The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Remote sensing big data computing: Challenges and opportunities
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MapReduce: simplified data processing on large clusters
Dean, J., & Ghemawat, S. (2008) · Communications of the ACM · doi:10.1145/1327452.1327492 · Cited by 18,476
A review of assessing the accuracy of classifications of remotely sensed data
Congalton, R. G. (1991) · Remote Sensing of Environment · doi:10.1016/0034-4257(91)90048-b · Cited by 7,724
Pregel: a system for large-scale graph processing
Malewicz, G., Austern, M. H., Bik, A. J. C., Dehnert, J. C., Horn, I., Leiser, N., & Czajkowski, G. (2010) · Proceedings of the 2010 ACM SIGMOD International Conference on Management of data · doi:10.1145/1807167.1807184 · Cited by 3,515
(2007) · doi:10.1145/1294261.1294281 · Cited by 3,447
Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
Philip Chen, C. L., & Zhang, C.-Y. (2014) · Information Sciences · doi:10.1016/j.ins.2014.01.015 · Cited by 3,047
Cassandra: a decentralized structured storage system
Lakshman, A., & Malik, P. (2010) · ACM SIGOPS Operating Systems Review · doi:10.1145/1773912.1773922 · Cited by 2,664
Bigtable: a distributed storage system for structured data
Chang, F. W., Dean, J. B., Ghemawat, S., Hsieh, W. C., Wallach, D. A., Burrows, M., Chandra, T., Fikes, A., & Gruber, R. E. (2006) · doi:10.5555/1298455.1298475 · Cited by 1,928
Recent advances in techniques for hyperspectral image processing
Plaza, A., Benediktsson, J. A., Boardman, J. W., Brazile, J., Bruzzone, L., Camps-Valls, G., Chanussot, J., Fauvel, M., Gamba, P., Gualtieri, A., et al. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2007.07.028 · Cited by 1,687
Web search for a planet: the google cluster architecture
Barroso, L. A., Dean, J., & Holzle, U. (2003) · IEEE Micro · doi:10.1109/mm.2003.1196112 · Cited by 1,025
Parallel Programmability and the Chapel Language
Chamberlain, B. L., Callahan, D., & Zima, H. P. (2007) · The International Journal of High Performance Computing Applications · doi:10.1177/1094342007078442 · Cited by 879
Cited by
Geospatial big data handling theory and methods: A review and research challenges
Li, S., Dragicevic, S., Castro, F. A., Sester, M., Winter, S., Coltekin, A., Pettit, C., Jiang, B., Haworth, J., Stein, A., et al. (2016) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2015.10.012 · Cited by 749
Ball, J. E., Anderson, D. T., & Chan, C. S. (2017) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.11.042609 · Cited by 746
Agricultural remote sensing big data: Management and applications
Huang, Y., CHEN, Z.-X., YU, T., HUANG, X.-Z., & GU, X.-F. (2018) · Journal of Integrative Agriculture · doi:10.1016/s2095-3119(17)61859-8 · Cited by 448
Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring
Hermosilla, T., Wulder, M. A., White, J. C., Coops, N. C., Hobart, G. W., & Campbell, L. B. (2016) · International Journal of Digital Earth · doi:10.1080/17538947.2016.1187673 · Cited by 293
Jakubik, J., Muszynski, M., Vössing, M., Kühl, N., & Brunschwiler, T. (2023) · IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium · doi:10.1109/igarss52108.2023.10282643 · Cited by 6
Metadata
- Authors
- Ma, Y., Wu, H., Wang, L., Huang, B., Ranjan, R., Zomaya, A., & Jie, W.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 51
- Pages
- 47-60
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2095483845
- Cited by
- 676
- References
- 35
- FWCI
- 57.54
- Type
- journal article
- Language
- en
- Open access
- green
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- Ma, Y., Wu, H., Wang, L., Huang, B., Ranjan, R., Zomaya, A., & Jie, W. (2015). Remote sensing big data computing: Challenges and opportunities. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2014.10.029
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
