Cited by 749Geographic Information Systems StudiesBig Data Technologies and Applications3D Modeling in Geospatial Applications

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Geospatial big data handling theory and methods: A review and research challenges

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Li, Songnian, Dragicevic, Suzana, Castro, Francesc Antón, Sester, Monika, Winter, Stephan, Coltekin, Arzu, Pettit, Christopher, Jiang, Bin, Haworth, James, Stein, Alfred, Cheng, Tao·2016·ISPRS Journal of Photogrammetry and Remote Sensing

DOI 10.1016/j.isprsjprs.2015.10.012

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The Fractal Geometry of Nature
Mandelbrot, B. B., & WHEELER, J. A. (1983) · American Journal of Physics · doi:10.1119/1.13295 · Cited by 21,964
Mining association rules between sets of items in large databases
Agrawal, R., Imieliński, T., & Swami, A. (1993) · Proceedings of the 1993 ACM SIGMOD international conference on Management of data · doi:10.1145/170035.170072 · Cited by 14,907
Anomaly detection: A survey
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011) · Perspectives on Psychological Science · doi:10.1177/1745691610393980 · Cited by 9,996
Untitled work
(2011) · Cited by 5,203
Random forests for classification in ecology
Cutler, D. R., Edwards, T. C., Beard, K. H., Cutler, A., Hess, K. T., Gibson, J., & Lawler, J. J. (2007) · Ecology · doi:10.1890/07-0539.1 · Cited by 4,950
Citizens as sensors: the world of volunteered geography
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Big data: a revolution that will transform how we live, work, and think
(2013) · Choice Reviews Online · doi:10.5860/choice.50-6804 · Cited by 3,657
Big data: A survey
Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
How Nature Works
Bak, P. (1996) · Springer eBooks · doi:10.1007/978-1-4757-5426-1 · Cited by 2,830

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Research works printed but not linked: 10

Ackermann, F., 1994. Digital Elevation Models – Techniques and Applications, Quality Standards, Development. IAPRS, 30/4(Commission IV), pp. 421–432.
Dasgupta, 2013, Big data: the future is in analytics, Geospatial World
Dittrich, A., Lucas, C., 2013. A step towards real-time detection and localization of disaster events based on tweets. In: Proceedings of the 10th International Conference on Information Systems for Crisis Response and Management, pp. 868–872.
Kandwal, 2010, Geospatial analysis of HIV-related social stigma: a study of tested females across Indian mandals, Int. J. Health Geogr., 9
Mechveliani, S.D., 2001. Computer algebra with Haskell: applying functional-categorial-‘lazy’ programming. In: Proceedings of International Workshop CAAP-2001 (Dubna, Russia), pp. 203–211; <http://ca-d.jinr.ru/confs/CAAP/Final/proceedings/proceed.ps>.
Milewski, 2009, Lock options, DR DOBBS J., 34, 28
Pettit, C., Stimson, R., Nino-Ruiz, M., Moradini, L., Widjaja, I., Delaney, P., et al., 2014. Supporting Urban Informatics through a Big Data Analytics Online Workbench. NSF Workshop on Big Data and Urban Informatics.
Rajasekar, 2006, Image mining for modeling of forest fires from Meteosat images, IEEE Trans. Geosci. Remote Sensing, 45, 246
Ujang, 2014, 3D hilbert space filling curves in 3D city modeling for faster spatial queries, Int. J. 3-D Inform. Model. (IJ3DIM), 3
Wang, 2013, On spatial data mining under big data, J. China Acad. Electron. Inform. Technol., 8, 8

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Authors: Li, S., Dragicevic, S., Castro, F. A., Sester, M., Winter, S., Coltekin, A., Pettit, C., Jiang, B., Haworth, J., Stein, A., & Cheng, T.
Affiliations: Toronto Metropolitan University (CA)
Technical University of Denmark (DK)
Leibniz University Hannover (DE)
The University of Melbourne (AU)
UNSW Sydney (AU)
University of Gävle (SE)
University College London (GB)
University of Twente (NL)
Corresponding author: Li, Songnian
ORCID: Sester, Monika
Winter, Stephan
Pettit, Christopher
Jiang, Bin
Haworth, James
Stein, Alfred
Cheng, Tao
Venue: ISPRS Journal of Photogrammetry and Remote Sensing
Publisher: Elsevier BV
Published: 2016-05
Volume: 115
Pages: 119-133
ISSN: 0924-2716 (ISSN-L)
DOI: 10.1016/j.isprsjprs.2015.10.012
OpenAlex: W2344199778
Cited by: 749
References: 176
Citations by year: 2026: 42 · 2025: 59 · 2024: 49 · 2023: 52 · 2022: 55 · 2021: 87 · 2020: 102 · 2019: 100 · 2018: 89 · 2017: 79 · 2016: 35
FWCI: 354.25
Type: journal article
Language: en
Open access: green
arxiv.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
arXiv (Cornell University) (submittedVersion)
University of Twente Research Information (submittedVersion, other-oa)
UCL Discovery (University College London) (submittedVersion)
Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
University of Twente Research Information (submittedVersion)
arXiv (Cornell University)
Zurich Open Repository and Archive (University of Zurich)
Funders: NSERC
Topics: Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
Physical Sciences › Engineering › Building and Construction › 3D Modeling in Geospatial Applications
Keywords: geospatial big data, spatial data management, geospatial data storage, geoprocessing, geospatial data visualization, data quality checks, research challenges

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