Remote sensing big data computing: Challenges and opportunities
By Yan Ma, Haiping Wu, Lizhe Wang, Bormin Huang, R. Ranjan, Albert Y. Zomaya, W. Jie. Future generations computer systems, 2015
604 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/9dee8f8c93e14647124aaf6298aec6eb8f52b921
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In Computer Networks and Communications
In Information Systems
Citations in the corpus
- Big Data for Remote Sensing: Challenges and Opportunities (2016, background): “Due to the aforementioned heterogeneity and high dimensionality of big data in remote sensing, we also face important computational and statistical challenges related to processing scalability, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors [19], [20].”
- Agricultural remote sensing big data: Management and applications (2018, background): “Remote sensing data are a form of big data (Ma et al. 2015).”
- Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges (2015, background): “Similarly, there are efforts in organizing remotely sensed imagery (Ma et al. 2014, Marshall & Boshuizen 2013).”
- Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community (2017, background): “73 gigabytes of spacecraft borne observation data for active missions alone.(65) IBM reports that 2.”