number of nodes in the transformed graph is not more than the number of cells in the given grid and decreases with the specified path width. However, a shortcoming of this method is the possibility of generating a self-intersecting path which occurs only when the given grid has an extremely skewed distribution of cost values.

  • 15.
    Shirabe, Takeshi
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    A path that buys time to decide where to go2014In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 28, no 2, p. 314-325Article in journal (Refereed)
    Abstract [en]

    This paper considers the problem of planning a path in a circumstance where its origin is given, but its destination is not specified and is to be selected from among a set of candidate destinations during a trip. A situation like this may be experienced by a group of people who have different preferred destinations, as well as by an individual who is simply indecisive about where to go. To resolve such an uncertainty, one may stay at the origin until he decides on a destination, or choose to proceed on some path that does not overly deviate from a shortest path, whichever destination is eventually chosen, and make a decision on the way. The latter action is sensible when the risk of traveling longer is outweighed by the benefit of buying more time for a better destination decision. The problem of finding such a time-buying path is formulated and a simple algorithm is developed for its solution. Some extensions and applications are also discussed.

  • 16.
    Yang, Can
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics. KTH, Royal Institute of Technology in Sweden.
    Gidofalvi, Gyözö
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Fast map matching, an algorithm integrating hidden Markov model with precomputation2017In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, p. 1-24Article in journal (Refereed)
    Abstract [en]

    Wide deployment of global positioning system (GPS) sensors has generated a large amount of data with numerous applications in transportation research. Due to the observation error, a map matching (MM) process is commonly performed to infer a path on a road network from a noisy GPS trajectory. The increasing data volume calls for the design of efficient and scalable MM algorithms. This article presents fast map matching (FMM), an algorithm integrating hidden Markov model with precomputation, and provides an open-source implementation. An upper bounded origin-destination table is precomputed to store all pairs of shortest paths within a certain length in the road network. As a benefit, repeated routing queries known as the bottleneck of MM are replaced with hash table search. Additionally, several degenerate cases and a problem of reverse movement are identified and addressed in FMM. Experiments on a large collection of real-world taxi trip trajectories demonstrate that FMM has achieved a considerable single-processor MM speed of 25,000–45,000 points/second varying with the output mode. Investigation on the running time of different steps in FMM reveals that after precomputation is employed, the new bottleneck is located in candidate search, and more specifically, the projection of a GPS point to the polyline of a road edge. Reverse movement in the result is also effectively reduced by applying a penalty.

  • 17.
    Yang, Can
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gidofalvi, Gyözö
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Mining and visual exploration of closed contiguous sequential patterns in trajectories2018In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 32, no 7, p. 1282-1303Article in journal (Refereed)
    Abstract [en]

    Large collections of trajectories provide rich insight into movement patterns of the tracked objects. By map matching trajectories to a road network as sequences of road edge IDs, contiguous sequential patterns can be extracted as a certain number of objects traversing a specific path, which provides valuable information in travel demand modeling and transportation planning. Mining and visualization of such patterns still face challenges in efficiency, scalability, and visual cluttering of patterns. To address these challenges, this article firstly proposes a Bidirectional Pruning based Closed Contiguous Sequential pattern Mining (BP-CCSM) algorithm. By employing tree structures to create partitions of input sequences and candidate patterns, closeness can be checked efficiently by comparing nodes in a tree. Secondly, a system called Sequential Pattern Explorer for Trajectories (SPET) is built for spatial and temporal exploration of the mined patterns. Two types of maps are designed where a conventional traffic map gives an overview of the movement patterns and a dynamic offset map presents detailed information according to user-specified filters. Extensive experiments are performed in this article. BP-CCSM is compared with three other state-of-the-art algorithms on two datasets: a small public dataset containing clickstreams from an e-commerce and a large global positioning system dataset with more than 600,000 taxi trip trajectories. The results show that BP-CCSM considerably outperforms three other algorithms in terms of running time and memory consumption. Besides, SPET provides an efficient and convenient way to inspect spatial and temporal variations in closed contiguous sequential patterns from a large number of trajectories.

  • 18.
    Yang, Can
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gidófalvi, Gyözö
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Detecting regional dominant movement patterns in trajectory data with a convolutional neural network2019In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824Article in journal (Refereed)
    Abstract [en]

    Detecting movement patterns with complicated spatial or temporal characteristics is a challenge. The past decade has witnessed the success of deep learning in processing image, voice and text data. However, its application in movement pattern detection is not fully exploited. To address the research gap, this paper develops a deep learning approach to detect regional dominant movement patterns (RDMP) in trajectory data. Specifically, a novel feature descriptor called directional flow image (DFI) is firstly proposed to store the local directional movement information in trajectory data. A DFI classification model called TRNet is designed based on convolutional neural network. The model is then trained with a synthetic trajectory dataset covering 11 classes of commonly encountered movement patterns in reality. Finally, a sliding window detector is built to detect RDMP at multiple scales and a clustering-based merging method is proposed to prune the redundant detection results. Training of TRNet on the synthetic dataset achieves considerably high accuracy. Experiments on a real-world taxi trajectory dataset further demonstrate the effectiveness and efficiency of the proposed approach in discovering complex movement patterns in trajectory data.

  • 19. Yang, Jianyi
    et al.
    Tang, Guo'an
    Cao, Min
    Zhu, Rui
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment.
    An intelligent method to discover transition rules for cellular automata using bee colony optimisation2013In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 27, no 10, p. 1849-1864Article in journal (Refereed)
    Abstract [en]

    This paper presents a new, intelligent approach to discover transition rules for geographical cellular automata (CA) based on bee colony optimisation (BCO-CA) that can perform complex tasks through the cooperation and interaction of bees. The artificial bee colony miner algorithm is used to discover transition rules. In BCO-CA, a food source position is defined by its upper and lower thresholds for each attribute, and each bee searches the best upper and lower thresholds in each attribute as a zone. A transition rule is organised when the zone in each attribute is connected to another node by the operator And' and is linked to a cell status value. The transition rules are expressed by the logical structure statement IF-Then', which is explicit and easy to understand. Bee colony optimisation could better avoid the tendency to be vulnerable to local optimisation through local and global searching in the iterative process, and it does not require the discretisation of attribute values. Finally, The BCO-CA model is employed to simulate urban development in the Xi'an-Xian Yang urban area in China. Preliminary results suggest that this BCO approach is effective in capturing complex relationships between spatial variables and urban dynamics. Experimental results indicate that the BCO-CA model achieves a higher accuracy than the NULL and ACO-CA models, which demonstrates the feasibility and availability of the model in the simulation of complex urban dynamic change.

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