Casu, F. and Manunta, M. and Agram, P. S. and Crippen, R. E. (2017) Big Remotely Sensed Data: tools, applications and experiences. Remote Sensing of Environment, 202 . pp. 1-2. ISSN 0034-4257. https://resolver.caltech.edu/CaltechAUTHORS:20180104-155549103
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Abstract
The increased availability of large remote sensing datasets is generating heightened interest within the geoscience community, and more generally within human society. Indeed, remote sensing datasets that have commonly been analyzed as single scenes, or neighboring scenes, or temporally sequential scenes can now be analyzed en masse. This is due to the accumulation of large data volumes through time by increasing numbers of satellites, data access efficiencies due to technical advances and policy changes, and advances in hardware and software processing capabilities.
| Item Type: | Article | |||||||||
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| Additional Information: | © 2017 Elsevier. Received 30 July 2017, Accepted 14 September 2017, Available online 25 September 2017. | |||||||||
| Subject Keywords: | Big Data | |||||||||
| Record Number: | CaltechAUTHORS:20180104-155549103 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20180104-155549103 | |||||||||
| Official Citation: | F. Casu, M. Manunta, P.S. Agram, R.E. Crippen, Big Remotely Sensed Data: tools, applications and experiences, In Remote Sensing of Environment, Volume 202, 2017, Pages 1-2, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.09.013. (http://www.sciencedirect.com/science/article/pii/S003442571730425X) | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 84108 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | George Porter | |||||||||
| Deposited On: | 05 Jan 2018 00:01 | |||||||||
| Last Modified: | 03 Oct 2019 19:14 |
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