This map service provides access to the Chronology dataset shown on the GeoAtlas application.**Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse. They are therefore identical and share the same refresh schedule. This dataset represents the chronology for the Province of Saskatchewan at 1:1 million scale. It is a regional distribution of bedrock categorized by age into Archean, Archean or Proterozoic, Proterozoic, Helikian, Ordovician, Silurian, Devonian, Cretaceous, and Tertiary for the province of Saskatchewan, Canada. Mapping in support of this dataset was over many years of compiling bedrock data and integrating into this product. The data was created as a file geodatabase feature class and output for public distribution.

This dataset compiles information and photographs collected at 49 observation stations during a field campaign conducted from July 31 to August 11, 2025, in the central part of the Kivalliq region. It includes the locations of sites where ice-flow indicators were measured, along with their relative chronology where it could be determined in the field.It also includes the locations of till sampling sites collected for geochemical and indicator mineral analyses, as well as sites where boulders and bedrock surfaces were sampled for terrestrial cosmogenic isotope dating.Analytical results and interpretations will be presented in subsequent publications.

Get data on fish stocking records from 1900 - 2012. This dataset is the most complete collection of historical fish stocking records available for the time period 1900 to 2012. It includes: * data source * species * rearing location * developmental stage * stock strain * spawning year * stocking date Related datasets: * [Ontario waterbody location identifer](https://data.ontario.ca/dataset/ontario-waterbody-location-identifier)

Polygons containing the date of capture of the Landsat images used to create the first version of the Baseline Thematic Mapping v1 (BTM1). This spatial view is only meaningful in conjunction with the satellite images or the BTM data derived from the satellite images. The images were captured from 1990 to 1997

Wildfire change year 1985-2022.Wildfire changes occurred from 1985 to 2022 displaying the year of greatest wildfire disturbance. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The information outcomes represent 38 years of wildfires in Canada's forests, derived from a single, consistent, spatially explicit data source in a fully automated manner. Time series of Landsat data with 30 m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2022 for Canada's 650-million-hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. https://doi.org/10.1080/17538947.2016.1187673 (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution, and time series change detection methods applied, as well as information on independent accuracy assessment of the data..Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., (2015). An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. https://doi.org/10.1016/j.rse.2014.11.005 (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., (2015). Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. https://doi.org/10.1016/j.rse.2015.09.004 (Hermosilla et al. 2015b).Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63,104-111. https://doi.org/10.1016/j.jag.2017.07.013 (Hermosilla et al. 2017).

Fire weather refers to weather conditions that are conducive to fire. These conditions determine the fire season, which is the period(s) of the year during which fires are likely to start, spread and do sufficient damage to warrant organized fire suppression.The length of fire season is the difference between the start- and end-of-fire-season dates. These are defined by the Canadian Forest Fire Weather Index (FWI; http://cwfis.cfs.nrcan.gc.ca/) start-up and end dates. Start-up occurs when the station has been snow-free for 3 consecutive days, with noon temperatures of at least 12°C. For stations that do not report significant snow cover during the winter (i.e., less than 10 cm or snow-free for 75% of the days in January and February), start-up occurs when the mean daily temperature has been 6°C or higher for 3 consecutive days. The fire season ends with the onset of winter, generally following 7 consecutive days of snow cover. If there are no snow data, shutdown occurs following 7 consecutive days with noon temperatures lower than or equal to 5°C.Historical climate conditions were derived from the 1981–2010 Canadian Climate Normals. Future projections were computed using two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: the fire season length across Canada for a reference period (1981-2010).

In this dataset, we share maps of annual dominant tree species (also known as leading tree species) from 1984-2022 covering the entirety of Canada's 650 Mha forested ecosystems using Landsat time-series imagery at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Classifications are based on regionally representative Random Forests model using local training samples from Canada's National Forest Inventory (Hermosilla et al., 2024). Descriptive metrics provide information on spectral, geographic, climatic, and topographic characteristics. Initial annual tree species classifications were subjected to a time series post-classification process using the forward-backward Hidden Markov Model to improve the temporal consistency of tree species transitions within the time series. Assessment of the annual species maps using independent validation data resulted in an overall accuracy of 86.1% ± 0.14% (95%-confidence interval). These data allow consistent comparison of trends and rates of change in tree species composition nationally and across regions using a common time frame, spatial resolution, and analytical approach.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Bater, C.W., Hobart, G.W., 2024. Characterizing long-term tree species dynamics in Canada's forested ecosystems using annual time series remote sensing data. Forest Ecology and Management, 122313. https://doi.org/10.1016/j.foreco.2024.122313 (Hermosilla et al. 2024)

This dataset represents the geochronological ages for selected Precambrian rocks in the province of Saskatchewan, Canada.This dataset represents the compilation of geochronological ages for selected Precambrian rocks in the province of Saskatchewan, Canada.  **Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse. They are therefore identical and share the same refresh schedule.

Harvest changes occurred from 1985 to 2022 displaying the year of greatest harvest disturbance. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The information outcomes represent 38 years of harvest activity in Canada's forests, derived from a single, consistent, spatially explicit data source in a fully automated manner. Time series of Landsat data with 30 m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by harvest for the period 1985-2022 for Canada's 650-million-hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. https://doi.org/10.1080/17538947.2016.1187673 ( Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution, and time series change detection methods applied, as well as information on independent accuracy assessment of the data.Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., (2015). An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. ( Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., (2015). Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. ( Hermosilla et al. 2015b).Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63,104-111. https://doi.org/10.1016/j.jag.2017.07.013 (Hermosilla et al. 2017)

The Historic treaties (formerly known as the Pre-1975 treaties) dataset contains geographic boundaries as well as basic attribute data representing signed treaties that were negotiated between Indigenous peoples and the Crown between 1725 and 1929. However, the Treaties of Peace and Neutrality, signed between 1701 and 1760, are not represented in this dataset because they do not have geographic boundaries that can be represented on a map. Apart from the Peace and Friendship Treaties, these boundaries represent the historic treaties signed after 1763, which provided large areas of First Nations land, to the Crown (transferring their Aboriginal title to the Crown) in exchange for reserve lands and other benefits. The Government of Canada recognizes 70 historic treaties in Canada signed between 1701 and 1923. These treaties include:• Treaties of Peace and Neutrality (1701-1760)• Peace and Friendship Treaties (1725-1779)• Upper Canada Land Surrenders and the Williams Treaties (1764-1862/1923)• Robinson Treaties and Douglas Treaties (1850-1854)• The Numbered Treaties (1871-1921)These boundaries are usually not surveyed but help to delineate the broad area described within the treaty. The boundaries are composed of the sum of specific geographies such as lakes, rivers, townships, mountains, administrative boundaries or height of land as mentioned in the treaties transcript. These boundaries are estimated based on written descriptions and should be used for informational and representational purposes only. If there is no geographic description included in the treaty, illustrative polygons may be used to represent locations where the signatory nations, as modern-day collectives, assert and/or exercise Section 35 rights. For more information about Historic treaties, visit https://www.rcaanc-cirnac.gc.ca/eng/1100100028574/1529354437231#chp3.The Historic treaties dataset is one of multiple datasets representing treaties and agreements between the Crown and Indigenous peoples. The Crown-Indigenous treaties and agreements geospatial datasets represent the geographic boundaries of the solemn agreements between the Crown and Indigenous peoples that set out promises, obligations and benefits for parties. The following datasets are also available: 1) The Modern treaties (formerly known as the Post-1975 treaties) dataset, which represents the areas of Canada where Indigenous land rights and title have not been addressed by preceding treaties or through other legal means.2) The Indigenous agreements dataset, which represents established protocols in place for consultation processes, self-government agreements, and other signed agreements between Indigenous groups and the Crown which do not fall into the aforementioned categories.The Historic treaties dataset is Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) and Indigenous Services Canada (ISC)’s primary source for Historic treaties geographic boundaries on maps.This dataset can also be viewed in the Aboriginal and Treaty Rights Information System (ATRIS). This web-based system provides access to information to inform governments, industry and other interested parties in determining their consultation obligations and in carrying out their consultation research. For more information, visit https://www.rcaanc-cirnac.gc.ca/eng/1100100014686/1609421785838.