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Spatial Generalization and Aggregation of Massive Movement Data

Natalia Adrienko, Gennady Adrienko
2011 IEEE Transactions on Visualization and Computer Graphics  
We suggest a method for spatial generalization and aggregation of movement data, which transforms trajectories into aggregate flows between areas. It is assumed that no predefined areas are given.  ...  We introduce local and global numeric measures of the quality of the generalization, and suggest an approach to improve the quality in selected parts of the territory where this is deemed necessary.  ...  CONCLUSION We have described an approach to spatial generalization and aggregation of movement data.  ... 
doi:10.1109/tvcg.2010.44 pmid:21149876 fatcat:m4mikokmczfshbgonx5wysniq4

A Comparison of Spatial Generalization Algorithms for LBS Privacy Preservation

Sergio Mascetti, Claudio Bettini
2007 2007 International Conference on Mobile Data Management  
Spatial generalization has been recently proposed as a technique for the anonymization of requests in location based services.  ...  This paper presents the results of an extensive experimental study, considering known generalization algorithms as well as new ones proposed by the authors.  ...  We would like to thank Dario Freni for his excellent programming job in the set-up of the experiments, and the reviewers for their helpful comments.  ... 
doi:10.1109/mdm.2007.54 dblp:conf/mdm/MascettiB07 fatcat:lgw7d64btbcb5jwcaqaotqjgim

A QTM-based Algorithm for Generation of the Voronoi Diagram on a Sphere [chapter]

Xuesheng Zhao, Jun Chen, Zhilin Li
2002 Advances in Spatial Data Handling  
To efficiently store and analyse spatial data at a global scale, the digital expression of the Earth's data must be global, continuous and conjugate, i.e., a spherical dynamic data model is needed.  ...  The complexity of the Voronoi algorithms for line and area data sets in a vector-based context limits its application in dynamic GISs.  ...  The Principle of Generating the Voronoi Diagram on a Sphere in QTM The Algorithm for generating the Voronoi diagram on a spherical surface is based on the principle of dilation operation in mathematical  ... 
doi:10.1007/978-3-642-56094-1_20 fatcat:4ra535ubifcprbbchdycfplqwy

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

Weiming Huang, Syed Amir Raza, Oleg Mirzov, Lars Harrie
2019 ISPRS International Journal of Geo-Information  
The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects.  ...  Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs).  ...  Funding: The work was supported by Lund University and China Scholarship Council. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi8070310 fatcat:dczpbeeyhndbboxr2lxuhojj6m

High-fidelity reconstruction of turbulent flow from spatially limited data using enhanced super-resolution generative adversarial network [article]

Mustafa Z. Yousif, Linqi Yu, HeeChang Lim
2021 arXiv   pre-print
The instantaneous and statistical results obtained from the model agree well with the ground truth data, indicating that the model can successfully learn to map the coarse flow fields to the high-resolution  ...  The model capability to reconstruct high-resolution laminar flows is examined using data of laminar flow around a square cylinder.  ...  with similar spatial and temporal accuracy as that of the DNS data.  ... 
arXiv:2109.04250v2 fatcat:v6ombdpu65cq7gbezrzjd2dg6e


H. Latifi, B. Koch
2012 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The applied methods show positive potential towards producing spatial models of forest structure.  ...  Models were built using information from airborne optical and LiDAR data across two adjacent forest sites using the remote sensing data collected by a similar instrument.  ...  We thank the Forest Service of BW for providing the required forest inventory data.  ... 
doi:10.5194/isprsarchives-xxxviii-4-w19-173-2011 fatcat:6ix5ug2hmfh7xpwxuq3kgesggm

Learning to Generate Descriptions of Visual Data Anchored in Spatial Relations

Adrian Muscat, Anja Belz
2017 IEEE Computational Intelligence Magazine  
We describe the data we have created, and compare a range of machine learning methods in terms of the success with which they learn the mapping from features to spatial relations, using automatic and human-assessed  ...  The task we address in this paper is the automatic generation of image descriptions that are anchored in spatial relations.  ...  Krahmer and van Deemter observe that if relations are important and frequently used, then this may call into question the validity of the incremental generation algorithm, perhaps the most influential  ... 
doi:10.1109/mci.2017.2708559 fatcat:lzqsen7l2ndrnfgvl7vd5arl4a

Spatial data modeling by means of Gibbs Markov random fields based on a generalized planar rotator model [article]

Milan Žukovič, Dionissios T. Hristopulos
2022 arXiv   pre-print
We introduce a Gibbs Markov random field for spatial data on Cartesian grids which is based on the generalized planar rotator (GPR) model.  ...  The GPR model generalizes the recently proposed modified planar rotator (MPR) model by including in the Hamiltonian additional terms that better capture realistic features of spatial data, such as smoothness  ...  Spatial data on regular grids are often modeled by means of Gaussian Markov random fields (MRF) [23] , which are based on the principles of conditional independence and the imposition of spatial correlations  ... 
arXiv:2201.02537v1 fatcat:d2glhovcdvgrlmvisysvkmnel4


W. Lu, J. Zhang, G. Xue, C. Wang
2018 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
is adopted to remove the gross errors and the threshold is selected according to the coherence of the interferometry.  ...  First of all, when the DSM is generated by interferometry, unavoidable factors such as overlay and shadow will produce gross errors to affect the data accuracy, so the adaptive threshold segmentation method  ...  The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3, 2018 ISPRS TC III Mid-term Symposium "Developments, Technologies and Applications in Remote  ... 
doi:10.5194/isprs-archives-xlii-3-1203-2018 fatcat:zn4kx76rrfd2dmbpo6kcgqyh2y


H. C. Oliveira, M. Galo
2013 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W1, ISPRS Hannover Workshop  ...  Considering this context, the aim of this article is to introduce an alternative procedure for occlusion detection in aerial images, using LiDAR (Light Detection And Ranging) data, aiming at the generation  ...  of data used in this work.  ... 
doi:10.5194/isprsarchives-xl-1-w1-275-2013 fatcat:ivectllprfdslintlu4ai6xska


U. G. Sefercik, I. Dana
2012 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
For DEM generation, a part of Istanbul (historical peninsula and near surroundings) was selected as the test field because of data availability.  ...  The quality of the data set and used software package come into prominence for the stability of the generated DEM.  ...  The TerraSAR-X images were acquired in the framework of the general proposal "Evaluation of DEM derived from TerraSAR-X data" (ID LAN_0634), submitted to DLR in 2009.  ... 
doi:10.5194/isprsarchives-xxxviii-4-w19-289-2011 fatcat:4byzepmp2zb6vco34ik2vkdhoq


U. Bacher
2021 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Special attention is paid to the hybrid orientation of the data and the integrated generation of base and enhanced products.  ...  The process of data acquisition is discussed and strategies for hybrid urban mapping are proposed. A hybrid sensor alone is just a part of the whole procedure to generate 3D content.  ...  A selection of the possibilities will be presented here in Table 4 .  ... 
doi:10.5194/isprs-archives-xliii-b2-2021-297-2021 fatcat:cn5k5osu4bcu5ndlkvza3nm2nu


T. Horanont, M. Basa, R. Shibasaki
2012 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
a principle for communication and allow users to visualize spatial information online.  ...  DATA INPUT AND CLASSIFICATION SCHEMES Data Input Automated cartographic interpretation of generic data requires an intelligent spatial data discovery and integration of geographic information system  ... 
doi:10.5194/isprsannals-i-4-147-2012 fatcat:lrbba74qxbcsdnixt4b3wm3fae

Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling

Mateusz Ciski, Krzysztof Rząsa, Marek Ogryzek
2019 Sustainability  
Thus, various map content generalizations were analyzed in the article; the main goal was to find the level for which the data with an acceptable loss of accuracy can be generalized.  ...  To analyze the various forms of spatial management inscribed into sustainable development, information on the location of objects and their concentration at specific areas is necessary.  ...  Acknowledgments: Authors would like to thank the National Heritage Board of Poland, for sharing data on non-movable monuments in Poland.  ... 
doi:10.3390/su11205616 fatcat:flddpgovinhodmig2ua4zhrjbi

Generation of Synthetic Spatially Embedded Power Grid Networks [article]

Saleh Soltan, Gil Zussman
2015 arXiv   pre-print
The algorithm uses the Gaussian Mixture Model (GMM) for density estimation of the node positions and generates a set of nodes with similar spatial distribution to the nodes in a given network.  ...  Therefore, we study the structural properties of the North American grids and present an algorithm for generating synthetic spatially embedded networks with similar properties to a given grid.  ...  Algorithm 1: Geographical Network Learner and Generator (GNLG) Input: G, {p i } n i=1 , and parameters κ, α, β, γ > 0 and N ∈ N. 1: Generate a set of nodes with similar spatial distribution to the nodes  ... 
arXiv:1508.04447v1 fatcat:5rshqbdyurcsfah2u6w6m3twye
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