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Titlebook: Volunteered Geographic Information; Interpretation, Visu Dirk Burghardt,Elena Demidova,Daniel A. Keim Book‘‘‘‘‘‘‘‘ 2024 The Editor(s) (if a

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发表于 2025-3-21 18:53:49 | 显示全部楼层 |阅读模式
书目名称Volunteered Geographic Information
副标题Interpretation, Visu
编辑Dirk Burghardt,Elena Demidova,Daniel A. Keim
视频video
概述This book is open access, which means that you have free and unlimited access.Discusses recent approaches to enhance the representation and analysis of Volunteered Geographic Information (VGI).Explore
图书封面Titlebook: Volunteered Geographic Information; Interpretation, Visu Dirk Burghardt,Elena Demidova,Daniel A. Keim Book‘‘‘‘‘‘‘‘ 2024 The Editor(s) (if a
描述This open access book includes methods for retrieval, semantic representation, and analysis of Volunteered Geographic Information (VGI), geovisualization and user interactions related to VGI, and discusses selected topics in active participation, social context, and privacy awareness. It presents the results of the DFG-funded priority program "VGI: Interpretation, Visualization, and Social Computing" (2016-2023)..The book includes three parts representing the principal research pillars within the program. Part I "Representation and Analysis of VGI" discusses recent approaches to enhance the representation and analysis of VGI. It includes semantic representation of VGI data in knowledge graphs; machine-learning approaches to VGI mining, completion, and enrichment as well as to the improvement of data quality and fitness for purpose. Part II "Geovisualization and User Interactions related to VGI" book explores geovisualizations and user interactions supporting the analysis and presentation of VGI data. When designing these visualizations and user interactions, the specific properties of VGI data, the knowledge and abilities of different target users, and technical viability of soluti
出版日期Book‘‘‘‘‘‘‘‘ 2024
关键词Open Access; Spatio-temporal Systems; Geographical Information Systems; Social Media Systems; Data Priva
版次1
doihttps://doi.org/10.1007/978-3-031-35374-1
isbn_softcover978-3-031-35376-5
isbn_ebook978-3-031-35374-1
copyrightThe Editor(s) (if applicable) and The Author(s) 2024
The information of publication is updating

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发表于 2025-3-21 20:43:08 | 显示全部楼层
https://doi.org/10.1007/978-3-031-35374-1Open Access; Spatio-temporal Systems; Geographical Information Systems; Social Media Systems; Data Priva
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Analyzing and Improving the Quality and Fitness for Purpose of OpenStreetMap as Labels in Remote Sentches (. km) in combination with deep learning approaches. The first approach was applied to 1000 randomly selected relevant OSM objects. The quality score for each OSM object in the samples was combined with a large set of intrinsic quality indicators (such as the experience of the mapper, the numb
发表于 2025-3-22 16:01:17 | 显示全部楼层
Uncertainty-Aware Enrichment of Animal Movement Trajectories by VGIincrease the number of available records in citizen science platforms. These works are an important foundation for a dynamic matching approach to jointly integrate geospatial trajectory data and user-generated geo-referenced content. Building on this work, we explore the joint visualization of traje
发表于 2025-3-22 17:03:13 | 显示全部楼层
Two Worlds in One Network: Fusing Deep Learning and Random Forests for Classification and Object Dett learn the decision boundaries of a random forest. The generated model is differentiable, can be used as a warm start for fine-tuning, and enables end-to-end optimization. Experiments on several real-world benchmark datasets demonstrate superior performance, especially when training with very few t
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Addressing Landmark Uncertainty in VGI-Based Maps: Approaches to Improve Orientation and Navigation ariations of the data quality in VGI-based maps, including spatial accuracy of landmark representations. In a series of experiments, we investigated and quantified to what extent spatial inaccuracies of landmark representations in VGI-based maps affect map matching. Based on the findings, we were ab
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