Table of Contents Author Guidelines Submit a Manuscript
Journal of Sensors
Volume 2018, Article ID 2075057, 12 pages
https://doi.org/10.1155/2018/2075057
Research Article

Spark Sensing: A Cloud Computing Framework to Unfold Processing Efficiencies for Large and Multiscale Remotely Sensed Data, with Examples on Landsat 8 and MODIS Data

1Department of Computer Science and Engineering, Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA
2Center for Urban Science + Progress, New York University, Brooklyn, NY 11201, USA

Correspondence should be addressed to Hai Lan; ude.uyn@nal.iah

Received 26 April 2018; Accepted 8 July 2018; Published 23 August 2018

Academic Editor: Victor Mesev

Copyright © 2018 Hai Lan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Hai Lan, Xinshi Zheng, and Paul M. Torrens, “Spark Sensing: A Cloud Computing Framework to Unfold Processing Efficiencies for Large and Multiscale Remotely Sensed Data, with Examples on Landsat 8 and MODIS Data,” Journal of Sensors, vol. 2018, Article ID 2075057, 12 pages, 2018. https://doi.org/10.1155/2018/2075057.