Real-time water level and flow (discharge) data collected at over 2100 hydrometric stations across Canada (last 30 days).

Results of the last hour available, in real time, of the [Air Quality Index (AQI)] (https://www.iqa.environnement.gouv.qc.ca/contenu/index.asp) for the stations of the [Quebec Air Quality Monitoring Network] (https://www.environnement.gouv.qc.ca/air/reseau-surveillance/Carte.asp). These results exclude those from stations located on [Montreal Island] (https://www.donneesquebec.ca/recherche/dataset/vmtl-rsqa-indice-qualite-air).The IQA is an information and awareness tool designed to inform the population about the quality of ambient air in Quebec.If you have any questions about this data, contact the Info-Air department:.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Traffic obstacles on the City of Montreal's road network updated in real time and standardized according to the CIFS standard. Data is entered by City teams. This data allows decision-making in real time in knowledge of the state of the network.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

All files and resources that allow you to connect to planned and real-time data from the Société de transport de Laval.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This set provides users of the Société de Transport de Montréal (STM) public transport with timetables, real-time bus positioning and, since version 2, data on the occupancy rate on board buses. *To access GTFS—Realtime and the i3 API, register on the [Developers] Portal (https://www.stm.info/fr/a-propos/developpeurs) *.Note:This data set is the property of the Société de transport de Montréal. Consequently, according to the attribution clause of the Creative Commons 4.0 license, the authorship of the data must be attributed to the Société de transport de Montréal.Please contact the Société de transport de Montréal (dev@stm.info) if you have any questions about this package.The routes of bus and metro lines as well as the planned schedules of their trips are also [available] (https://donnees.montreal.ca/organization/societe-de-transport-de-montreal) in open data.__Warning__: The GTFS-Realtime v1 API will reach end of life in the coming weeks. It will no longer be available after Friday, May 28, 2021. After this date, you will need to use version 2 of the GTFS-RealTime API.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Terrestrial gamma dose rates, reported as ambient dose equivalent in the unit nSv/hr, are presented for the past ninety days to present. Data is measured in real-time, typically from the spectroscopic dosimeters of the Fixed Point Surveillance (FPS) Network. Dosimeter stations of this network are located in population centres and other strategic locations across Canada. Real-time data provides insight into typical levels and fluctuations of radioactivity in the Canadian environment and may provide early detection of sources of radioactivity other than environmental background.As a reference, the Nuclear facilities and uranium mines and mills can be found in the Open Maps catalogue and added to the Real-time Environmental Radioactivity Monitoring map using the "+" (Add layer) button of the viewer’s “Layers” panel. The ESRI REST or WMS links found in the Nuclear facilities and uranium mines and mills metadata record is what’s needed to proceed. These links can be found here: https://open.canada.ca/data/en/dataset/6478153c-829f-4649-bd52-41f63b41021f.The Nuclear facilities and uranium mines and mills dataset provided by the Canadian Nuclear Safety Commission corresponds to nuclear licensees that operate across Canada. This includes uranium mines and mills, uranium processing facilities, nuclear power plants, research reactors, particle accelerators, and nuclear substances processing facilities. All of these facilities are licensed by the CNSC and are subject to strict regulatory oversight to ensure the safety of the public and the environment.

All files and resources that allow you to connect to planned and real-time data from the Société de transport de Trois-Rivières. GTFS 2024**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Data include a collection of annual land cover maps derived from MODIS 250 m spatial resolution remotely sensed imagery for the period 2000 to 2011. Processing of the time series was designed to reduce the occurrence of false change between maps. The method was based on change updating as described in Pouliot et al. (2011, 2013). Change detection accounted for both abrupt changes such as forest harvesting and more gradual changes such as recurrent insect defoliation. To determine the new label for a pixel identified as change, an evidential reasoning approach was used to combine spectral and contextual information. The 2005 MODIS land cover of Canada at 250 m spatial resolution described in Latifovic et al. (2012) was used as the base map. It contains 39 land cover classes, which for time series development was considered too detailed and was reduced to 25 and 19 class versions. The 19 class version corresponds to the North America Land Change Monitoring System (NALCMS) Level 2 legend as described in Latifovic et al. (2012). Accuracy assessment of time series is difficult due to the need to assess many maps. For areas of change in the time series accuracy was found to be 70% based on the 19 class thematic legend.This time series captures the spatial distribution of dominant land cover transitions. It is intended for use in modeling, development of remote sensing products such as leaf area index or land cover based albedo retrievals, and other exploratory analysis. It is not appropriate for use in any rigorous reporting or inventory assessments due to the accuracy of the land cover classification and uncertainty as to the capture of all relevant changes for an application.

Data include a collection of annual land cover maps derived from MODIS 250 m spatial resolution remotely sensed imagery for the period 2000 to 2011. Processing of the time series was designed to reduce the occurrence of false change between maps. The method was based on change updating as described in Pouliot et al. (2011, 2013). Change detection accounted for both abrupt changes such as forest harvesting and more gradual changes such as recurrent insect defoliation. To determine the new label for a pixel identified as change, an evidential reasoning approach was used to combine spectral and contextual information. The 2005 MODIS land cover of Canada at 250 m spatial resolution described in Latifovic et al. (2012) was used as the base map. It contains 39 land cover classes, which for time series development was considered too detailed and was reduced to 25 and 19 class versions. The 19 class version corresponds to the North America Land Change Monitoring System (NALCMS) Level 2 legend as described in Latifovic et al. (2012). Accuracy assessment of time series is difficult due to the need to assess many maps. For areas of change in the time series accuracy was found to be 70% based on the 19 class thematic legend.This time series captures the spatial distribution of dominant land cover transitions. It is intended for use in modeling, development of remote sensing products such as leaf area index or land cover based albedo retrievals, and other exploratory analysis. It is not appropriate for use in any rigorous reporting or inventory assessments due to the accuracy of the land cover classification and uncertainty as to the capture of all relevant changes for an application.NOTE: To see this entire product in the map viewer, use a base map in the "World" section (EPSG: 3857).

Temperature data (typically in time series format) comes from investigations performed by government agencies, geotechnical engineers and consultants, academics, and others to obtain information on the air or ground thermal conditions of a site. Ground temperature investigations generally include the installation of temperature sensors at a variety of depth intervals, and data loggers which record the temperatures at regular time intervals ( e.g., hourly or daily) for varying time periods ranging from one-time or occasional measurements to multi-year monitoring. They also often involve the installation or monitoring of above-ground weather stations. Where ground temperature data characterizes the ground thermal regime, weather data allows for an understanding of the relationship between the ground thermal regime and local weather.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)