The Global Land Ice Measurements from Space (GLIMS) initiative is a cooperative effort of over sixty institutions world-wide with the goal of inventorying and monitoring a majority of the world\'s estimated 160000 glaciers. Each GLIMS institution oversees the analysis of satellite imagery for a particular region containing glacier ice. Data received by the GLIMS team at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado are inserted into a geospatial database and made available via an on-line interactive map, text-based search interface, a Web Map Service (WMS), and a Web Feature Service (WFS). The GLIMS Glacier Database contains outlines for glaciers smapping all continents having glacial ice. This OGC Web Service is designed to serve GLIMS Glacier Outlines (http://www.glims.org) via the OGC WMS and WFS protocols.

Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as the first of a planned series of maps to be updated every five years, or more frequently. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2010 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) Landsat sensors. An accuracy assessment based on 2811 randomly distributed samples shows that land cover data produced with this new approach has achieved 76.60% accuracy with no marked spatial disparities. - [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)

Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as well as this 2015 land cover map. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2015 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Operational Land Imager (OLI) Landsat sensor. An accuracy assessment based on 806 randomly distributed samples shows that land cover data produced with this new approach has achieved 79.90% accuracy with no marked spatial disparities. - [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)

Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the years 2010, 2015 as well as this 2020 land cover map. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2020 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Operational Land Imager (OLI) Landsat sensor. An accuracy assessment based on 832 randomly distributed samples shows that land cover data produced with this new approach has achieved 86.9% accuracy with no marked spatial disparities. - [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)

Collection of Land Cover products for Canada as produced by Natural Resources Canada using Landsat satellite imagery. This collection of cartographic products offers classified Land Cover of Canada at a 30 metre scale, updated on a 5 year basis. - [Landcover of Canada 2010](https://open.canada.ca/data/en/dataset/c688b87f-e85f-4842-b0e1-a8f79ebf1133) - [Landcover of Canada 2015](https://open.canada.ca/data/en/dataset/4e615eae-b90c-420b-adee-2ca35896caf6) -[Landcover of Canada 2020](https://open.canada.ca/data/en/dataset/ee1580ab-a23d-4f86-a09b-79763677eb47)

__The link: * Access the data directory* is available in the section*Dataset description sheets; Additional information*__. Products derived from lidar (Light Detection and Ranging) are generated as part of the [__provincial lidar sensor data acquisition project__] (https://mffp.gouv.qc.ca/documents/forets/inventaire/Analyse_retombees_lidar-Finale.pdf). It is therefore to facilitate the use of raw lidar data and optimize its benefits that the Ministry of Natural Resources and Forests (MRNF) generated and made available products derived from lidar in a user-friendly format. Lidar technology makes it possible to accurately provide information such as ground altitude, forest cover height (canopy), slopes, and contour lines. Here is the list of the five derived products: + Digital terrain model (spatial resolution: 1 m) + Digital terrain model in shaded relief (spatial resolution: 2 m) + Canopy height model (spatial resolution: 1 m) + Slopes (spatial resolution: 2 m) + Slopes (spatial resolution: 2 m) + Level curve (interval of: 1 m) This data covers almost the entire territory of Quebec south of the 52nd parallel. This map is distributed by map sheet at a scale of 1/20,000. __Note 1:__ The resolution of the following products (digital terrain model, digital terrain model in shaded relief, canopy height model and slopes) has been slightly degraded in visualization in the interactive map to ensure efficient display. __Note 2:__ The planimetric and altimetric accuracy of the curves is variable, but inevitably lower than that of the lidar surveys used to generate them. Moreover, it is recommended to use these level curves only for visual representations, and not for quantitative analyses.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This geographic reference system shows the mapping of land occupancy in Quebec. Land use is defined as physical and biological land cover. It includes artificial surfaces, agricultural areas, forests, forests, semi-natural areas, wetlands, and water bodies. This map covers the territory of southern Quebec and will be extended to northern regions in a later version. The data is generated by a semi-automated classification of high-resolution satellite images, which makes it possible to more accurately identify types of land use. Mapping is available in a unified matrix format. A metadata index as well as a [user guide] (https://diffusion.mern.gouv.qc.ca/diffusion/RGQ/Imagerie/COTQ/Documentation/guide-utilisation.pdf) presenting the data structure and land use classes are available to users.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Maps of the analysis of change between * [mapping of heat islands/freshness 2020-2022] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2020-2022) * and * [mapping of heat/freshness islands using 2013-2014 data] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2013-2014) * on all major urban centers by two methods, i.e. - The map of the __Difference between the differences of temperatures in °C (* [2020-2022] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2020-2022) * minus * [2013-2014] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2013-2014)*)__), which is calculated at the pixel level and produced at the scale of the Quebec ecumene (2016 census, 2016 census, 167,764 km2). The temperature difference is the difference in temperature in the city compared to a nearby wooded area. A positive value of the difference in temperature differences represents an increase in the temperature gap in 2020-2022 compared to 2013-2014, a negative value represents a decrease in the temperature difference in 2020-2022 compared to 2013-2014. - The map of __SUHII index variation between 2020-2022 and 2013-2014 (%) __, which represents the percentage of change in the *Surface Urban Heat Island Intensity* (SUHII) index between the two years. This map covers the extent of * [2021 census population centers] (https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/pop/pop-fra.htm) * () * (CTRPOP) with at least 1,000 inhabitants and a density of at least 400 inhabitants per km2 to which a 2 km buffer zone is added and the values are calculated at the scale of the * [dissemination island] (https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/db-id/db-id-fra.htm) * of Statistics Canada. The SUHII index highlights areas with higher heat island intensity, by calculating a weighted average from the temperature difference classes, giving more weight to the hottest classes. Index change values below 100% represent a decrease in the intensity of UHIs in 2020-2022 compared to 2013-2014. Values greater than 100% represent an increase in UHI intensity between 2013-2014 and 2020-2022. Values around 100% correspond to an absence of change. The temperature difference classes were produced by the k-means algorithm, which takes into account the distribution of temperature difference values in a population center in a given year. The limits of temperature difference classes may therefore differ between the two years, which will influence the variation value of the SUHII index. For more details on the creation of the various maps as well as their advantages, limitations and potential uses, consult the * [Technote] (https://www.donneesquebec.ca/recherche/dataset/analyse-de-changement-ilots-chaleur-fraicheur-et-indice-intensite-ilots-chaleur-urbains/resource/021c5399-a7b3-4b02-a753-39dda706ab27) * (simplified version) and/or the * [methodological report] ( https://www.donneesquebec.ca/recherche/dataset/analyse-de-changement-ilots-chaleur-fraicheur-et-indice-intensite-ilots-chaleur-urbains/resource/ef7e3450-9347-4051-b3bb-bedcba3c0d92) * (full version). The production of this data was coordinated by the National Institute of Public Health of Quebec (INSPQ) and carried out by the forest remote sensing laboratory of the Center for Forestry Education and Research (CERFO), funded under the * [2013-2020 Climate Change Action Plan] (https://www.environnement.gouv.qc.ca/changementsclimatiques/plan-action.asp) * of the Quebec government entitled Le Québec en action vert 2020.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The data presented on this page concern the 2020-2022 mapping of temperature differences, the classification maps of these temperature differences (i.e. urban heat and freshness islands) and the map of the urban heat island intensity index. These different maps are detailed below: - The mapping of __Temperature differences in °C__ represents the temperature difference in the city compared to a nearby forest. It was produced at the scale of the ecumene of Quebec (2021 census, 185,453 km2). This mapping, provided on a grid with a spatial resolution of 15 m, was carried out with a predictive machine learning model built on Landsat-8 satellite data provided by the *United States Geological Survey (USGS) * as well as from other geospatial variables such as hydrography and topography. - Mapping of classes of surface temperature differences, i.e. __Islands of urban heat and freshness (ICFU) * as well as from other geospatial variables such as hydrography and topography. - Mapping of classes of surface temperature differences, i.e. __Islands of urban heat and freshness (ICFU) __ was conducted for * [population centers from the 2021 census] ( https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/pop/pop-fra.htm) * (CTRPOP) with at least 1,000 inhabitants and a density of at least 400 inhabitants per km2 to which is added a 2 km buffer zone. It thus covers all major urban centers, i.e. 14,072 km2. The method for categorizing ICFUs is the ranking of predicted temperature differences for each population center into 9 levels. Classes 8 and 9 are considered __Urban Heat Islands__ and classes 1, 2, and 3 as __Urban Freshness Islands__. The interval values for each class and population center are shown in the production metadata file. Since surface temperatures were analyzed at the Quebec ecumene scale, but the classification intervals were calculated for each population center individually, the differences in temperature grouped into the different classes vary from region to region. Thus, there are differences observed in the predicted temperature differences between North and South Quebec and according to urban realities. For example, a temperature difference of 2°C may be present in class 1 (cooler) in a population center located in southern Quebec, but may be present in class 9 (very hot) in a population center in northern Quebec. It is therefore important to interpret the identification of heat islands in relation to the relative temperature difference data produced at the Quebec ecumene scale. In addition to this map, the map of * [Temperature variations for the urbanization perimeters of the smallest municipalities 2020-2022] (https://www.donneesquebec.ca/recherche/dataset/variations-des-temperatures-pour-les-perimetres-d-urbanisation-des-plus-petites-municipalites) * covers all the urbanization perimeters that are not (or only partially) covered by the ICFU map. Thus, the two maps put side by side allow a complete coverage of all population centers and urbanization perimeters in Quebec. - The __Urban Heat Island Intensity Index (SUHII) __ map __ represents the *Surface Urban Heat Island Intensity* (SUHII) index __ represents the *Surface Urban Heat Island Intensity* (SUHII) index. This index is calculated for each * [dissemination island] (https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/db-id/db-id-fra.htm) * (ID) of Statistics Canada included in the * [2021 census population centers] (https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/pop/pop-fra.htm) * (CTRPOP) * () * (CTRPOP). It highlights areas with higher heat island intensity, by calculating a weighted average from temperature difference classes, giving more weight to the hottest classes. This weight is proportional to the class number (e.g. a class 9 surface is 9 times more important in the index than the same area with a class 1). These maps as well as those of * [2013-2014] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2013-2014) * are used for the * [Analysis of change between the mapping of heat/freshness islands 2013-2014 and 2020-2022] (https://www.donneesquebec.ca/recherche/dataset/analyse-de-changement-ilots-chaleur-fraicheur-et-indice-intensite-ilots-chaleur-urbains) *. For more details on the creation of the various maps as well as their advantages, limitations and potential uses, consult the * [Technote] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2020-2022/resource/285927d4-125e-443a-b5fb-e7c11515b617) * (simplified version) and/or the * [methodological report] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2020-2022/resource/ef5f91cb-f6c9-48f4-ae06-bbfb3483e06e) * (version complete). The production of this data was coordinated by the National Institute of Public Health of Quebec (INSPQ) and carried out by the forest remote sensing laboratory of the Center for Forestry Education and Research (CERFO), funded under the * [2013-2020 Climate Change Action Plan] (https://www.environnement.gouv.qc.ca/changementsclimatiques/plan-action.asp) * of the Quebec government entitled Le Québec en action vert 2020.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Map illustrating the differences in relative surface temperatures for all small urban areas in Quebec. The relative temperature difference is the temperature difference in the city compared to a nearby wooded area. With a 9-level scale for classifying relative differences in temperature, this map indicates areas that are relatively cooler or warmer within urbanization perimeters. This map is complementary to the * [map of urban heat/fresh islands (ICFU)] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2020-2022) *. In fact, it covers all areas of urbanization that are not (or only partially) covered by the ICFU card. Thus, the two maps placed side by side allow a complete coverage of all population centers and urbanization perimeters in Quebec. The interval values for each class of temperature difference within the urbanization perimeters also come from the ICFU map: the classification thresholds for the temperature differences of an urbanization perimeter are reproduced from those of the ICFU map for the population center closest to the urbanization perimeter. The production of this data was carried out by the National Institute of Public Health of Quebec (INSPQ) and was funded under the * [Plan for a Green Economy] (https://www.quebec.ca/gouvernement/politiques-orientations/plan-economie-verte) * of the Government of Quebec.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**