CHS offers 500-metre bathymetric gridded data for users interested in the topography of the seafloor. This data provides seafloor depth in metres and is accessible for download as predefined areas.

An interpretation of bedrock geology, topography and other sources of information that shows the potential for karst formations. This is a reconnaissance level map for all of British Columbia

The Nova Scotia Hydrographic Network is an enhanced version of the Nova Scotia Topographic Database's Water Features theme. This dataset includes network spines for connectivity of water flow and various attribution for flow direction, priority of water flow and toponymic objects where applicable.

::: (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: :::

This feature delineates forest and vegetation stands in the Yukon at a scale of 1: 40 ,000. It is a management level forest inventory (as opposed to a n operational level) - meaning that analysis and mapping are most effective close to the 1:40,000 scale and not larger . This inventory has been completed in various stages : delineation from hardcopy black and white photographs took place from 1987 to 2002; while recent data collection has proceeded through a digital (aka 'softcopy') methodology of scanned photographs and digital elevation models.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)

Canada’s landmass is very diversified and comprises 7 distinctive areas called physiographic regions, each of which has its own unique topography and geology. Physiographic regions are large areas that share similar relief and landforms shaped by common geomorphic processes and geological history. Physiographic regions are often used to describe Canada’s geography to show regional differences in climate, vegetation, population and the economy.This dataset collection contains three interrelated datasets mapping the location of Canada’s 7 different physiographic regions, their 21 subregions and many divisions (landforms).

Five meter contour intervals derived from the Whitehorse Inventory data capture. The field work for the inventory was carried out during the winter of 2004/2005 with the project delivered by the contractor in October 2005. Delineation was based on 1:10,000 black and white photography acquired by the City of Whitehorse in 2001. Mapping and DTM were available for this project based on the 2001 photography.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 Yukon Geological Survey (YGS) has compiled over 195 surficial geology maps into a standardized GIS format, providing approximately 80% coverage of the territory. The maps range in scales from 1:250,000 to 1:10,000 with spatial overlap between scales. The original maps were produced by various agencies, including the Geological Survey of Canada, YGS, Yukon Government, universities, and the City of Whitehorse.All original feature descriptions have been preserved and also converted to standardized values using the Yukon terrain classification system. The compilation includes 4 GIS datasets and supporting documents available for download via [YGS integrated data system](https://data.geology.gov.yk.ca/Compilation/33) (YGSIDS) or GeoYukon. A .lyr file is [provided](https://data.geology.gov.yk.ca/Compilation/33) to symbolize feature classes and differentiate overlapping maps at different scales. Additionally, there is a surficial geology map index.The polygon attributes captured include surficial material, texture, age, surface expression, and geomorphological processes.Line features include geological contacts, glacial limits, glacial landforms (cirques, arêtes, eskers, meltwater channels, moraines), and non-glacial landforms (faults, lineaments, landslides, escarpments).Point features include field station, fossil and sample locations, glacial landforms (erratics, kames, kettles, drumlins, flutings), permafrost features (pingos, palsas, patterned ground, thermokarst depressions), and other non-glacial landforms (landslides, tors).The map index provides information on each map publication such as author, map title, map scale, publisher.These data are valuable for land-use applications in the territory, including: mineral and placer exploration, geotechnical engineering, infrastructure planning, granular resource assessments, permafrost modeling, agricultural assessments, forest management, and biophysical or ecological land classification.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 data shared are spatially explicit projections of wildfire burn probability across Canada’s forested ecozones under multiple future climate scenarios at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Four future climate scenarios were used to examine the spatiotemporal distribution of burn probability in the 21st century based on climate, vegetation, and topographic conditions ( Mulverhill et al. 2024). Projected burn probability is provided for four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and four future time periods, including 2021-2040, 2041-2060, 2061-2080, and 2081-2100, along with a baseline period representing average climate conditions and burn probability between 1991 and 2020. Outputs represent the probability that the conditions (climate, vegetation, topography) of a given pixel resemble those of historically burned areas. All non-climate variables were held static; therefore, projections represent burn probability under future climate scenarios given contemporary (2020) forest conditions. When using this dataset, please cite Mulverhill et al. (2025), as below.Mulverhill, C., Coops, N. C., Wulder, M. A., Hermosilla, T., White, J. C., & Bater, C. W. (2025). Projected Future Changes in Burn Probability in Canada’s Forests and Communities Under Different Climate Change Scenarios. Canadian Journal of Remote Sensing, 51(1). https://doi.org/10.1080/07038992.2025.2560347(Mulverhill et al. 2025).For a detailed description of the source data and methods applied to the baseline period to enable the Mulverhill et al. (2025) projections, see:Mulverhill, C., Coops, N.C., Wulder, M.A., White, J.C., Hermosilla, T., and Bater, C.W. 2024. “Multidecadal mapping of status and trends in annual burn probability over Canada’s forested ecosystems.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 209 pp. 279–295. https://doi.org/10.1016/j.isprsjprs.2024.02.006(Mulverhill et al. 2024).

40 Class - Canadian Ecological Domain Classification from Satellite Data. Satellite derived data including 1) topography, 2) landscape productivity based on photosynthetic activity, and 3) land cover were used as inputs to create an environmental regionalization of the over 10 million km2 of Canada’s terrestrial land base. The outcomes of this clustering consists of three main outputs. An initial clustering of 100 classes was generated using a two-stage multivariate classification process. Next, an agglomerative hierarchy using a log-likelihood distance measure was applied to create a 40 and then a 14 class regionalization, aimed to meaningfully group ecologically similar components of Canada's terrestrial landscape. For more information (including a graphical illustration of the cluster hierarchy) and to cite this data please use: Coops, N.C., Wulder, M.A., Iwanicka, D. 2009. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecological Informatics, Vol. 4, No. 1, Pp. 8-22, DOI: https://doi.org/10.1016/j.ecoinf.2008.09.005. ( Coops et al. 2009).