{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T19:15:08Z","timestamp":1740165308486,"version":"3.37.3"},"reference-count":9,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,11,23]],"date-time":"2019-11-23T00:00:00Z","timestamp":1574467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"The advent of new data collection technologies, such as LiDAR and drones, have made geospatial data available in large amounts and at low costs. While access to data is getting easier, geospatial tools have to evolve towards further automation and guarantee the reproducibility of the process and the quality of the results. As such, algorithms and data structures for handling geospatial data also need to be more and more robust and efficient to model complex, multidimensional geospatial phenomena in GISystems and provide higher levels of analysis. Articles in this special issue address two complementary aspects of the problem. They introduce new algorithms and data structures that allow for a more efficient handling of multidimensional data but also present complete processing chains dealing with the integration and the dissemination of multidimensional data.<\/jats:p>","DOI":"10.3390\/ijgi8120523","type":"journal-article","created":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T08:10:00Z","timestamp":1574669400000},"page":"523","source":"Crossref","is-referenced-by-count":1,"title":["Multidimensional and Multiscale GIS"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9507-3485","authenticated-orcid":false,"given":"Eric","family":"Guilbert","sequence":"first","affiliation":[{"name":"Department of Geomatics Sciences, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1914-9214","authenticated-orcid":false,"given":"Pawel","family":"Boguslawski","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering, Wroclaw University of Science and Technology, 50-421 Wroclaw, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2660-0106","authenticated-orcid":false,"given":"Umit","family":"Isikdag","sequence":"additional","affiliation":[{"name":"Department of Informatics, Mimar Sinan Fine Arts University, Istanbul 34427, Turkey"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Giovanella, A., Bradley, P.E., and Wursthorn, S. (2019). Evaluation of topological consistency in CityGML. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8060278"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Vitalis, S., Arroyo Ohori, K., and Stoter, J. (2019). Incorporating topological representation in 3D city models. ISPRS Int. J. Geo Inf., 8.","DOI":"10.20944\/preprints201905.0024.v1"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Feng, Y., Thiemann, F., and Sester, M. (2019). Learning cartographic building generalization with deep convolutional networks. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8060258"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Lafrance, F., Daniel, S., and Dragi\u0107evi\u0107, S. (2019). Multidimensional web GIS approach for citizen participation on urban evolution. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8060253"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Kulawiak, M., Kulawiak, M., and Lubniewski, Z. (2019). Integration, Processing and Dissemination of LiDAR Data in a 3D Web-GIS. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8030144"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"233","DOI":"10.3390\/ijgi8050233","article-title":"Obstacle-aware indoor pathfinding using point clouds","volume":"8","author":"Boguslawski","year":"2019","journal-title":"ISPRS Int. J. Geo Inf."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Lewandowicz, E., Lisowski, P., and Flisek, P. (2019). A Modified Methodology for Generating Indoor Navigation Models. ISPRS Int. J. Geo Inf., 8.","DOI":"10.20944\/preprints201901.0255.v1"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Maheshwari, N., Srivastava, S., and Rajan, K.S. (2019). Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8080333"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Wu, J., Fang, J., and Tian, J. (2019). Terrain Representation and Distinguishing Ability of Roughness Algorithms Based on DEM with Different Resolutions. ISPRS Int. J. Geo Inf., 8.","DOI":"10.3390\/ijgi8040180"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/12\/523\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,22]],"date-time":"2024-06-22T11:29:36Z","timestamp":1719055776000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/12\/523"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,23]]},"references-count":9,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["ijgi8120523"],"URL":"https:\/\/doi.org\/10.3390\/ijgi8120523","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2019,11,23]]}}}