Bottom temperature time series at the 3 fixed stations and 46 stations, grouped into transects, of the Atlantic Zonal Monitoring Program (AZMP) under the Quebec region responsibility. The mean bottom temperature of the last ten years are displayed as 2 layers, one for the June survey (2014-2023, 2020 not sampled), another for the autumn survey (2014-2023). A third layer shows the positions of the fixed stations of the program (Anticosti Gyre, Gaspé Current and Rimouski). Each station is linked with a .png file showing the bottom temperature time series and with a .csv file containing all the bottom temperature data acquired at those stations since the beginning of the program sampling (columns : Station, Latitude, Longitude, Date(UTC), Sounding(m), Depth/Profondeur(m), Temperature/Température(ºC)). Purpose The Atlantic Zone Monitoring Program (AZMP) was implemented in 1998 with the aim of increasing the Department of Fisheries and Oceans Canada’s (DFO) capacity to detect, track and predict changes in the state and productivity of the marine environment. The AZMP collects data from a network of stations composed of high-frequency monitoring sites and cross-shelf sections in each following DFO region: Québec, Gulf, Maritimes and Newfoundland. The sampling design provides basic information on the natural variability in physical, chemical, and biological properties of the Northwest Atlantic continental shelf. Cross-shelf sections sampling provides detailed geographic information but is limited in a seasonal coverage while critically placed high-frequency monitoring sites complement the geography-based sampling by providing more detailed information on temporal changes in ecosystem properties. In Quebec region, two surveys (46 stations grouped into transects) are conducted every year, one in June and the other in autumn in the Estuary and Gulf of St. Lawrence. Historically, 3 fixed stations were sampled more frequently. One of these is the Rimouski station that still takes part of the program and is sampled about weekly throughout the summer and occasionally in the winter period. Annual reports (physical, biological and a Zonal Scientific Advice) are available from the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm). Devine, L., Scarratt, M., Plourde, S., Galbraith, P.S., Michaud, S., and Lehoux, C. 2017. Chemical and Biological Oceanographic Conditions in the Estuary and Gulf of St. Lawrence during 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/034. v + 48 pp. Supplemental Information The bottom temperature is determined from CTD profile in the water column according to AZMP sampling protocol: Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.

The Inuit Communities geographic location dataset contains the geographic location of inhabited and serviced Inuit Communities in Canada as points, as well as data attributes specific to each community. This dataset is Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) and Indigenous Services Canada (ISC) official source for Inuit Communities geographic location on maps. For more information, visit https://www.rcaanc-cirnac.gc.ca/eng/1100100014187/1534785248701.

A Township is a land subdivision in Ontario. This information was captured through the Ontario Base Mapping Program, is maintained by the Ministry of Natural Resources and distributed through Geospatial Ontario (GEO) Warehouse. The spatial accuracy for some of the townships was improved through the Ontario Parcel, Township Realignment and Township Improvement projects. Improvements may include: * road allowance widths * spatial changes to better represent where the township boundaries are located * more consistent concession names Materials used to improve the location of township lines may include: * township Improvement plots * survey information i.e. retracements * original township plans * surveys notes * the physical features e.g. fence lines in the corporate editing environment * water bodies * GPS Ontario Road Network geometry This product requires the use of geographic information system (GIS) software.

Snow and ice are important hydrological resources. Their minimum spatial extent here referred to as annual minimum snow/ice (MSI) cover, plays a very important role as an indicator of long-term changes and baseline capacity for surface water storage. The MSI probability is derived from sequence of seventeen 10-day clear-sky composites corresponding to April, 1 to September, 20 warm period for each year since 2000. Data from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite for the period since 2000 have been processed with the special technology developed at the Canada Centre for Remote Sensing (CCRS) as described in Trishchenko, 2016; Trishchenko et al., 2016; 2009, 2006, Trishchenko and Ungureanu, 2021, Khlopenkov and Trishchenko, 2008, Luo et al., 2008. The presence of snow or ice is determined for each pixel of the image based on snow/ice scene identification procedure and the probability if computed for the entire warm season as a ratio of number of snow/ice flags to the total number of pixels available (less or equal to 17). The minimum snow and ice extent can be derived from the probability map by applying a certain threshold. New data version V5.0 replaces previous version V4.0 for all data available since 2000. All MSI files were reprocessed for all MODIS input data based on collection 6.1. The output format has not changed since previous version. It is described in Trishchenko (2024). The impact of input data change is small and can be detected only for time interval 2000-2015. Data starting 2016 has been already derived using MODIS collection 6.1 input. The differences between the MSI data based on MODIS Collection 5 (i.e. MSI V4) versus MODIS Collection 6.1 (i.e. MSI V5), on average, are quite small. The region-wide relative difference in the MSI extent varies from -3.97% to +1.75%. The mean value is -0.14%, the median value is 0.18% and standard deviation is 1.83%. As such, we do not expect any sizeable impact of the version change on our previous conclusions regarding trends and climate variations, except for refining the relative values of statistical parameters within the range of a few percents. References: TRISHCHENKO, A.P., 2024: Probability maps of the annual minimum snow and ice (MSI) presence over April,1 to September, 20 period since 2000 derived from MODIS 250m imagery over Canada and neighbouring regions. Data format description. CCRS, NRCan. 4pp.

Inventory of buildings and land subject to the right of pre-emption. The right of pre-emption allows the City of Montreal to buy certain buildings or land in priority over any other purchaser in order to carry out projects for the benefit of the community.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Annual Minimum Snow and Ice (MSI) Extent of the Atlas of Canada National Scale Data, are data sets compiled containing annual data from 2000 to present. The data sets were derived from research published by the Canada Centre for Remote Sensing which classified satellite imagery over Canada and neighbouring regions for the continued presence or absence of snow and ice from April 1 to September 20 each year. The Atlas of Canada MSI products consist of a vector dataset and a raster time-series animation application. VECTOR DATASET The vector dataset has been generalized to display at the scale of 1:1,000,000. TIME-SERIES ANIMATION APPLICATION The time-series animation application has not been generalized from its original scale (250 m pixels). The application is disseminated through the Data Cube Platform, implemented by the Canada Centre for Mapping and Earth Observation, Natural Resources Canada using geospatial big data management techniques. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The time-series is also available as a Web Map Service (WMS) and Web Coverage Service (WCS). CREDIT Source data provided by Alexander P. Trishchenko, Canada Centre for Remote Sensing, Natural Resources Canada Metadata record: https://open.canada.ca/data/en/dataset/808b84a1-6356-4103-a8e9-db46d5c20fcf

The Strait of Belle Isle connects the Labrador Shelf and Gulf of St. Lawrence. Few observations of currents in the Strait of Belle Isle exist despite its important contribution to the heat, salt, and mass budgets of the Gulf of St. Lawrence. This is because the deployment of instruments is complicated by the Strait’s remote location, its strong currents, and the presence of thick winter sea ice and icebergs. The present data set aims to provide a long-term time series of currents in the Strait of Belle Isle. Data were collected using a moored Teledyne RDI Workhorse 300 KHz acoustic Doppler current profiler (ADCP). The ADCP was mounted on a subsurface buoy anchored 5 m from the sea floor, in water approximately 70 m deep near the north shore of the Strait (56° 37.2 W, 51° 34.7 N). This instrument provides three-dimensional current profiles every 30 minutes at a vertical resolution of 4 m. Backscatter intensity is also collected at the same resolution. Raw data were processed using the Magtogoek software (https://github.com/iml-gddaiss/magtogoek), developed by the Department of Fisheries and Oceans Canada. Quality flags have been assigned to the data based on beam sidelobe contamination and required thresholds for extreme velocities, beam correlation and percentage of good four-beam transformations. The ancillary data used to apply this quality control are included in the data set. Reference : Shaw, J.-L., & Galbraith, P. S. (2023). Climatology of transport in the Strait of Belle Isle. Journal of Geophysical Research: Oceans, 128, e2022JC019084. https://doi.org/10.1029/2022JC019084

Sectors targeted for urban densification. Polygons resulting from an analysis by the urban planning department and identified as areas conducive to urban densification. **Collection context** Areas determined by the urban planning department. Manual analysis and limits according to an anthropogenic constraint, a street or a zoning limit. **Collection method** Technical drawing and computer-aided mapping. **Attributes** * `ID_ZONAGE` (`long`): Zoning ID * `NUM_ZONE` (`varchar`): Zone number * `GROUPE_USA` (`varchar`): Use group * `LABEL` (`varchar`): Label * `DATE_CREAT` (`date`): Creation date * `DATE_MODIF` (`date`): Date of modification * `USER_MODIF` (`varchar`): Modified by * `Source` (`varchar`): Source * `GRILLE_URL` (`varchar`): Grid of uses For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The National Pollutant Release Inventory (NPRI) is Canada's public inventory of pollutant releases (to air, water and land), disposals and transfers for recycling. The files below contain a map of Canada showing the locations of all facilities that reported direct releases to surface waters to the NPRI. The data are for the most recent reporting year, by reported total quantities of these releases. The map is available in both ESRI REST (to use with ARC GIS) and WMS (open source) formats. For more information about the individual reporting facilities, a dataset is available in a CSV format. Please consult the following resources to enhance your analysis: - Guide on using and Interpreting NPRI Data: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/using-interpreting-data.html - Access additional data from the NPRI, including datasets and mapping products: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/tools-resources-data/exploredata.html

Deforestation in Canada is estimated with the National Deforestation Monitoring System (NDMS). Details describing this process are published here: https://cfs.nrcan.gc.ca/publications?id=36042. Deforestation is the direct human-induced conversion of forested land to non-forested land use. Canada’s National Deforestation Monitoring System (NDMS) was designed and implemented to provide information needed by Canada to meet its obligation under the United Nations Framework Convention on Climate Change (UNFCCC) to report the areas affected annually by deforestation. It also provides important information for the public, government policy makers, and scientists. To provide information about the amount of deforestation and why, where, and when it occurred in Canada, the NDMS uses deforestation mapped on a system of sample areas. The mapping is based on visual interpretation of satellite imagery supported by available ancillary information, such as high resolution imagery, forest inventory, and industrial databases, and informed by records-based information and expert knowledge. Accurate detection and mapping of deforestation events involves manual interpretation of satellite remote sensing imagery by specialized analysts. A key factor in the mapping is to distinguish deforestation from other forest cover losses that occur in Canada. The NDMS was designed to make use of all available lines of evidence and be flexible to accommodate variable resourcing levels. This system has been producing national deforestation monitoring results annually since 2006. The flexibility of the NDMS’s design makes it possible to adapt to future changes in data and resource availability, and positions the program well for sustained operational delivery into the future.