Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2024.attributes:ID - Unique IDSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The High Resolution Digital Elevation Model (m) product The High Resolution Digital Elevation Model (HRDM) product is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east/vertical 2D decomposition is approximate and assumes constant viewing geometry and the absence of horizontal-north deformation.In the line-of-sight (LOS) map computed from ascending orbit data, a negative signal approximately corresponds to either subsidence or eastward motion, while a positive signal corresponds to uplift or westward motion. In the LOS map computed from descending orbit data, a negative signal approximately corresponds to either subsidence or westward motion, while a positive signal corresponds to uplift or eastward motion.In the horizontal-east map, a negative signal corresponds to westward motion, while a positive signal corresponds to eastward motion. In the vertical map, a negative signal indicates subsidence, while a positive signal indicates uplift.The maps were calculated from Sentinel-1 Synthetic Aperture Radar data collected between 2017 and 2024 during the snow-free season. Interferometric analysis of Sentinel-1 data was performed using GAMMA Software (https://www.gamma-rs.ch), and the long-term deformation rate was computed with the Multidimensional Small Baseline Subset (MSBAS) Software Version 10 (https://doi.org/10.1080/07038992.2024.2424753) at the Canada Centre for Mapping and Earth Observation, Natural Resources Canada.Long-wavelength signals caused by postglacial rebound and tectonic motion were filtered to enhance the visibility of small-scale deformation processes, such as those originating from landslides and mining. Field studies have confirmed only a few of these processes to date. The maps are expected to contain processing artifacts, which will be addressed in future work.References:Samsonov, S. V., & Feng, W. (2023). Deformation Retrievals for North America and Eurasia from Sentinel-1 DInSAR: Big Data Approach, Processing Methodology and Challenges. Canadian Journal of Remote Sensing, 49(1). https://doi.org/10.1080/07038992.2023.2247095Samsonov, S. V. (2024). Multidimensional Small Baseline Subset (MSBAS) Software for Constrained and Unconstrained Deformation Analysis of Partially Coherent DInSAR and Speckle Offset Data. Canadian Journal of Remote Sensing, 50(1). https://doi.org/10.1080/07038992.2024.2424753Limitation of Liability :The information contained on this website is provided on an “as is” basis and Natural Resources Canada makes no representations or warranties respecting the information, either expressed or implied, arising by law or otherwise, including but not limited to, effectiveness, completeness, accuracy or fitness for a particular purpose. Natural Resources Canada does not assume any liability in respect of any damage or loss based on the use of this website. In no event shall Natural Resources Canada be liable in any way for any direct, indirect, special, incidental, consequential, or other damages based on any use of this website or any other website to which this site is linked, including, without limitation, any lost profits or revenue or business interruption.

Forest Elevation(Ht) Mean 2015Mean 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 spatial layer displays Range Tenures (grazing and hay cutting licence and permits) administered by the Ministry of Forests, Lands and Natural Resource Operations. A Range Tenure is an area of Crown rangeland where a Range Act tenure applies. Tenure holders access a defined amount of forage through grazing (measured in Animal Unit Months) or hay (tonnage). Range Tenures apply only to Crown Land. In some cases, digital boundaries may overlap Private Land but these lands are not part of the Grazing area (as described in the legal description). Grazing may overlap waterbodies during drawdown (also described legally in the Tenure documents and where applicable, Range Use Plan). Livestock may graze islands and large bodies of water may act as Natural Range Barriers. March 3, 2023: Updates to the Range Tenure attribute table as described. Please contact Nancy.Elliot@gov.bc.ca if you have questions. To guide your use: 1. Layer contains RETIRED, PENDING, and ACTIVE Tenures (=Licenses and Permits); Select ACTIVE under attribute LIFE_CYCLE_STATUS_CODE to isolate all active tenures (status refers to spatial boundary status - therefore, a spatial boundary must be Retired in the Forest Tenure Administration system to have a status of retired); 2. Unique ID for Polygon is by RAN# in attribute FOREST_FILE_ID. Each tenure has own its RAN# (e.g. RAN07777). Multiple areas (polygons) belonging to the same tenure may have same RAN# with unique map block ids (e.g. RAN07777 A, RAN07777 B) 3. The field SUM_TENURE_ACTIVE_AREA_HA will provide, where LIFE_CYCLE_STATUS_CODE is ACTIVE, the total tenure area in Ha. For single block (polygon) tenures, this will be the same area as the polygon. Where there are multiple blocks, this will be the total sum area of all Active blocks. (Note this does not include PENDING or RETIRED tenure areas. Area is for Approved and Active Tenure boundaries. A block may be Approved but Pending, and therefore is not included). Review data for multipart vs multi polygons 4. AUTHORIZED_USE and TOTAL_ANNUAL_USE are for the entire Tenure; where there are multiple blocks, the total is over all blocks, seasonally distributed through different pastures 3. FILE_TYPE_CODE contains information on the type of Permit: • E01 - Grazing License • E02 - Grazing Permit • H01 - Haycutting License • H02 - Haycutting Permit 4. IF YOU ARE DOING SPATIAL ANALYSIS based on AREA --- Please note that tenures overlap either partially or wholly amongst tenure holders. One area may be shared by more than one Tenure holder and therefore there will be multiple congruent or partially overlapping polygons (multipart). If you want to do SPATIAL ANALYSIS based strictly on area, you must collapse or flatten the data using DISSOLVE so that the polygons are 1:1 with the land base (suggested approach)

Total soil moisture is the modelled amount of plant available water (mm) in the root zone of the soil. The value given is the amount calculated to be present on the modeled day of the product.Values are computed using the Versatile Soil Moisture Budget (VSMB)

Difference from Average Precipitation represents the accumulated precipitation value for a location, subtracted by the long-term average value. A negative value indicates that the location has received less than the normal amount of precipitation (mm) for that timeframe. A positive value indicates that the location has received more than the normal amount of precipitation (mm).Time periods calculated for difference from average precipitation are 1, 2, 3, 6, 9, 12, 18, 24 months.Long-term average is 1991-2020. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

Surveyed Condominium are Real Property Object representing the spatial extents of a condominium or apartment unit to which rights or interests can be registered. Condominium common areas are not included within this definition. Common areas are not spatially represented within the ICM Database. Condominium units must be associated to a Land Parcel.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 dataset contains the outputs for Bute Inlet from two simulations shown in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). The Finite Volume Community Ocean Model (FVCOM v4.1) was run with two different sets of initial conditions for the Discovery Islands region of British Columbia, Canada, from May 24 to June 27, 2019. The "Baseline" simulation used observed initial conditions, while the "Sensitivity" simulation removed the observed cold subsurface water mass from the initial profiles. Here in this dataset, we provide 29-day averages of the following variables in a transect along Bute Inlet: potential temperature, density, along-inlet velocity, and Brunt-Väisälä frequency (N^2). The averaging properly removes the tidal effects.

Surveyed Easement Boundaries consists of the lines required to form the boundaries of the Easements. COGO attributes are associated to the lines and depict the adjusted framework of the easement fabric.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)

::: (style="text-align:Left;")Footprints for all imagery in the Yukon Composite 150 cm Imagery Service. The Yukon Composite is a composite imagery basemap created from the most recent medium resolution SPOT-6/7 satellite images from the Government of Yukon satellite imagery repository.Distributed from GeoYukon by the Government of Yukon. Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: :::