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We have found 258 datasets for the keyword "samplingevent". You can continue exploring the search results in the list below.
Datasets: 105,253
Contributors: 42
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258 Datasets, Page 1 of 26
MBON Pole to Pole: Sandy beach biodiversity of southwest New Brunswick, Canada
The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on sandy beaches of the Musquash Harbour, Mispec Bay, and New River Beach, New Brunswick, Canada, using the MBON P2P sampling protocol for sandy beaches, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Jonah L (2025). MBON POLE TO POLE: SANDY BEACH BIODIVERSITY OF SOUTHWEST NEW BRUNSWICK, CANADA. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=sandybeachesbayoffundynb&v=1.7
Standardized Precipitation Evapotranspiration Index (SPEI)
The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment.Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.
Forecasted Basin-Average Accumulated Precipitation - GEPS 384 hrs
Shows sub-basin-averaged precipitation from the GEPS ensemble, reflecting the mean (or other metrics) of multiple ensemble members. Useful to understand probabilistic rainfall/snowfall expectations for each watershed.GEPS is ECCC’s ensemble system, running ~20 members globally to quantify forecast uncertainty out to ~16 days. This layer aggregates ensemble precipitation data over sub-basin polygons. The attribute “Average Accumulated Precipitation” often represents the ensemble mean, capturing a more probable average scenario. Operators can use this for risk-based hydrological planning or to gauge confidence in upcoming flood/drought scenarios across different sub-basins.
The MPMO Project Inventory - August, 2019 Snapshot
This dataset includes all MPMO projects at various stages in the review process, including those that are currently undergoing review and those that have completed a review.
Air quality – Peak fine particulate matter concentrations at monitoring stations
The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Air quality indicators track ambient concentrations of fine particulate matter, ground-level ozone, sulphur dioxide, nitrogen dioxide and volatile organic compounds at the national, regional and urban area levels and at local monitoring stations. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated.Canadian Environmental Sustainability Indicators: https://www.canada.ca/environmental-indicators
Homogenized Surface Pressure (AHCCD)
The Homogenized Surface Pressure data consist of monthly, seasonal and annual means of hourly sea level and station pressure (hectopascals) for 626 locations in Canada. Homogenized climate data incorporate adjustments (derived from statistical procedures) to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The time periods of the data vary by location, with the oldest data available from 1953 at some stations to the most recent update in 2014. Data availability over most of the Canadian Arctic is restricted to 1953 to present. The data will continue to be updated every few years (as time permits).
Trends of precipitation change based on adjusted and homogenized climate station data
Monthly, seasonal and annual trends of total precipitation change (millimetres) based on adjusted station data (AHCCD) are available. Trends are calculated using the Theil-Sen method using the station’s full period of available data. The availability of precipitation trends will vary by station; if more than 5 consecutive years are missing data or more than 10% of the data within the time series is missing, a trend was not calculated.
Discharge Cases (Spills) Historic
This tabular data contains environmental discharges (spills) in Saskatchewan with limited information outlining best known location, confirmed substance and quantity. This data is limited to events that occurred before January 1, 2015. Information is not always complete, please contact the Ministry of Environment for further details.The Ministry of Environment's Environmental Protection Branch (EPB) is responsible for responding to incidents where a substance has been discharged into the environment. Under The Environmental Management and Protection Act 2010 (EMPA, 2010), “discharge” means a discharge, drainage, deposit, release or emission into the environment. These records include locations and details of discharge incidents in the Province of Saskatchewan and are currently limited to incidents that were reported to the ministry prior to January 2015. The Discharge Date is when the Ministry created the record. This is not necessarily the date of the discharge event. We will continue to improve the quality of the information in the table. As it is validated it will move to the map format, consequently you may notice changes from the table to map format. Information related to discharges after Janurary 2015 to present are currently found at: https://geohub.saskatchewan.ca/datasets/saskatchewan::discharge-cases-spills/about For further information, please contact the Ministry of Environment Inquiry Centre (Toll Free): 800-567-4224, email: centre.inquiry@gov.sk.ca or visit: Hazardous Spills Reporting.
Historical trace metals concentrations from sediment samples and suspended particulate matter (SPM) samples, 1976 - 1987
This dataset is a compilation of numerous data files recovered as part of a data request in 2024 from a historical archive of DFO research data. Sediment and Suspended Particulate Matter (SPM) samples were collected over more than a decade as part of Dr. Douglas Loring’s research program while working at the Bedford Institute of Oceanography (BIO). Samples were collected as part of individual and collaborative research projects, and links to the relevant primary science publications and reports are included in the data in an effort to provide context to the data, as well as describe the field and laboratory techniques used to generate the attached data.
Canada's surface water frequency
Data represents surface water occurrence frequency (percentage), which describes the frequency for each grid appeared as water in the 30 years time period of 1991 to 2020. The data covers Canada’s entire landmass including all transboundary watersheds, and is at 30-meter spatial resolution. The surface water occurrence frequency is derived using the surface water model of Wang et al. (2023) from all-available monthly water data observed by the Landsat satellites (Pekel et al., 2016). Here, permanent waters are represented by 100%, and permanent land surfaces by 0%, of water occurrence for a 30-meter by 30-meter grid.References:Pekel, J.-F., A. Cottam, N. Gorelick, A.S. Belward, 2016, High-resolution mapping of global surface water and its long-term changes. Nature, 540, 418-422.Wang, S., J. Li, and H. A. J. Russell, 2023, Methods for Estimating Surface Water Storage Changes and Their Evaluations. Journal of Hydrometeorology, DOI: https://doi.org/10.1175/JHM-D-22-0098.1.
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