A Caltech Library Service

Big Remotely Sensed Data: tools, applications and experiences

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. doi:10.1016/j.rse.2017.09.013.

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item:


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
Related URLs:
URLURL TypeDescription
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:
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, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84108
Deposited By: George Porter
Deposited On:05 Jan 2018 00:01
Last Modified:15 Nov 2021 20:16

Repository Staff Only: item control page