A Functional Approach to Hyperspectral Image Analysis in the Cloud, Presented at the Winter 2018 ESIP Meeting
poster
posted on 2018-01-12, 16:43 authored by Anne Wilson, Doug Lindholm, Odele Coddington, Peter Pilewski, Tom Baltzer, Chris PankratzThe Hylatis project is building a tool set for hyperspectral image analysis in the cloud. Hyperspectral imagery is used across a broad range earth sciences.<div><br></div><div>In particular, we explore representing datasets as scientific domain agnostic, algebraic functions. Leveraging functional programming, this approach eases data interoperability problems, and provides ease of parallelization and proving code correctness.</div>
Funding
NASA ROSES AIST-16-0138
History
Usage metrics
Categories
- Applied computing not elsewhere classified
- Coding, information theory and compression
- Software engineering not elsewhere classified
- Inter-organisational, extra-organisational and global information systems
- Numerical computation and mathematical software
- Organisation of information and knowledge resources
- Distributed computing and systems software not elsewhere classified
- Astronomical instrumentation
- Climate change processes
- Climatology
- Other earth sciences not elsewhere classified
- Landscape ecology
- Environmental assessment and monitoring
- Ecosystem function
- Atmospheric sciences not elsewhere classified
Keywords
esip winter 2018Applied Computer ScienceCoding and Information TheoryComputer SoftwareInterorganisational Information Systems and Web ServicesMathematical SoftwareOrganisation of Information and Knowledge ResourcesWeb Technologies (excl. Web Search)Instrumentation, Techniques, and Astronomical ObservationsClimate Change ProcessesClimate ScienceEarth Sciences not elsewhere classifiedLandscape EcologyEnvironmental MonitoringEcosystem FunctionAtmospheric Sciences
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC