Geochronology is a discipline of geoscience which measures the age of earth materials and provides the temporal framework in which other geoscience data can be interpreted in the context of Earth history. This knowledge helps to answer questions such as when did a volcano last erupt, what is the rate of crustal uplift in a specific area, are rocks at one gold prospect the same age as those at another.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

This geodatabase includes hotspot maps of 1) nearshore habitat richness, 2) diversity (fish and invertebrates), and 3) biomass (using catch per unit effort of fish and invertebrates), as well as two layers showing the spatial extent of the diversity and biomass hotspot analyses. Full details and methods can be found in the Rubidge et al. 2018 CSAS Research Document 2018/053 available here or at https://waves-vagues.dfo-mpo.gc.ca/Library/40759842.pdf. These data were reviewed as part of a Canadian Science Advisory Secretariat (CSAS) regional peer review process on Nov 1-2, 2017.Habitat Richness Hotspots: Because there are no systematic surveys of nearshore species that span the entire coastline of Northern Shelf Bioregion, the nearshore habitat richness hotspots were developed as a proxy for species diversity in nearshore areas. Habitat richness was calculated from eight habitat features: eelgrass, surfgrass, canopy-forming kelp, estuaries, areas of high rugosity, and hard, mixed, and soft substrate. The number of features within 1 km x 1 km planning units was counted, and hotspots were identified using the Getis-Ord G* tool in ArcGIS. Planning units with Gi_Bin values of 3 (99% confidence) were classified as habitat richness hotspots.Diversity and Biomass Hotspots: Hotspots of fish and invertebrate diversity and biomass were developed as proxies for spatial patterns of productivity in the Northern Shelf Bioregion. Diversity (Shannon diversity) and biomass (kg/hour or count/hook/hour) were calculated from DFO synoptic trawl and outside hard-bottom longline (HBLL) survey catch records. The outside HBLL survey was previously referred to as Pacific Halibut Management Area (PHMA) survey. The synoptic trawl and HBLL surveys have complementary spatial coverage, with the HBLL surveys occurring in more coastal areas (20–260 m) and the synoptic trawl surveys occurring on deeper shelf areas (50–1300 m). Hotspots were identified using the Getis-Ord G* tool in ArcGIS for five separate analyses: fish biomass (trawl), fish diversity (trawl), fish diversity (longline), invertebrate biomass (trawl), and invertebrate diversity (trawl). Using the Minimum Bounding Geometry Tool, convex hull polygons were drawn around groups of hotspot points (Gi_Bin values of 1, 2, or 3; confidence ≥90%) containing 10 or more points. The resulting polygons were then buffered by 1 km and manually edited where needed to exclude any large areas of the polygons that did not include hotspot points.

GEO - Geological and geophysical (geoscientificInformation)The earth sciences. For example, resources describing geophysical features and processes; minerals; the composition, structure, and origin of the earths rocks; earthquakes; volcanic activity; landslides; gravity information; soils; permafrost; hydrogeology; and erosion

This is a spatial layer showing Ministry of Forests Radio Communication Sites. Communication Sites are physical land locations containing structures and equipment which provide two or one-way voice and or data wireless communications to field staff or for operational activities

Geotechnical reports are indexed within a database maintained by HPW-TEB Geotechnical Unit. Meta data associated to each geotechnical report are captured within this indexing table, including report reference number, title, author, highway and km start and end. The table has been modified to include columns that aid in georeferencing geotechnical reports. Added columns include route ID, Latitude, and Longitude.Transportation Engineering Branch is continually improving its geographical information systems with a major focus on creating linear referencing routes within ArcGIS. Georeferencing geotechnical reports will utilize the linear referencing routes in creating points and line shape files by referencing the highway number and km points or ranges as defined within the indexing table.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

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.

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.

A predictive model for Canadian carbonatite-hosted REE ± Nb deposits is presented herein. This model was developed by integrating diverse data layers derived from geophysical, geochronological, and geological sources. These layers represent the key components of carbonatite-hosted REE ± Nb mineral systems, including the source, transport mechanisms, geological traps, and preservation processes. Deep learning algorithms were employed to integrate these layers into a comprehensive predictive framework. Here is a link to the publication that describes this product: https://link.springer.com/article/10.1007/s11053-024-10369-7

The Canada Geological Map Compilation (CGMC) is a database of previously published bedrock geological maps sourced from provincial, territorial, and other geological survey organizations. The geoscientific information included within these source geological maps wasstandardized, translated to English, and combined to provide complete coverage of Canada and support a range of down-stream machine learning applications. Detailed lithological, mineralogical, metamorphic, lithostratigraphic, and lithodemic information was not previously available as onenational-scale product. The source map data was also enhanced by correcting geometry errors and through the application of a new hierarchical generalized lithology classification scheme to subdivide the original rocks types into 35 classes. Each generalized lithology is associated with asemi-quantitative measure of classification uncertainty. Lithostratigraphic and lithodemic names included within the source maps were matched with the Lexicon of Canadian Geological Names (Weblex) wherever possible and natural language processing was used to transform all of the available text-basedinformation into word tokens. Overlapping map polygons and boundary artifacts across political boundaries were not addressed as part of this study. As a result, the CGMC is a patchwork of overlapping bedrock geological maps with varying scale (1:30,000-1:5,000,000), publication year (1996-2023), andreliability. Preferred geological and geochronological maps of Canada are presented as geospatial rasters based on the best available geoscientific information extracted from these overlapping polygons for each map pixel. New higher resolution geological maps will be added over time to fill datagaps and to update geoscientific information for future applications of the CGMC.