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  • Mitigating Spoofed GNSS Trajectories through Nature Inspired Algorithm
    GeoInformatica (IF 1.317) Pub Date : 2020-05-22
    Saravjeet Singh, Jaiteg Singh, Sukhjit Singh

    Advancement in technology has resulted in the easy sharing of locations across various stakeholders. Unprotected sharing of location information makes any Global Navigation Satellite System (GNSS) device vulnerable to spoofing attacks. Spoofed GNSS signals propagate misleading trajectories to cripple any Location-Based Service (LBS). This manuscript introduces a novel algorithm for the detection and

  • Affine-invariant querying of spatial data using a triangle-based logic
    GeoInformatica (IF 1.317) Pub Date : 2020-05-19
    Sofie Haesevoets, Bart Kuijpers, Peter Z. Revesz

    If the same land area is photographed from two different angles, then a computer can recognize the two images to show the same land area by proving that the images are affine-invariant. In practice, images are abstracted as a type of spatial data that is a finite set of triangles. Hence we propose a simple affine-generic query language with variables over finite sets of triangles. The proposed query

  • A novel spectral–spatial based adaptive minimum spanning forest for hyperspectral image classification
    GeoInformatica (IF 1.317) Pub Date : 2020-05-11
    Jing Lv, Huimin Zhang, Ming Yang, Wanqi Yang

    The classification methods based on minimum spanning forest (MSF) have yielded impressive results for hyperspectral image. However, previous methods exist several drawbacks, i.e., marker selection methods are easily affected by boundary noise pixels, dissimilarity measure methods between pixels are inaccurate, and also image segmentation process is not robust, since they have not effectively utilized

  • Road network simplification for location-based services
    GeoInformatica (IF 1.317) Pub Date : 2020-05-01
    Abdeltawab Hendawi, John A. Stankovic, Ayman Taha, Shaker El-Sappagh, Amr A. Ahmadain, Mohamed Ali

    Road-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of memory and disks, and (b) reduces the I/O and communication overhead. There are several road network compression techniques proposed in the literature. These techniques

  • SST: Synchronized Spatial-Temporal Trajectory Similarity Search
    GeoInformatica (IF 1.317) Pub Date : 2020-04-28
    Peng Zhao, Weixiong Rao, Chengxi Zhang, Gong Su, Qi Zhang

    The volume of trajectory data has become tremendously large in recent years. How to effectively and efficiently search similar trajectories has become an important task. Firstly, to measure the similarity between a trajectory and a query, literature works compute spatial similarity and temporal similarity independently, and next sum the two weighted similarities. Thus, two trajectories with high spatial

  • A Framework for Group Converging Pattern Mining using Spatiotemporal Trajectories
    GeoInformatica (IF 1.317) Pub Date : 2020-04-25
    Bin Zhao, Xintao Liu, Jinping Jia, Genlin Ji, Shengxi Tan, Zhaoyuan Yu

    A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents

  • Top- k spatial distance joins
    GeoInformatica (IF 1.317) Pub Date : 2020-02-12
    Shuyao Qi, Panagiotis Bouros, Nikos Mamoulis

    Top-k joins have been extensively studied when numerical valued attributes are joined on an equality predicate. Other types of join attributes and predicates have received little to no attention. In this paper, we consider spatial objects that are assigned a score (e.g., a ranking). Give two collections R, S of such objects and a spatial distance threshold 𝜖, we introduce the top-k spatial distance

  • Mining Boundary Effects in Areally Referenced Spatial Data Using the Bayesian Information Criterion.
    GeoInformatica Pub Date : 2011-06-07
    Pei Li,Sudipto Banerjee,Alexander M McBean

    Statistical models for areal data are primarily used for smoothing maps revealing spatial trends. Subsequent interest often resides in the formal identification of 'boundaries' on the map. Here boundaries refer to 'difference boundaries', representing significant differences between adjacent regions. Recently, Lu and Carlin (2004) discussed a Bayesian framework to carry out edge detection employing

  • Local trend discovery on real-time microblogs with uncertain locations in tight memory environments
    GeoInformatica (IF 1.317) Pub Date : 2019-09-10
    Abdulaziz Almaslukh, Amr Magdy, Ahmed M. Aly, Mohamed F. Mokbel, Sameh Elnikety, Yuxiong He, Suman Nath, Walid G. Aref

    This paper presents GeoTrend+; a system approach to support scalable local trend discovery on recent microblogs, e.g., tweets, comments, online reviews, and check-ins, that come in real time. GeoTrend+ discovers top-k trending keywords in arbitrary spatial regions from recent microblogs that continuously arrive with high rates and a significant portion has uncertain geolocations. GeoTrend+ distinguishes

  • Online flu epidemiological deep modeling on disease contact network
    GeoInformatica (IF 1.317) Pub Date : 2019-07-25
    Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, Naren Ramakrishnan

    The surveillance and preventions of infectious disease epidemics such as influenza and Ebola are important and challenging issues. It is therefore crucial to characterize the disease progress and epidemics process efficiently and accurately. Computational epidemiology can model the progression of the disease and its underlying contact network, but as yet lacks the ability to process of real-time and

  • Crosstown traffic - supervised prediction of impact of planned special events on urban traffic
    GeoInformatica (IF 1.317) Pub Date : 2019-05-21
    Nicolas Tempelmeier, Stefan Dietze, Elena Demidova

    Large-scale planned special events in cities including concerts, football games and fairs can significantly impact urban mobility. The lack of reliable models for understanding and predicting mobility needs during urban events causes issues for mobility service users, providers as well as urban planners. In this article, we tackle the problem of building reliable supervised models for predicting the

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