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.

The field plots were used to help during the photo interpretation process. The temporary plots provided essential information to interpreters to relate photo observed attributes with field measurements. 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 STAC API for NRCan's Earth Observation Database Management System (EODMS)..**This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

The documented occurrence data package contains 3 datasets that, in combination, help to provide generalized information about woodland caribou locations and survey areas in Saskatchewan. This information may assist users in their efforts to avoid or mitigate impacts to woodland caribou when operating in woodland caribou range. Generalized locations of caribou use have been provided to better reflect their large home ranges. Absence of a hexagon in an area should not be interpreted as absence of woodland caribou.Please read the Data Guide for important information about this product. Download survey boundaries, telemetry occurrence, and sightings/sign. Download the full package, including data guide here. The Woodland Caribou Documented Occurrence public data product is composed of three shapefiles/feature classes: 1. Woodland Caribou Occurrence - Sighting and Sign 2. Woodland Caribou Occurrence - Telemetry 3. Woodland Caribou Survey Boundaries The two occurrence datasets contain a grid of 18 sq km hexagons (tessellation). The inclusion of a hexagon in the dataset indicates that one or more animal sightings or sign, or telemetry points have been documented in that area. Importantly, lack of caribou occurrence (e.g. no hexagon) should not be interpreted as absence of woodland caribou. Rather, data may not have been collected in these areas or incidental or other observations have not been received.   The survey boundaries dataset displays the boundaries of woodland caribou surveys that were completed by or in collaboration with the Ministry of Environment from 2005 to 2024. Boundaries are from multiple sources, and include various types of surveys (fecal pellet collection or telemetry). These boundaries provide context when viewed alongside the woodland caribou occurrence datasets. We expect to see more occurrence locations in areas that have been surveyed. This information may provide context to areas with a seemingly higher number of occurrences.  For a full description of the data, please refer to the Data Guide document available for download on the Saskatchewan GeoHub.

Groundwater samples have been collected in the hydrogeological unit, for various types of analysis. The dataset is not used to represent a particular phenomenon or observation but rather as a utility dataset to add context and reference to groundwater analysis. It represents a general description of the sample site and sample. Sampling methods vary according to the types of analysis.

A cross-country summary of the averages and extremes for the month, including precipitation totals, max-min temperatures, and degree days. This data is available from stations that produce daily data.

Polygon geometry for an invasive species observation. The polygon represents the area of the observation. An observation of an invasive species can be either positive or negative. Positive indicates the species was present at the time of the observation. Negative indicates the species was not present at the time of the observation. Dataset currently only includes plant species.

The Fieldnotes dataset provides information about science field work to be conducted each year by Fisheries and Oceans Canada (DFO) and collaborators. Field work takes place in the Pacific, Arctic and Atlantic Oceans, as well as the freshwater bodies of participating DFO Regions: Pacific, Arctic, Ontario and Prairie, Maritimes, and Gulf.

Polygon feature layer of Manitoba's economic regionsThis feature layer depicts the boundaries of economic regions in Manitoba. There are eight regions in Manitoba, defined by Statistics Canada. Fields included [Alias (Field Name): Field description] Economic Region (Economic_Region): The name of the economic region For more information, see Regional Economic Profiles on the Manitoba  government  website.FF

Description:These commercial whale watching data are comprised of two datasets. First, the ‘whale_watching_trips_jun_sep_british_columbia’ data layer summarizes commercial whale watching trips that took place in 2019, 2020 and 2021 during the summer months (June to September). The second data layer, ‘wildlife_viewing_events_jun_sep_british_columbia’ contains estimated wildlife viewing events carried out by commercial whale watching vessels for the same years (2019, 2020 and 2021) and months (June to September). Commercial whale watching trips and wildlife viewing events are summarized using the same grid, and they can be related using the unique cell identifier field ‘cell_id’. The bulk of this work was carried out at University of Victoria and was funded by the Marine Environmental Observation, Prediction and Response (MEOPAR) Network under the ‘Whale watching AIS Vessel movement Evaluation’ or WAVE project (2018 – 2022). The aim of the WAVE project was to increase the understanding of whale watching activities in Canada’s Pacific region using vessel traffic data derived from AIS (Automatic Identification System). The work was finalized by DFO Science in the Pacific Region. These spatial data products of commercial whale watching operations can be used to inform Marine Spatial Planning, conservation planning activities, and threat assessments involving vessel activities in British Columbia.Methods:A list of commercial whale watching vessels based in British Columbia and Washington State and their corresponding MMSIs (Maritime Mobile Service Identity) was compiled from the whale watching companies and Marine Traffic (www.marinetraffic.com). This list was used to query cleaned CCG AIS data to extract AIS positions corresponding to commercial whale watching vessels. A commercial whale watching trip was defined as a set of consecutive AIS points belonging to the same vessel departing and ending in one of the previously identified whale watching home ports. A classification model (unsupervised Hidden Markov Model) using vessel speed as the main variable was developed to classify AIS vessel positions into wildlife-viewing and non wildlife viewing events. Commercial whale watching trips in the south and north-east of Vancouver Island were limited to a duration of minimum 1 hour and maximum 3.5 hours. For trips in the west coast of Vancouver island the maximum duration was set to 6 hours. Wildlife-viewing events duration was set to minimum of 10 minutes to a maximum of 1 hour duration. For more information on methodology, consult metadata pdf available with the Open Data record.References:Nesdoly, A. 2021. Modelling marine vessels engaged in wildlife-viewing behaviour using Automatic Identification Systems (AIS). Available from: https://dspace.library.uvic.ca/handle/1828/13300.Data Sources:Oceans Network Canada (ONC) provided encoded AIS data for years 2019, 2020 and 2021, within a bounding box including Vancouver Island and Puget Sound used to generate these products. This AIS data was in turn provided by the Canadian Coast Guard (CCG) via a licensing agreement between the CCG and ONC for the non-commercial use of CCG AIS Data. More information here: https://www.oceannetworks.ca/science/community-based-monitoring/marine-domain-awareness-program/ Molly Fraser provided marine mammal sightings data collected on board a whale watching vessels to develop wildlife-viewing events classification models. More information about this dataset here: https://www.sciencedirect.com/science/article/pii/S0308597X20306709?via%3DihubUncertainties:The main source of uncertainty is with the conversion of AIS point locations into track segments, specifically when the distance between positions is large (e.g., greater than 1000 meters).