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  • MDPI AG  (5)
  • Cartography and geographic base data  (5)
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  • MDPI AG  (5)
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  • Cartography and geographic base data  (5)
  • 1
    Online Resource
    Online Resource
    An OD Flow Clustering Method Based on Vector Constraints: A Case Study for Beijing Taxi Origin-Destination Data
    MDPI AG ; 2020
    In:  ISPRS International Journal of Geo-Information Vol. 9, No. 2 ( 2020-02-22), p. 128-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 9, No. 2 ( 2020-02-22), p. 128-
    Abstract: Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling relationship of urban subspace and dynamic causes. The existing flow clustering methods are limited by the spatial constraints of OD points, rely on the spatial similarity of geographical points, and lack in-depth analysis of high-dimensional flow characteristics, and therefore it is difficult to find irregular flow clusters. In this paper, we propose an OD flow clustering method based on vector constraints (ODFCVC), which defines OD flow event point and OD flow vector to express the spatial location relationship and geometric flow behavior characteristics of OD flow. First, the OD flow vector coordinate system is normalized by the Euclidean distance-based OD flow event point spatial clustering, and then the OD flow clusters with similar flow patterns are mined using adjusted cosine similarity-based OD flow vector feature clustering. The transformation of OD data from point set space to vector space is realized by constraining the vector coordinate system and vector similarity through two-step clustering, which simplifies the calculation of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. Due to the OD flow cluster property, the k-means algorithm is selected as the basic clustering logic in the two-step clustering method, and a sum of squared error perceptually important points algorithm considering silhouette coefficients (SSEPIP) is adopted to automatically extract the optimal cluster number without defining any parameters. Tested by origin-destination flow data in Beijing, China, new traffic flow communities based on traffic hubs are obtained by using the ODFCVC method, and irregular traffic flow clusters (including cluster mode, divergence mode, and convergence mode) with representative travel trends are found.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi9020128
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 2
    Online Resource
    Online Resource
    A Spatio-Temporal Flow Model of Urban Dockless Shared Bikes Based on Points of Interest Clustering
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 8 ( 2019-07-31), p. 345-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 8 ( 2019-07-31), p. 345-
    Abstract: With the advantages of convenient access and free parking, urban dockless shared bikes are favored by the public. However, the irregular flow of dockless shared bikes poses a challenge for the research of flow pattern. In this paper, the flow characteristics of dockless shared bikes are expounded through the analysis of the time series location data of ofo and mobike shared bikes in Beijing. Based on the analysis, a model called DestiFlow is proposed to describe the spatio-temporal flow of urban dockless shared bikes based on points of interest (POIs) clustering. The results show that the DestiFlow model can find the aggregation areas of dockless shared bikes and describe the structural characteristics of the flow network. Our model can not only predict the demand for dockless shared bikes, but also help to grasp the mobility characteristics of citizens and improve the urban traffic management system.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi8080345
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Examining the Association of Economic Development with Intercity Multimodal Transport Demand in China: A Focus on Spatial Autoregressive Analysis
    MDPI AG ; 2018
    In:  ISPRS International Journal of Geo-Information Vol. 7, No. 2 ( 2018-02-07), p. 56-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 7, No. 2 ( 2018-02-07), p. 56-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi7020056
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2655790-3
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  • 4
    Online Resource
    Online Resource
    Bibliometric Analysis of OGC Specifications between 1994 and 2020 Based on Web of Science (WoS)
    MDPI AG ; 2022
    In:  ISPRS International Journal of Geo-Information Vol. 11, No. 4 ( 2022-04-11), p. 251-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 11, No. 4 ( 2022-04-11), p. 251-
    Abstract: The Open Geospatial Consortium (OGC) is an international non-profit standards organization. Established in 1994, OGC aims to make geospatial information and services FAIR-Findable, Accessible, Interoperable, and Reusable. OGC specifications have greatly facilitated interoperability among software, hardware, data, and users in the GIS field. This study collected publications related to OGC specifications from the Web of Science (WoS database) between 1994 to 2020 and conducted a literature analysis using Derwent Data Analyzer and VosViewer, finding that OGC specifications have been widely applied in academic fields. The most productive organizations were Wuhan University and George Mason University; the most common keywords were interoperability, data, and web service. Since 2018, the emerging keywords that have attracted much attention from researchers were 3D city models, 3D modeling, and smart cities. To make geospatial data FAIR, the OGC specifications SWE and WMS served more for “Findable”, SWE contributed more to “Accessible”, WPS and WCS served more for “Interoperable”, and WPS, XML schemas, WFS, and WMS served more for “Reusable”. The OGC specification also serves data and web services for large-scale infrastructure such as the Digital Earth Platform of the Chinese Academy of Sciences.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi11040251
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 5
    Online Resource
    Online Resource
    Lossless Watermarking Algorithm for Geographic Point Cloud Data Based on Vertical Stability
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 7 ( 2023-07-21), p. 294-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 7 ( 2023-07-21), p. 294-
    Abstract: With the increasing demand for high-precision and difficult-to-obtain geospatial point cloud data copyright protection in military, scientific research, and other fields, research on lossless watermarking is receiving more and more attention. However, most of the current geospatial point cloud data watermarking algorithms embed copyright information by modifying vertex coordinate values, which not only damages the data accuracy and quality but may also cause incalculable losses to data users. To maintain data fidelity and protect its copyright, in this paper, we propose a lossless embedded watermarking algorithm based on vertical stability. First, the watermark information is generated based on the binary encoding of the copyright information and the code of the traceability information. Second, the watermark index is calculated based on the length of the watermark information after compression and the vertical distribution characteristics of the data. Finally, watermark embedding is completed by modifying the relative storage order of the corresponding data according to the index and watermark value. The experimental results show that the proposed algorithm has good invisibility without damaging the data accuracy. In addition, compared with existing algorithms, this method has a higher robustness under operations such as projection transformation, precision perturbation, and vertex deletion of geospatial point cloud data.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12070294
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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