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TitleAnalysis ready data specification for Canadian SAR data
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AuthorShort, N H; Charbonneau, F; Peiman, R; De Abreu, R
SourceGeomatics Canada, Open File 51, 2019, 65 pages, https://doi.org/10.4095/314818 (Open Access)
Year2019
PublisherNatural Resources Canada
Documentopen file
Lang.English
Mediaon-line; digital
File formatpdf (Adobe® Reader®)
Subjectsgeophysics; Science and Technology; remote sensing; satellite imagery; radar methods; radar imagery; Committee on Earth Observation Satellites (CEOS); geographic data; synthetic aperture radar; datasets; specifications; data availability; Analysis Ready Data; data processing; RADARSAT; RADARSAT-2; RADARSAT Constellation Mission; earth observation; data cube architecture; polarimetric data; covariance matrix; archival data
Illustrationstables; flow diagrams; satellite images; digital elevation models
ProgramInformation Extraction Procedures for Landmass Monitoring, Remote Sensing Science
Released2019 07 12
Abstract(Summary)
This report examines the current and upcoming Canadian satellite SAR mission data holdings and considers how best to make these data available for analysis in the new era of 'Big Data'. The report considers relevant international endeavours, the unique contribution that Canada may be able to make, and the practical steps necessary to bring a Canadian vision to fruition. Three Analysis Ready Data (ARD) options are presented and the interdependent issues of data cube computing environment choice are addressed.
Summary(Plain Language Summary, not published)
This report examines the current and upcoming Canadian satellite SAR mission data holdings and considers how best to make these data available for analysis in the new era of Big Data. The report considers relevant international endeavours, the unique contribution that Canada may be able to make, and the practical steps necessary to bring a Canadian vision to fruition. Three Analysis Ready Data (ARD) options are presented and the interdependent issues of data cube computing environment choice are addressed.
GEOSCAN ID314818