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A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation

International Journal of Digital Earth 2023年第1期16卷 1828-1852页

作者： Huafei Yu Tinghua Ai Min Yang Weiming Huang lars harrie School of Resource and Environmental Sciences Wuhan UniversityWuhanPeople’s Republic of China Department of Physical Geography and Ecosystem Science Lund UniversityLundSweden School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore

Similarity measurement has been a prevailing research topic geographic information science.Geometric similarity measurement inin scaling transformation(GSM_ST)is critical to ensure spatial data quality while balancing detailed information with distinctive features.However,GSM_ST is an uncertain problem due to subjective spatial cognition,global and local concerns,and geometric complexity.Traditional rule-based methods considering multiple consistent conditions require subjective adjustments to characteristics and weights,leading to poor robustness in addressing GSM_ST.This study proposes an unsupervised representation learning framework for automated GSM_ST,using a Graph Autoencoder Network(GAE)and drainage networks as an example.The framework involves constructing a drainage graph,designing the GAE architecture for GSM_ST,and using Cosine similarity to measure similarity based on the GAE-derived drainage embeddings in different scales.We perform extensive experiments and compare methods across 71 drainage networks duringfive scaling transformations.The results show that the proposed GAE method outperforms other methods with a satisfaction ratio of around 88%and has strong robustness.Moreover,our proposed method also can be applied to other scenarios,such as measuring similarity between geographical entities at different times and data from different datasets.

关键词： Geometric similarity measurement drainage network scaling transformation graph autoencoder network

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Real-time visualization of 3D city models at street-level based on visual saliency

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Science China Earth Sciences 2015年第3期58卷 448-461页

作者： MAO Bo BAN YiFang lars harrie Jiangsu Provincial Key Laboratory of E-Business Nanjing University of Finance and Economics College of Computer Science and Engineering Nanjing University of Science and Technology Department of Urban Planning and Environment KTH Royal Institute of TechnologySE-10044 StockholmSweden Department of Physical Geography and Ecosystem Science Lund UniversityBox118SE-223 62 LundSweden

Street-level visualization is an important application of 3D city models.Challenges to street-level visualization include the cluttering of buildings due to fine detail and visualization performance.In this paper,a novel method is proposed for streetlevel visualization based on visual saliency evaluation.The basic idea of the method is to preserve these salient buildings in a scene while removing those that are non-salient.The method can be divided into pre-processing procedures and real-time visualization.The first step in pre-processing is to convert 3D building models at higher Levels of Detail(Lo Ds) into LoD 1 models with simplified ground plans.Then,a number of index viewpoints are created along the streets; these indices refer to both the position and the direction of each street site.A visual saliency value is computed for each building,with respect to the index site,based on a visual difference between the original model and the generalized model.We calculate and evaluate three methods for visual saliency:local difference,global difference and minimum projection area.The real-time visualization process begins by mapping the observer to its closest indices.The street view is then generated based on the building information stored in those indexes.A user study shows that the local visual saliency method performs better than do the global visual saliency,area and image-based methods and that the framework proposed in this paper may improve the performance of 3D visualization.

关键词：三维城市模型实时可视化视觉街道 3D可视化投影面积建筑信息建筑物

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Towards knowledge-based geovisualisation using Semantic Web technologies:a knowledge representation approach coupling ontologies and rules

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International Journal of Digital Earth 2020年第9期13卷 976-997页

作者： Weiming Huang lars harrie Department of Physical Geography and Ecosystem Science Lund UniversityLundSweden

Geovisualisation is a knowledge-intensive art in which both providers and users need to possess a wide range of knowledge.Current syntactic approaches to presenting visualisation information lack semantics on the one hand,and on the other hand are too bespoke.Such limitations impede the transfer,interpretation,and reuse of the geovisualisation knowledge.In this paper,we propose a knowledge-based approach to formally represent geovisualisation knowledge in a semantically-enriched and machine-readable manner using Semantic Web technologies.Specifically,we represent knowledge regarding cartographic scale,data portrayal and geometry source,which are three key aspects of geovisualisation in the contemporary web mapping era,coupling ontologies and semantic rules.The knowledge base enables inference for deriving the corresponding geometries and portrayals for visualisation under different conditions.A prototype system is developed in which geospatial linked data are used as underlying data,and some geovisualisation knowledge is formalised into a knowledge base to visualise the data and provide rich semantics to users.The proposed approach can partially form the foundation for the vision of web of knowledge for geovisualisation.

关键词： Geovisuaisation Semantic Web knowledge representation ontologies semantic rules

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Matching authority and VGI road networks using an extended node-based matching algorithm

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Geo-Spatial Information Science 2015年第2期18卷 65-80页

作者： Ehsan ABDOLMAJIDI Ali MANSOURIAN Julian WILL lars harrie GIS Center Department of Physical Geography and Ecosystem ScienceLund UniversitySölvegatan 1222362 LundSweden

The amount of volunteered geographic information(VGI)has increased over the past decade,and several studies have been conducted to evaluate the quality of VGI data.In this study,we evaluate the completeness of the road network in the VGI data set OpenStreetMap(OSM).The evaluation is based on an accurate and efficient network-matching algorithm.The study begins with a comparison of the two main strategies for network matching:segment-based and nodebased matching.The comparison shows that the result quality is comparable for the two strategies,but the node-based result is considerably more computationally efficient.Therefore,we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components.Finally,we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database(NVDB)in Scania,Sweden.The case study reveals that OSM has a completeness of 87%in the urban areas and 69%in the rural areas of Scania.The accuracy of the matching process is approximately 95%.The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions.

关键词： geographic data volunteered geographic information(VGI) OpenStreetMap(OSM) node-based matching segment-based matching pattern detection Swedish National Road Database(NVDB)

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