Automatic Scaling Hadoop in the Cloud for Efficient Process of Big Geospatial Data

Efficient processing of big geospatial data is crucial for tackling global and regional challenges such as climate change and natural disasters, but it is challenging not only due to the massive data volume but also due to the intrinsic complexity and high dimensions of the geospatial datasets. Whil...

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Bibliographic Details
Main Authors: Zhenlong Li, Chaowei Yang, Kai Liu, Fei Hu, Baoxuan Jin
Format: Article
Language:English
Published: MDPI AG 2016-09-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/5/10/173