{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T18:38:28Z","timestamp":1770489508906,"version":"3.49.0"},"reference-count":59,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,3]],"date-time":"2018-08-03T00:00:00Z","timestamp":1533254400000},"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":"<jats:p>Geographic data is growing in size and variety, which calls for big data management tools and analysis methods. To efficiently integrate information from high dimensional data, this paper explicitly proposes array-based modeling. A large portion of Earth observations and model simulations are naturally arrays once digitalized. This paper discusses the challenges in using arrays such as the discretization of continuous spatiotemporal phenomena, irregular dimensions, regridding, high-dimensional data analysis, and large-scale data management. We define categories and applications of typical array operations, compare their implementation in open-source software, and demonstrate dimension reduction and array regridding in study cases using Landsat and MODIS imagery. It turns out that arrays are a convenient data structure for representing and analysing many spatiotemporal phenomena. Although the array model simplifies data organization, array properties like the meaning of grid cell values are rarely being made explicit in practice.<\/jats:p>","DOI":"10.3390\/ijgi7080313","type":"journal-article","created":{"date-parts":[[2018,8,3]],"date-time":"2018-08-03T11:03:26Z","timestamp":1533294206000},"page":"313","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Multidimensional Arrays for Analysing Geoscientific Data"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6850-581X","authenticated-orcid":false,"given":"Meng","family":"Lu","sequence":"first","affiliation":[{"name":"Institute for Geoinformatics, University of Muenster, 48149 Muenster, Germany"},{"name":"Department of Physical Geography, Faculty of Geoscience, Utrecht University, 3584 CB Utrecht, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5281-3896","authenticated-orcid":false,"given":"Marius","family":"Appel","sequence":"additional","affiliation":[{"name":"Institute for Geoinformatics, University of Muenster, 48149 Muenster, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8049-7069","authenticated-orcid":false,"given":"Edzer","family":"Pebesma","sequence":"additional","affiliation":[{"name":"Institute for Geoinformatics, University of Muenster, 48149 Muenster, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1207\/s15427633scc0401_4","article-title":"Fields and objects in space, time, and space-time","volume":"4","author":"Galton","year":"2004","journal-title":"Spat. 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