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TitleModerate resolution time series data management and analysis: automated large area mosaicking and quality control
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AuthorLatifovic, R; Pouliot, D; Sun, L; Schwarz, J; Parkinson, W
SourceGeomatics Canada, Open File 6, 2015, 25 pages, https://doi.org/10.4095/296204 (Open Access)
Year2015
PublisherNatural Resources Canada
Documentopen file
Lang.English
Mediaon-line; digital
File formatpdf
ProvinceBritish Columbia; Alberta; Saskatchewan; Manitoba; Ontario; Quebec; New Brunswick; Nova Scotia; Prince Edward Island; Newfoundland and Labrador; Northwest Territories; Yukon; Nunavut
NTS1; 2; 3; 10; 11; 12; 13; 14; 15; 16; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 52; 53; 54; 55; 56; 57; 58; 59; 62; 63; 64; 65; 66; 67; 68; 69; 72; 73; 74; 75; 76; 77; 78; 79; 82; 83; 84; 85; 86; 87; 88; 89; 92; 93; 94; 95; 96; 97; 98; 99; 102; 103; 104; 105; 106; 107; 114O; 114P; 115; 116; 117; 120; 340; 560
Lat/Long WENS-141.0000 -50.0000 90.0000 41.7500
Subjectsgeophysics; environmental geology; remote sensing; landscape types; vegetation; data collections; models; modelling; Landsat; SPOT; land cover
Illustrationssatellite imagery; satellite images; tables; plots; flow charts; histograms
ProgramLand Surface Characterization, Remote Sensing Science
Released2015 04 01
AbstractThe Canada Centre for Remote Sensing1 (CCRS) maintains national-scale Long Term Satellite Data Records (LTSDRs) as an essential component of Earth Observation (EO) based land surface monitoring. The CCRS LTSDR framework provides long-term capability to generate, archive and provide access to value-added satellite data and thematic products addressing various land surface monitoring needs of the Government of Canada. For many years, coarse-resolution LTSDRs supported basic land-cover and landuse information needs over large areas. While these LTSDRs, with pixel sizes between 250m and 1000m, are important for ongoing long-term time series analysis, increasingly there is an opportunity to use greater spatial resolution data to more effectively address monitoring and assessment of both anthropogenic and natural land surface changes.
Until recently, cost and availability limited the usefulness of medium resolution (~30m pixel size) EO data for such analyses. Then, in 2009, the United States Geological Survey made Landsat data freely available. The potential for medium-resolution time series monitoring has been further strengthened by Landsat-8 and the pending launch of ESA's Sentinels. For this potential to be realized, new methods and algorithms are required to extract and analyse information from the medium resolution data, such as Landsat Time Series data, to monitor aspects of land surface dynamics. CCRS' new medium resolution LTSDR framework, the Time Series Data Management and Analysis System (TSDMAS), generates and manages value-added LTSDRs based on the TM, ETM and OLI sensors on board the Landsat 5, 7 and 8 missions, respectively. An overview of the TSDAMS system, and the algorithms implemented therein, will be presented.
A new value-added data product will also be presented: a Top of Atmosphere Reflectance Coverage of Canada, at 30 m spatial resolution. This circa 2010 product has been generated by the TSDAMS from data acquired by the TM and ETM sensors. Product generation, quality control, and characteristics of the underlying dataset will be described. By providing readily available, national-scale Landsat data products, of "research quality", CCRS TSDMAS harnesses the potential of medium resolution EO data, and can exponentially increase the downstream generation and use of medium resolution land surface information products. The new system and example data product which are described were designed to assist government agencies, the scientific community, natural resources managers and non-governmental groups engaged in land cover mapping, and the generation of geophysical and biophysical products for the assessment of surface dynamics at national and regional scales.
Summary(Plain Language Summary, not published)
An overview of the new framework, the Moderate Resolution Time Series Data Management and Analysis System (TSDMAS) for generating value-added data product based on TM, ETM+ and OLI sensors on board the Landsat 5, 7 and 8 missions. Specific focus is on the generation of a circa 2010 Top of Atmosphere Reflectance Coverage of Canada, at 30 m spatial resolution. Product generation, quality control, and characteristics of the underlying dataset are described.
GEOSCAN ID296204