Marsh inventory in the Chaleur Bay, the Estuary and the Gulf of St. Lawrence according to a literature review of documents produced between 1985 and 2002.Additional InformationThe marsh inventory was produced according to a literature review of the following documents:Bolduc, F. et P. Kaltenback. 1995. Caractérisation de l'habitat du poisson du banc de Portneuf et avenues de mise en valeur. Rapport présenté par Pro Faune à la Corporation de développement touristique de Rivière-Portneuf. 13 pages et annexes.Comité ZIP Baie des Chaleurs, 2002. Données numériques acquises suite à la cartographie de milieux humides Baie des Chaleurs pour le comité ZIP (printemps 2002).Comité ZIP Côte-Nord du Golfe. 2001. Inventaire du potentiel côtier et marin de la Basse-Côte-Nord. Version préliminaire de rapport sous forme de CD-ROM, Sept-Îles, mars 2001.Kedney, G. et P. Kaltenback. 1996. Acquisition de connaissances et mise en valeur des habitats du banc de Portneuf. Document réalisé par la firme Pro Faune pour le Comité touristique de Rivière-Portneuf. 50 pages et 5 annexes.Labrecque, J., G. Lavoie et F. Boudreau. 1995. Les plantes susceptibles d'être désignées menacées ou vulnérables du barachois de la rivière Malbaie, Barachois-Ouest, Gaspésie. Gouvernement du Québec, ministère de l'Environnement et de la Faune, Direction de la conservation et du patrimoine écologique, Québec. 20 p.Lemieux, C. 1995. Acquisition de connaissances des habitats côtiers dans la région de Rimouski (1995). Rapport du Groupe-Conseil GENIVAR présenté au Ministère des Pêches et des Océans du Canada, Division de la Gestion de l’Habitat du Poisson, 52 pages + 2 annexes.Lemieux, C. 2001. Projet de projection et de mise en valeur de la baie au Chêne et d'habitats côtiers de la région de Pointe-à-la-Croix (Gaspésie). Rapport du Groupe conseil Génivar inc. Présenté au Comité ZIP Baie des Chaleurs et au ministère de l'Environnement du Québec, direction du patrimoine écologique et du développement durable. 76 p. + 8 annexes.Lemieux, C. et R. Lalumière. 1995. Acquisition de connaissances des habitats côtiers du barachois de Saint-Omer. Rap. du Groupe conseil Genivar inc. pour la DGHP, MPO, 44 pages + 3 ann.Les consultants en environnement Argus inc. 1995a. Caractérisation physico-chimique et biologique de l'habitat du poisson du barachois de Malbaie: automne 1994. Rapport présenté au Club des ornithologues de la Gaspésie dans le cadre du programme Saint-Laurent Vision 2000. 62 p. + ann.Les consultants en environnement Argus inc. 1995b. Barachois de Malbaie: étude d'avant-projet de conservation et de mise en valeur. Rapport présenté au Club des ornithologues de la Gaspésie dans le cadre du programme Saint-Laurent Vision 2000. 71 p. + ann.Les consultants en environnement Argus inc. 1995c. Étude biophysique complémentaire de conservation et mise en valeur de la baie des Capucins. Rapport présenté à la corporation de développement de Les Capucins. 48 p. + ann.Les consultants en environnement Argus inc. 1998. Perspectives d'aménagement et de restauration des marais à spartine du Québec. Rapport final. En collaboration avec le Service canadien de la Faune (Environnement Canada), Pêches et Océans Canada, le Ministère des Transports du Québec et Canards Illimités inc. 123 pages + annexes et index cartographique.Létourneau, G. et M. Jean. 1996. Cartographie des marais, marécages et herbiers aquatiques le long du Saint-Laurent par télédétection aéroportée. Environnement Canada – Région du Québec, Conservation de l’environnement, Centre Saint-Laurent, Montréal. 101 pagesLétourneau, Guy. 1991. Milieux humides, Base de données Létourneau 1991 (de Cornwall à Trois-Pistoles et les Îles-de-la-Madeleine.Logimer. 1985. Développement d'un programme de conservation et de reconstitution des habitats lagunaires gaspésiens. Rapport présenté à Pêches et Océans Canada, section Habitat du poisson. 306 p. et annexes.Procéan inc. 1996. Caractérisation du milieu physique et inventaire biologique du barachois de New Richmond : rapport final. Présenté à la Division de la gestion de l'habitat du poisson, Pêches et Océans Canada par Procéan inc.Vaillancourt, M.-A. et C. Lafontaine. 1999. Caractérisation de la Baie Mitis. Jardins de Métis et Pêches et Océans Canada. Grand-Métis. 185 p.

Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.

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).**

Under the Regulation Respecting the Mandatory Reporting of Certain Contaminant Emissions into the Atmosphere (RDOECA), the Ministère de l'Environnement et de la Lutte contre les Changements Climates de la Faune et des Parcs collects data on air contaminants emitted by Quebec businesses in particular. Thus, any person or municipality operating an establishment that emits air contaminants above thresholds into the atmosphere is required to report its emissions no later than June 1 of each year. This dataset includes emissions of air contaminants reported under RDOECA or voluntarily expressed in metric tons, with the exception of dioxin and furan emissions, which are expressed in metric tons of toxic equivalents.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This layer is the current fire year burn severity classification for large fires (greater than 100 ha). Burn severity mapping is conducted using best available pre- and post-fire satellite multispectral imagery acquired by the MultiSpectral Instrument (MSI) aboard the Sentinel-2 satellite or the Operational Land Imager (OLI) sensor aboard the Landsat-8 and 9 satellites. Every attempt is made to use cloud, smoke, shadow and snow-free imagery that was acquired prior to September 30th. However, in late fire seasons imagery acquired after September 30th may be used. This layer is considered an interim product for the 1-year-later burn severity dataset (WHSE_FOREST_VEGETATION.VEG_BURN_SEVERITY_SP). Mapping conducted during the following growing season benefits from greater post-fire image availability and is expected to be more representative of tree mortality. #### Methodology: • Select suitable pre- and post-fire imagery or create a cloud/snow/smoke-free composite from multiple images scenes • Calculate normalized burn severity ratio (NBR) for pre- and post-fire images • Calculate difference NBR (dNBR) where dNBR = pre NBR – post NBR • Apply a scaling equation (dNBR_scaled = dNBR*1000 + 275)/5) • Apply BARC thresholds (76, 110, 187) to create a 4-class image (unburned, low severity, medium severity, and high severity) • Mask out water bodies using a satellite-derived water layer • Apply region-based filters to reduce noise • Confirm burn severity analysis results through visual quality control • Produce a vector dataset and apply Euclidian distance smoothing

Coal Agreement feature class contains provincial extent polygon features representing Coal applications, agreements, leases, and licences, with varying term dates and conditions. These applications and subsequent agreements give the holder the right to explore Coal.

Glaciers and ice masses for the province, derived from aerial imagery flown in the late 1980s and early 1990s. Please refer to the [Glaciers](https://catalogue.data.gov.bc.ca/dataset/glaciers) dataset for recent glacier extents in British Columbia, and [Historical Glaciers](https://catalogue.data.gov.bc.ca/dataset/historical-glaciers) for a comparable historic view.

Under the Regulation Respecting the Mandatory Reporting of Certain Contaminant Emissions into the Atmosphere (RDOECA), the Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks collects data on greenhouse gases (GHGs) emitted by Quebec businesses in particular. Thus, any person or municipality operating an establishment that emits GHGs into the atmosphere in a quantity equal to or greater than 10,000 metric tons in CO2 equivalent (t eq. CO2) is required to report its emissions no later than June 1 of each year.The data is presented in separate files:* Total biogenic and CO2 emissions per establishment;* Emissions per establishment and per greenhouse gas and per establishment.Total emissions files include the total quantity of GHGs, the total quantity of GHGs excluding CO2 from biomass, the quantity of CO2 from the combustion of biomass, and the quantity of CO2 from other uses of biomass (for example fermentation).The emission files by establishment and by greenhouse gas include the quantity emitted of each of the GHGs in metric tons and t eq. CO2. Note that CO2 emissions include those from biomass.The data presented in this dataset includes emissions from mandatory and voluntary reporting.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The purpose of this dataset is to show end users where LiDAR data has been acquired by the Government of Manitoba.LiDAR (Light Detection and Ranging) is a remote sensing technology that uses lasers to collect accurate, continuous elevation data over relatively large areas. These data are essential for activities such as forestry, flood risk management, land use planning, and natural resources management. The Manitoba Government is increasingly acquiring LiDAR data across the province.This layer was created on August 5, 2009 by Manitoba Sustainable Development and was updated on August 9, 2021.To  download LiDAR data from the Manitoba Land Initiative (MLI) site, follow this link: https://mli2.gov.mb.ca/dems/index_external_lidar.html Fields included ( Alias (Field Name): Field description.) ObjectID (OBJECTID) - Automatically generated feature numberAcquired  (ACQUIRED) - LiDAR data capture dateContractor  (CONTRACTOR) - Contractor nameContributor  (CONTRIB) - Manitoba Government departmentName (NAME) - Dataset nameCellsize (CELLSIZE) - Raster DEM cell sizeMLI (MLI) - Data available for download on the Manitoba Land Initiative site

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in maximum temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected change in maximum temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected maximum temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of maximum temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in statistically downscaled maximum temperature (°C) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of downscaled CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.