Portions of Universal Transverse Mercator Zones 7 - 12 which cover British Columbia, Northern Hemisphere only, formed into polygons, in BC Albers projection

This record contains two datasets: 1. Raw unfiltered geographic coordinates and accuracy estimates of ringed seals tagged in the Western Canadian Arctic and 2. The location estimate from state-space models using a 12-hr time step. In total, 17 ringed seals were captured, measured, weighed, and tagged with satellite-linked transmitters (SDR-10, SDR-16, SPLASH) in June and July of 1999, 2000, and 2010. The tags, manufactured by Wildlife Computers Ltd. (Redmond, Washington, USA), sent data to polar orbiting satellites. Data were then retrieved via the Argos system (Harris et al., 1990). Tags collected and relayed information on movement (geographic positions) and diving data of the instrumented animals.

Land cover information is essential for a wide range of environmental applications, including climate impact assessment and adaptation, emergency response, and wildlife habitat monitoring. In Canada, a 2008 user survey identified that the most practical format for land cover data is a nationwide map with a 30 m spatial resolution, updated every five years. To meet this need, the Canada Centre for Remote Sensing (CCRS) has been producing 30 m resolution land cover maps since 2010, with updates released in 2015 and 2020. These datasets also serve as Canada’s contribution to the 30 m Land Cover Map of North America, developed collaboratively by government agencies in Mexico, the United States, and Canada through the North American Land Change Monitoring System (NALCMS). The classification system used in these maps is designed for consistency across North America. It follows a two-level hierarchy based on the Food and Agriculture Organization (FAO) Land Cover Classification System (LCCS), consisting of 12 classes at Level I and 19 classes at Level II. Of the 19 Level II classes, 15 are applicable to Canada and are included in the national land cover dataset. Tropical vegetation classes (specifically classes 3, 4, 7, and 9) are either absent or occur only minimally in Canada and are therefore excluded from the national dataset. Canada’s land cover maps are generated using observations from the Operational Land Imager (OLI) Landsat sensor. An accuracy assessment based on 832 randomly distributed samples indicates that the latest dataset achieves 86.9% overall accuracy, with no marked spatial inconsistencies.- [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)- [NALCMS — The North American Land Change Monitoring System](https://www.cec.org/publications/nalcms/)

Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as well as this 2015 land cover map. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2015 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Operational Land Imager (OLI) Landsat sensor. An accuracy assessment based on 806 randomly distributed samples shows that land cover data produced with this new approach has achieved 79.90% accuracy with no marked spatial disparities.- [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)

Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as the first of a planned series of maps to be updated every five years, or more frequently. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2010 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) Landsat sensors. An accuracy assessment based on 2811 randomly distributed samples shows that land cover data produced with this new approach has achieved 76.60% accuracy with no marked spatial disparities.- [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)

This layer is part of the Geological Survey of Canada's earthquake monitoring network. There are some blank fields toward the beginning of the listing, from the time the network was being installed and hence parameters were often unknown. Also, all depths in the table are "fixed" to a depth which is an integer multiple of 5km, according to lowest obtainable residuals and known crustal structure. The number and magnitude of located events are also dependent on the time recorded, as the magnitude threshold lowered as more stations were installed. The larger, potentially damaging earthquakes, however, were likely recorded from the inception of the network as these events produce waves which reach the entire western network.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)

A direction one looks from a viewpoint towards a visual landscape. When a view is panoramic, it is to the middle of that panoramic view

"KFN-WRFN Overlap Resolution Boundary" means the boundary which, for the purposes of Settlement Agreements, eliminates the KFN-WRFN Overlapping Area.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)

The Brier Island/Digby Neck area has been identified as an Ecologically and Biologically Significant Area (EBSA) by Fisheries and Oceans Canada and is one of four marine areas within the Bay of Fundy recognised by Parks Canada as of national significance for marine conservation planning. The area is representative of important outer Bay of Fundy features with significant marine mammal, bird, and benthic diversity including potentially important aggregations of sensitive benthic species such as horse mussel and sponge. Much of the information used for this recognition is now over 40 years old and should be re-validated using standardised georeferenced survey methods. As a first phase, a diver-based survey of the sublittoral habitats and associated species was conducted in August and September of 2017 for the Brier Island area. This report summarises the major sublittoral habitat types, species assemblages, and oceanographic conditions observed at 20 locations including Northwest and Southwest Ledges, Gull Rock, Peter’s Island, and Grand Passage. A total of 962 records were made of 178 taxa, consisting of 43 algae and 135 animals. Comparison with historical records largely confirmed the continued presence of unique habitats and species assemblages for which this area was initially recognised as an EBSA. Differences in species richness observed for cryptic and less known taxonomic groups such as sponges and bryozoans were attributable to changes in survey methods and knowledge. Based on these findings, additional surveys of inshore and offshore Brier Island using more quantitative methods developed for other Bay of Fundy EBSAs would further support regional MPA network planning and provide relative scales of species diversity and habitat coverage for this area.

All island polygons. Islands may overlap as there are islands within islands (e.g., a lake on an island contains an island). GNIS_NAME_1 contains the most atomic name for the island. For example, there are 3797 "Haida Gwaii" islands. If the island has not been named as part of a more specific group or with an individual name, "Haida Gwaii" is the GNIS_NAME_1 value. GNIS_NAME_2 and GNIS_NAME_3 values are null. If the island has a more specific name, "Haida Gwaii" moves to GNIS_NAME_2, and the more atomic name, such as "Moresby Island" is the GNIS_NAME_1. If the island has an individual name, belongs to a group, and is part of Haida Gwaii, the same logic of naming from most to least specific applies. For example, GNIS_NAME_1 = "George Island", GNIS_NAME_2 = "Copper Islands", GNIS_NAME_3 = "Haida Gwaii".