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MODIS-Aqua Chlorophyll-a (Chl-a) was acquired from the NASA Ocean Biology Processing Group at processing Level-2 (version 2018), 1-km resolution, where Chl-a concentration was calculated using the OC3/OCI method. The months of January and December were excluded from this dataset, as data in the winter months at higher latitudes are missing due to low sun angle preventing acquisition. The pixels were aligned on a regular grid using the SeaDAS program, after which the monthly geometric mean value at all pixels was calculated for individual years. Finally, the geometric mean and geometric standard deviation factor of chlorophyll-a were calculated by month from …
MODIS-Aqua Chlorophyll-a (Chl-a) was acquired from the NASA Ocean Biology Processing Group where Chl-a concentration was calculated using the OC3/OCI method. The months of January and December were excluded from these datasets, as data in the winter months at higher latitudes are missing due to low sun angle preventing acquisition. The monthly geometric mean value at all pixels was calculated for individual years, then the geometric mean and geometric standard deviation factor of chlorophyll-a were calculated by month from these images. These methods of calculating mean and standard deviation were used due to the log-normal distribution of chlorophyll-a. The geometric …
MODIS-Aqua Chlorophyll-a (Chl-a) was acquired from the NASA Ocean Biology Processing Group at processing Level-3 (version 2018), 4-km resolution, where Chl-a concentration was calculated using the OC3/OCI method. The months of January and December were excluded from this dataset, as data in the winter months at higher latitudes are missing due to low sun angle preventing acquisition. The monthly geometric mean value at all pixels was calculated for individual years, then the geometric mean and geometric standard deviation factor of chlorophyll-a were calculated by month from these images. These methods of calculating mean and standard deviation were used due to …
The file contains one record for every offender serving a sentence of two years or more under Correctional Services of Canada (CSC) jurisdiction. The data were extracted from the Offender Management System (OMS) and reflects the status and attributes of offenders as of the year end.
Prospectivity model highlights areas of Canada with the greatest potential for clastic-dominated zinc deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.
Prospectivity model highlights areas of Canada with the greatest potential for magmatic nickel deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.
Prospectivity model highlights areas of Canada with the greatest potential for
Mississippi Valley-type zinc deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.
This GIS dataset depicts the surficial geology of the Cleardale area (NTS 84D/SW) (point features). The data are created in geodatabase format and output for public distribution in shapefile format.
All available bathymetry and related information for Dakin Lake were collected and hard copy maps digitized where necessary. The data were validated against more recent data (Shuttle Radar Topography Mission 'SRTM' imagery and Indian Remote Sensing 'IRS' imagery) and corrected where necessary. The published data set contains the lake bathymetry formatted as an Arc ascii grid. Bathymetric contours and the boundary polygon are available as shapefiles.
All available bathymetry and related information for Jack Fish Lake were collected and hard copy maps digitized where necessary. The data were validated against more recent data (Shuttle Radar Topography Mission 'SRTM' imagery and Indian Remote Sensing 'IRS' imagery) and corrected where necessary. The published data set contains the lake bathymetry formatted as an Arc ascii grid. Bathymetric contours and the boundary polygon are available as shapefiles.