Geographic database containing the result of Statistics Canada's __2021 Census geography harmonization process__. Harmonization is a process of editing geographic boundaries in order to adjust them spatially to the official geographic base. This work was carried out in 2022 by the Institut de la Statistique du Québec (ISQ) according to the official provincial geographic base. A metadata sheet shows the process of harmonizing this geography. __The content of the resulting database is detailed there (page 2), as well as the description of the attributes in the appendix (pages 7 to 11) __. **This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Faults in the valleys near Ottawa could rupture and produce strong, shallow earthquakes. This magnitude 5.5 scenario visualizes the effects of such an event. It does not represent the most severe earthquake that could occur, but one that is more likely and could still cause damage.

This dataset includes White Sturgeon (Acipenser transmontanus) mark-recapture data collected in the Fraser River drainage. Users can use a Passive Integrated Responder (PIT) tag serial number to look up if the fish has been recaptured before and any associated data at last capture (e.g. fish length, girth, location, etc.). This dataset is maintained by the Reconciliation, Lands, Policy and Data Division within the Ministry of Water, Land and Resource Stewardship (WLRS). Data and information housed within the database is collected by both government biologists and partners such as First Nations, scientific fish collection permit holders, and participating fishery organizations. The [Fraser River drainage White Sturgeon PIT tag lookup app] (https://bcgov-env.shinyapps.io/sturgeon-pit-tag-lookup/) is also available as a tool to access this dataset.

Forest Elevation(Ht) Mean 2015 Mean height of lidar first returns (m). Represents the mean canopy height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018) Wulder et al. 2018) Geographic extent: Canada's forested ecosystems (~ 650 Mha) Time period: 1985–2011

This dataset makes it possible to locate a public library and its contact details.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

PURPOSE: To gather localized high-quality data for mapping eelgrass distribution in bays and estuaries in the Gulf Region of Atlantic Canada. DESCRIPTION: Between 2018 and 2023, a total of 48 coastal sites in New Brunswick (NB), Prince Edward Island (PE), and Nova Scotia (NS) have been fully processed for eelgrass presence/absence and depth information. An additional 18 sites from the same region and time period (2018–2023) have data collected but not yet fully processed for depth and eelgrass classification. These sites will be incorporated into the dataset as processing is completed. PARAMETERS COLLECTED: Geographic coordinates, timestamp, submerged aquatic vegetation presence. NOTES ON QUALITY CONTROL: BioSonics Visual Aquatic was used to process raw dt4 files by delineating the bottom and submerged aquatic vegetation (SAV) heights. Initial delineation of the estuary bottom was performed using an automated algorithm within the software, followed by manual adjustments to refine the delineation as needed. An algorithm was then used to delineate vegetation, which was edited visually by referring to written ground-truthing notes and underwater photos taken with a GoPro underwater camera with GPS capacity. Expert advice within DFO was used to advise the analysts on best practices and subtleties in the echograms. All efforts were made to ensure vegetation mapped was eelgrass, but in some cases, such as where the acoustic response was not clear or ground-truthing notes were lacking, it is possible that other types of SAV were included. The processed data were exported from BioSonics Visual Aquatic aggregating sets of 10 pings that were in very close proximity. Grouped pings with a vegetation canopy height >= 0.1 m were assigned an eelgrass presence (i.e., "EG_Presence") value of "Y", while grouped pings with a height < 0.1 m were assigned a presence value of "N". SAMPLING METHODS: Acoustic data were collected during the summer or early fall season (varies depending on the site) by the Southern Gulf of St. Lawrence Coalition on Sustainability (Coalition-SGSL) in partnership with Fisheries and Oceans Canada (DFO) Gulf Region. At some sites, the Province of New Brunswick's Department of Agriculture, Aquaculture and Fisheries (NBDAAF) also collected data using their boat. BioSonics MX Aquatic Habitat Echosounder units with a single beam (8.7°) 204.8kHz transducer (mounting height varied depending on the boat used) was used for data collection by all parties. Positioning was achieved using the BioSonics internal GPS through 2020, then subsequently an external GPS unit (Hemisphere S631 RTK GPS) was used to improve positioning from 1-2m accuracy to ~20cm when differential was obtained. BioSonics Visual Acquisition software was used to collect the data. USE LIMITATION: This product is provided as-is and has not been accuracy-assessed against other data. Since there were no transect-independent ground-truthing points surveyed, the accuracy of any interpolated surfaces created from this data cannot be known. Not for use without inclusion of full metadata. The data products are supplied "as they stand" and DFO does not guarantee the integrity, the completeness, or the accuracy. There were issues with the internal GPS of the BioSonics unit, and their impact on positional accuracy has yet to be determined. Beginning in 2021, an external, higher precision GPS unit was used to increase accuracy. Use of various boats and surveyors, as well as analysts, can introduce some inconsistencies in the data collection and analysis between sites and years. Site-specific characteristics such as mixed submerged aquatic vegetation can complicate mapping efforts. Shallow areas can also be challenging to delineate accurately since the bottom and/or the vegetation can extend higher than the mounted transducer. In these cases, a best estimate was used by the analyst. Weather conditions such as wind can affect the accuracy of the results, as the transponder may pitch and roll with the boat, while increased sediment in the water can interfere with the signal. Single-beam acoustic data has a very small focus footprint, which varies with depth, so it should not be considered a comprehensive bottom mapping tool. However, it does provide valuable point data that can indicate presence of vegetation, canopy height, relative depth, and ground-truthing for other mapping techniques (e.g. aerial or satellite imagery). For example, at 1 m depth, the 8.6 degree single-beam used for this work has a footprint of approximately 0.0177 square metres, and at 2 m depth that footprint becomes 0.0711 square metres.

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification. The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada. For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276 When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

This area has been identified as important for species movement. Analysis was completed on the natural heritage features of the fragmented areas of this region. This region has considerable development pressures in Ontario and New York State. Official GEO title: Algonquin to Adirondack (A2A) Landscape Analysis

Minimum residential density thresholds of the revised layout and development plan of the City of Laval.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

A spatial representation of the Map Blocks for Timber Licences after the elimination for that Map Block (if one exists) has been removed from the Map Block. Only active Map Blocks are included in this view