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  • 1.
    Andrée, Martin
    et al.
    Lantmäteriet.
    Larsson, Karolina
    KLM; Stockholms stad.
    Nordqvist Darell, Fanny
    Stockholms stad.
    Malm, Linus
    Tyréns.
    Tullberg, Odd
    WSP.
    Wallberg, Ann
    JM.
    Norsell, Johan
    NAI Svefa.
    Paasch, Jesper M.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Paulsson, Jenny
    Kungliga Tekniska Högskolan, Stockholm.
    Slutrapport för projektet Smart planering för byggande: Delprojekt 3 - BIM som informationsstöd för 3D fastighetsbildning2018Report (Other academic)
    Abstract [sv]

    Samhällsbyggnadsprocessen behöver utvecklas och bli smartare, öppnare och mer effektiv för ett ökat bostadsbyggande. En digitalisering av samhällsbyggnadsprocessen kan ge ett effektivare samarbete mellan kommun, fastighetsägare, byggherrar, medborgare, näringsliv och myndigheter.Vid bildande av tredimensionellt avgränsade fastigheter eller fastighetsutrymmen (3D-fastigheter) behöver gränsernas läge redovisas både verbalt och i kartor och ritningar, detsamma gäller berörda rättigheter. Det är idag ofta svårt att korrekt redovisa en 3D-volym med enbart dagens pappersritningar och även svårt att läsa en registerkarta i 2D med fastigheter och rättigheter beslutade i 3D. Beslutsunderlagen i fastighetsbildnings-processen behöver bli mer enhetliga och entydiga samt fastighetsinformationen behöver bli återanvändningsbar i hela samhällsbyggnadsprocessen.I detta projekt har vi studerat informationsbehovet i de olika tidpunkterna under fastighetsbildningsprocessen för 3D-fastigheter med fokus på vem som är ansvarig för att tillhandahålla informationsunderlag för att identifiera krav på utformning av 3D-modeller (t.ex BIM) och 3D-stöd för fastighetsbildning.Internationellt finns det ett stort intresse och många frågeställningar gällande samspelet mellan BIM och Fastighetsinformation; det är däremot ganska få fall som har identifierats där man har arbetat praktiskt med BIM i relation till redovisning av 3D-fastigheter.Projektethar även tittat på behov av visualisering och tillhandahållande av fastighetsinformation i 3D, hur informationen bör utformas för att kunna tolkas korrekt samt nyttjas vidare av andra aktörer i samhällsbyggnadsprocessen.Slutsatsen i projektetär att en framtida arbetsmodell där man i samband med myndighetsutövningen för fastighetsbildning samverkar med stöd av BIM och geografisk information i ärendehandläggningen kan ge stora effekter på både myndighetens effektivitet och i ärendeutövningen och för förståelsen av fastighetbildningsbeslutet hos samtliga intressenter i processen. För att det arbete som genomförts i denna utredning skall få genomslag i den dagliga verksamheten rekommenderar vibland annatatt de statliga och kommunala lantmäterimyndigheterna arbetar vidare med att utveckla arbetsprocessen och rekommendationerna för 3D-fastighetsbildning baserat på resultatet från detta projekt och redan i dagens modell efterfrågar att man i handläggningsprocessen kan arbeta BIM-baserat även om kommande beslutshandlingar under en övergångsperiod fortfarande kommer att vara baserade på ritningsbilagor i 2D.

  • 2.
    Andrée, Martin
    et al.
    Lantmäteriet.
    Paasch, Jesper M.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Paulsson, Jenny
    Kungliga Tekniska Högskolan.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    BIM and 3D property visualisation2018In: FIG Congress 2018: Proceedings, 2018, article id 9367Conference paper (Other academic)
    Abstract [en]

    The concept of 3D property has only existed a short period of time in Sweden, being introduced in 2004 and expanded in 2009 by the addition of condominium (apartment) ownership. It is therefore a rather new form of land management, and the demand for 3D property formation has not been as high as initially expected. There is however an increased interest in 3D property and ownership apartments today, also as being part of the nation’s geospatial infrastructure together with related 3D information for e.g. buildings, utility networks and other features. An effective management of 3D property is depending on, among other things, visualization, representation and storage of 3D real property data, such as legal boundaries and real property rights. There are at present a number of ongoing 3D development and research projects focusing on visualization and standardization of 3D cadastral boundaries. They are part of the national "Smart Built Environment" development and research program, which includes the use of BIM in the (future) 3D property formation process with focus on visualization of 3D real property and condominiums, and specification of requirements and evaluation of 3D digital real property information created and managed in the processes.

    This paper presents the preliminary results of the working group on visualization of 3D boundaries in the project "Smart planning, construction and management processes throughout the life cycle". The aim is to test the results produced in the project "Information for planning, real property formation and building permission", working group "BIM for 3D property formation." The purpose of this working group is to set the requirements for and evaluate the test bed for 3D property information. The focus is on visualization of 3D property and ownership apartments. The proposed model for digitization and visualization of 3D property formation will be tested in a test bed environment. A pilot case from the Stockholm area is then used in the test bed to see how it could work in practice.

    The expected outcome is recommendations for the exchange of documentation and other digital information in 3D processes, the visualization of legal boundaries for stakeholders, registration of legal 3D objects in the Swedish national real property register and how to communicate 3D models to right holders/stakeholders for 3D property and condominiums and the property market, as well as suggestions for a homogeneous, effective and digital flow of 3D information to be used by actors and other stakeholders in the property formation, planning and building processes.

  • 3.
    Aslani, Mohammad
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Mesgari, Mohammad Saadi
    Division of Visual Information and Interaction, Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, Iran.
    Wiering, Marco
    Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, Groningen, Netherlands.
    Developing adaptive traffic signal control by actor-critic and direct exploration methods2018In: Proceedings of the Institution of Civil Engineers: Transport, ISSN 0965-092X, E-ISSN 1751-7710, article id jtran.17.00085Article in journal (Refereed)
    Abstract [en]

    Designing efficient traffic signal controllers has always been an important concern in traffic engineering. This is owing to the complex and uncertain nature of traffic environments. Within such a context, reinforcement learning has been one of the most successful methods owing to its adaptability and its online learning ability. Reinforcement learning provides traffic signals with the ability automatically to determine the ideal behaviour for achieving their objective (alleviating traffic congestion). In fact, traffic signals based on reinforcement learning are able to learn and react flexibly to different traffic situations without the need of a predefined model of the environment. In this research, the actor-critic method is used for adaptive traffic signal control (ATSC-AC). Actor-critic has the advantages of both actor-only and critic-only methods. One of the most important issues in reinforcement learning is the trade-off between exploration of the traffic environment and exploitation of the knowledge already obtained. In order to tackle this challenge, two direct exploration methods are adapted to traffic signal control and compared with two indirect exploration methods. The results reveal that ATSC-ACs based on direct exploration methods have the best performance and they consistently outperform a fixed-time controller, reducing average travel time by 21%.

  • 4.
    Aslani, Mohammad
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, Iran.
    Mohammad Saadi, Mesgari
    Division of Visual Information and Interaction, Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Wiering, Marco A.
    Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, Groningen, Netherlands.
    Traffic signal optimization through discrete and continuous reinforcement learning with robustness analysis in downtown Tehran2018In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 38, p. 639-655Article in journal (Refereed)
    Abstract [en]

    Traffic signal control plays a pivotal role in reducing traffic congestion. Traffic signals cannot be adequately controlled with conventional methods due to the high variations and complexity in traffic environments. In recent years, reinforcement learning (RL) has shown great potential for traffic signal control because of its high adaptability, flexibility, and scalability. However, designing RL-embedded traffic signal controllers (RLTSCs) for traffic systems with a high degree of realism is faced with several challenges, among others system disturbances and large state-action spaces are considered in this research.

    The contribution of the present work is founded on three features: (a) evaluating the robustness of different RLTSCs against system disturbances including incidents, jaywalking, and sensor noise, (b) handling a high-dimensional state-action space by both employing different continuous state RL algorithms and reducing the state-action space in order to improve the performance and learning speed of the system, and (c) presenting a detailed empirical study of traffic signals control of downtown Tehran through seven RL algorithms: discrete state Q-learning(λ" role="presentation">), SARSA(λ" role="presentation">), actor-critic(λ" role="presentation">), continuous state Q-learning(λ" role="presentation">), SARSA(λ" role="presentation">), actor-critic(λ" role="presentation">), and residual actor-critic(λ" role="presentation">).

    In this research, first a real-world microscopic traffic simulation of downtown Tehran is carried out, then four experiments are performed in order to find the best RLTSC with convincing robustness and strong performance. The results reveal that the RLTSC based on continuous state actor-critic(λ" role="presentation">) has the best performance. In addition, it is found that the best RLTSC leads to saving average travel time by 22% (at the presence of high system disturbances) when it is compared with an optimized fixed-time controller.

  • 5.
    Aslani, Mohammad
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Division of Visual Information and Interaction, Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Wiering, Marco
    Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, Groningen, the Netherlands.
    Continuous residual reinforcement learning for traffic signal control optimization2018In: Canadian journal of civil engineering (Print), ISSN 0315-1468, E-ISSN 1208-6029, Vol. 45, no 8, p. 690-702Article in journal (Refereed)
    Abstract [en]

    Traffic signal control can be naturally regarded as a reinforcement learning problem. Unfortunately, it is one of the most difficult classes of reinforcement learning problems owing to its large state space. A straightforward approach to address this challenge is to control traffic signals based on continuous reinforcement learning. Although they have been successful in traffic signal control, they may become unstable and fail to converge to near-optimal solutions. We develop adaptive traffic signal controllers based on continuous residual reinforcement learning (CRL-TSC) that is more stable. The effect of three feature functions is empirically investigated in a microscopic traffic simulation. Furthermore, the effects of departing streets, more actions, and the use of the spatial distribution of the vehicles on the performance of CRL-TSCs are assessed. The results show that the best setup of the CRL-TSC leads to saving average travel time by 15% in comparison to an optimized fixed-time controller.

  • 6.
    Lim, Nancy J.
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Brandt, S. Anders
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Assessment of spatial-based decisions and user perspectives in utilisation of flood certainty mapsManuscript (preprint) (Other academic)
  • 7.
    Liu, Fei
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Centre for Image Analysis, Uppsala University, Uppsala, Sweden.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Centre for Image Analysis, Uppsala University.
    On the precision of third person perspective augmented reality for target designation tasks2017In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 76, no 14, p. 15279-15296Article in journal (Refereed)
    Abstract [en]

    The availability of powerful consumer-level smart devices and off-the-shelf software frameworks has tremendously popularized augmented reality (AR) applications. However, since the built-in cameras typically have rather limited field of view, it is usually preferable to position AR tools built upon these devices at a distance when large objects need to be tracked for augmentation. This arrangement makes it difficult or even impossible to physically interact with the augmented object. One solution is to adopt third person perspective (TPP) with which the smart device shows in real time the object to be interacted with, the AR information and the user herself, all captured by a remote camera. Through mental transformation between the user-centric coordinate space and the coordinate system of the remote camera, the user can directly interact with objects in the real world. To evaluate user performance under this cognitively demanding situation, we developed such an experimental TPP AR system and conducted experiments which required subjects to make markings on a whiteboard according to virtual marks displayed by the AR system. The same markings were also made manually with a ruler. We measured the precision of the markings as well as the time to accomplish the task. Our results show that although the AR approach was on average around half a centimeter less precise than the manual measurement, it was approximately three times as fast as the manual counterpart. Additionally, we also found that subjects could quickly adapt to the mental transformation between the two coordinate systems.

  • 8.
    Liu, Fei
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Centre for Image Analysis, Uppsala University, Uppsala, Sweden.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Centre for Image Analysis, Uppsala University, Uppsala, Sweden.
    Precision study on augmented reality-based visual guidance for facility management tasks2018In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 90, p. 79-90Article in journal (Refereed)
    Abstract [en]

    One unique capability of augmented reality (AR) is to visualize hidden objects as a virtual overlay on real occluding objects. This “X-ray vision” visualization metaphor has proved to be invaluable for operation and maintenance tasks such as locating utilities behind a wall. Locating virtual occluded objects requires users to estimate the closest projected positions of the virtual objects upon their real occluders, which is generally under the influence of a parallax effect. In this paper we studied the task of locating virtual pipes behind a real wall with “X-ray vision” and the goal is to establish relationships between task performance and spatial factors causing parallax through different forms of visual augmentation. We introduced and validated a laser-based target designation method which is generally useful for AR-based interaction with augmented objects beyond arm's reach. The main findings include that people can mentally compensate for the parallax error when extrapolating positions of virtual objects on the real surface given traditional 3D depth cues for spatial understanding. This capability is, however, unreliable especially in the presence of the increasing viewing offset between the users and the virtual objects as well as the increasing distance between the virtual objects and their occluders. Experiment results also show that positioning performance is greatly increased and unaffected by those factors if the AR support provides visual guides indicating the closest projected positions of virtual objects on the surfaces of their real occluders.

  • 9.
    Milutinovic, Goran
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Ahonen-Jonnarth, Ulla
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Decision, Risk and Policy Analysis.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Department of Information Technology, Uppsala University, Uppsala, Sweden.
    GISwaps: A New Method for Decision Making in Continuous Choice Models Based on Even Swaps2018In: International Journal of Decision Support System Technology, ISSN 1941-6296, E-ISSN 1941-630X, Vol. 10, no 3, p. 57-78Article in journal (Refereed)
    Abstract [en]

    This article describes how continuous GIS-MCDM problems are commonly managed by combining some weighting method based on pairwise comparisons of criteria with an aggregation method. The reliability of this approach may be questioned, though. First, assigning weights to criteria, without taking into consideration the actual consequences or values of the alternatives, is in itself controversial. Second, the value functions obtained by this approach are in most cases linear, which is seldom the case in reality. The authors present a new method for GIS-MCDM in continuous choice models based on Even Swaps. The method is intuitive and easy to use, based on value trade-offs, and thus not relying on criteria weighting. Value functions obtained when using the method may be linear or non-linear, and thereby are more sensitive to the characteristics of the decision space. The performed case study showed promising results regarding the reliability of the method in GIS-MCDM context.

  • 10.
    Milutinovic, Goran
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Ahonen-Jonnarth, Ulla
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Decision, Risk and Policy Analysis.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science. Division of Visual Information and Interaction, Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Brandt, S. Anders
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.
    The impact of interactive visualization on trade-off-based geospatial decision-making2019In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 33, no 10, p. 2094-2123Article in journal (Refereed)
    Abstract [en]

    In a previous work we developed GISwaps, a novel method for geospatial decision-making based on Even Swaps. In this paper, we present the results of an evaluation of a visualization framework integrated with this method, implemented within a decision support system. This evaluation is based on two different studies. In the quantitative study, 15 student participants used GISwaps with no visual features, and 15 participants used GISwaps with the integrated visual framework, as the tool in a solar farm site location case study. The results of the quantitative evaluation show positive impact of the visualization in terms of increased coherency in trade-offs. The results also show a statistically significant difference in average trade-off values between the groups, with users from the non-visual group setting on average 20% higher trade-off values compared with the users in the visual group. In the qualitative study, we had one expert in GIS, two experts in decision-making and two experts in solar energy as a focus user group. Data in this study were obtained by observations and semi-structured interviews with the participants. The impact of the visualization framework was assessed positively by all participants in the expert group. 

  • 11.
    Milutinovic, Goran
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Visual GISwaps - an interactive visualization framework for geospatial decision making2018In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018, Funchal, Madeira - Portugal, January 27-29, 2018 / [ed] Alexandru Telea, Andreas Kerren and Jose Braz, SciTePress, 2018, p. 236-243Conference paper (Refereed)
    Abstract [en]

    Different visualization techniques are frequently used in geospatial information systems (GIS) to support geospatial decision making. However, visualization in GIS context is usually limited to the initial phase of the decision-making process, i.e. situation analysis and problem recognition. This is partly due to the choice of methods used in GIS multi-criteria decision-making (GIS-MCDM) that usually deploy some non-interactive approach, leaving the decision maker little or no control over the calculation of overall values for the considered alternatives; the role of visualization is thus reduced to presenting the final results of the computations. The contributions of this paper are twofold. First, we introduce GISwaps, a novel, intuitive interactive method for decision making in geospatial context. The second and main contribution is an interactive visualization of the choice phase of the decision making process. The visualization allows the decision maker to explore the consequences of trade-offs and costs accepted during the iterative decision process, both in terms of the abstract relation between different decision variables and in spatial context.

  • 12.
    Ooms, Kristien
    et al.
    Department of Geography, Ghent University, Ghent, Belgium.
    Åhlén, Julia
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Detecting Collapsed Buildings in Case of Disaster: Which Visualisation Works Best?2018In: Eye Tracking for Spatial Research: Proceedings of the 3rd International Workshop / [ed] Kiefer, Peter Giannopoulos, Ioannis Göbel, Fabian Raubal, Martin Duchowski, Andrew T., Zurich, 2018Conference paper (Refereed)
    Abstract [en]

    A user study is conducted to evaluate the efficiency and effectiveness of two types of visualizations to identify damage sites in case of disaster. The test consists out 36 trials (18 for each visualisation) and in each trial an area of 1x1km, located in Ghent, is displayed on a screen. This image shows the combined height information from before and after the disaster. The first visualisation, page flipping, is based on greyscale images with height information from the pre- and post-disaster situation between which users can switch manually. The second visualisation, difference image, is a result of subtracting the heights (before versus after) and assigning a blue-white-red colour ramp. In order to simulate the urgency with which the data is captured, systematic and random imperfections are introduced in the post-disaster data. All participants’ mouse and key interactions are logged, which is further complemented by the registration of their eye movements. This give insights the visualizations’ efficiency, effectiveness and the overall search strategies of the participants.

  • 13.
    Ooms, Kristien
    et al.
    Department of Geography, Ghent University, Ghent, Belgium.
    Åhlén, Julia
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Efficiency and effectiveness in case of disaster: a visual damage assessment test2018In: Proceedings of the International Cartographic Association (Proceedings of the ICA), 2018, Vol. 1, article id 86Conference paper (Refereed)
    Abstract [en]

     A user study is conducted to evaluate the efficiency and effectiveness of two types of visualizations to identify damages sites in case of disaster. The test consists out 36 trials (18 for each visualisation) and in each trial an area of 1×1km, located in Ghent, is displayed on a screen. This image shows the combined height information from before and after the disaster. The first visualisation, page flipping, is based on greyscale images with height information from the pre- and post-disaster situation between which users can switch manually. The second visualisation, difference image, is a result of subtracting the heights (before versus after) and assigning a blue-white-red colour ramp. In order to simulate the urgency with which the data is captured, systematic and random imperfections are introduced in the post-disaster data. All participants’ mouse and key interactions are logged, which is further complemented by the registration of their eye movements. This give insights the visualizations’ efficiency, effectiveness and the overall search strategies of the participants.

  • 14.
    Ren, Zheng
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.
    Jiang, Bin
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Capturing and characterizing human activities using building locations in America2019In: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 8, no 5, article id 200Article in journal (Refereed)
    Abstract [en]

    Capturing and characterizing collective human activities in a geographic space have become much easier than ever before in the big era. In the past few decades it has been difficult to acquire the spatiotemporal information of human beings. Thanks to the boom in the use of mobile devices integrated with positioning systems and location-based social media data, we can easily acquire the spatial and temporal information of social media users. Previous studies have successfully used street nodes and geo-tagged social media such as Twitter to predict users’ activities. However, whether human activities can be well represented by social media data remains uncertain. On the other hand, buildings or architectures are permanent and reliable representations of human activities collectively through historical footprints. This study aims to use the big data of US building footprints to investigate the reliability of social media users for human activity prediction. We created spatial clusters from 125 million buildings and 1.48 million Twitter points in the US. We further examined and compared the spatial and statistical distribution of clusters at both country and city levels. The result of this study shows that both building and Twitter data spatial clusters show the scaling pattern measured by the scale of spatial clusters, respectively, characterized by the number points inside clusters and the area of clusters. More specifically, at the country level, the statistical distribution of the building spatial clusters fits power law distribution. Inside the four largest cities, the hotspots are power-law-distributed with the power law exponent around 2.0, meaning that they also follow the Zipf’s law. The correlations between the number of buildings and the number of tweets are very plausible, with the r square ranging from 0.53 to 0.74. The high correlation and the similarity of two datasets in terms of spatial and statistical distribution suggest that, although social media users are only a proportion of the entire population, the spatial clusters from geographical big data is a good and accurate representation of overall human activities. This study also indicates that using an improved method for spatial clustering is more suitable for big data analysis than the conventional clustering methods based on Euclidean geometry.

  • 15.
    Åhlén, Julia
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Uppsala University, Department of Information Technology, Sweden.
    Mapping of roof types in orthophotos using feature descriptors2018In: International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM: Proceedings of the International Multidisciplinary Scientific GeoConference SGEM, 2018, Vol. 18, p. 285-291Conference paper (Refereed)
    Abstract [en]

    In the context of urban planning, it is very important to estimate the nature of the roof of every building and, in particular, to make the difference between flat roofs and gable ones. This analysis is necessary in seismically active areas. Also in the assessment of renewable energy projects such solar energy, the shape of roofs must be accurately retrieved. In order to perform this task automatically on a large scale, aerial photos provide a useful solution. The goal of this research project is the development of algorithm for accurate mapping of two different roof types in digital aerial images. The algorithm proposed in this paper includes several components: pre-processing step to reduce illumination differences of individual roof surfaces, statistical moments calculation and color indexing. Roof models are created and saved as masks with feature specific descriptors. Masks are then used to mark areas that contain elements of the different roof types (e.g. gable and hip). The final orthophoto visualize an accurate position of each of the roof types. The result is evaluated using precision recall method.

  • 16.
    Åhlén, Julia
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Urban and regional planning/GIS-institute.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Time-space visualisation of Amur river channel changes due to flooding disaster2014In: Proceedings of the International Multidisciplinary Scientific GeoConference SGEM, 2014, Vol. 1:2, p. 873-882Conference paper (Refereed)
    Abstract [en]

    The analysis of flooding levels is a highly complex temporal and spatial assessment task that involves estimation of distances between references in geographical space as well as estimations of instances along the time-line that coincide with  given spatial locations. This work has an aim to interactively explore changes of Amur River boundaries caused by the severe flooding in September 2013. In our analysis of river bank changes we use satellite imagery (Landsat 7) to extract parts belonging to Amur River. We use imagery from that covers time interval July 2003 until February 2014. Image data is pre-processed using low level image processing techniques prior to visualization. Pre-processing has a purpose to extract information about the boundaries of the river, and to transform it into a vectorized format, suitable as inputs subsequent visualization. We develop visualization tools to explore the spatial and temporal relationship in the change of river banks. In particular the visualization shall allow for exploring specific geographic locations and their proximity to the river/floods at arbitrary times. We propose a time space visualization that emanates from edge detection, morphological operations and boundary statistics on Landsat 2D imagery in order to extract the borders of Amur River. For the visualization we use the time-space-cube metaphor. It is based on a 3D rectilinear context, where the 2D geographical coordinate system is extended with a time-axis pointing along the 3rd Cartesian axis. Such visualization facilitates analysis of the channel shape of Amur River and thus enabling for a conclusion regarding the defined problem. As a result we demonstrate our time-space visualization for river Amur and using some amount of geographical point data as a reference we suggest an adequate method of interpolation or imputation that can be employed to estimate value at a given location and time.   

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