Contains 2 datasets: * lower and single tier municipalities * upper tier municipalities and districts.

The flood magnitude statistics can be used for applications such as flood plain delineation and design of hydraulic structures. The drought severity statistics can be used for applications such as water abstraction and effluent dilution.

Anthropogenic and natural constraints of the revised land use and development plan of the City of Laval.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

# #Données of the 2022 Hydroclimatic Atlas ## #Description The Hydroclimatic Atlas describes the current and future water regime in southern Quebec in order to support the implementation of water management practices that are resilient to climate change. These data are from the most recent version of the [Hydroclimatic Atlas] (https://www.cehq.gouv.qc.ca/atlas-hydroclimatique). ## #Nouveautés * Improvement of the spatial resolution of the hydrographic network; * Greater spatial coverage; * Addition of the ClimeX and CORDEX-NA sets, in addition to the scenarios of the CMIP5 set; * Use of six hydrological platforms; * Addition of indicators, especially annual ones. * Etc. ## #Liste data available * Link to the new Hydroclimatic Atlas website. * Map of the 24,604 river sections from the Hydroclimatic Atlas with their attributes, available in GeoJSON and shapefile format. To facilitate download and display, the map is divided into 11 GeoJSON files: ABIT (Abitibi and Lac Abitibi region), CND west (North Shore A and B regions), CND east (North Shore regions C, D and E), GASP (North Shore regions C, D and E), GASP (Gaspésie), MONT (Gaspesie), MONT (Montégérie), OUTM (Outaouais Upstream), OUTV (Outaouais Downstream), OUTV (Outaouais Downstream), SAGU (Saguenay), SLNO (St-Laurent north-west), SLSO (St-Laurent south-west) and VAUD (Vaudreuil). * The CSV tables (“Magnitude...”) for each of the 76 hydrological indicators describing the __ampliture__, __direction__ and __dispersion__ for RCP4.5 and RCP8.5, for the three future horizons (see the [documentation] (https://www.donneesquebec.ca/recherche/dataset/8bc217ff-d25d-4f55-a9a7-ada3df4b29a7/resource/086e3a6d-9e79-4aee-81c3-4b2343bf7996/download/metadonnees_atlas2022.pdf) for details). * The CSV tables (“Projected Indicator...”) for each of the 76 hydrological indicators detailing the flow values with their uncertainty for the historical period and the three future horizons (RCP4.5 and 8.5). See the [documentation] (https://www.donneesquebec.ca/recherche/dataset/8bc217ff-d25d-4f55-a9a7-ada3df4b29a7/resource/086e3a6d-9e79-4aee-81c3-4b2343bf7996/download/metadonnees_atlas2022.pdf) for more details. * A [PDF] (https://www.donneesquebec.ca/recherche/dataset/8bc217ff-d25d-4f55-a9a7-ada3df4b29a7/resource/086e3a6d-9e79-4aee-81c3-4b2343bf7996/download/metadonnees_atlas2022.pdf) with metadata and a more detailed description of the data. ## #Note The [2018 version data] (https://www.donneesquebec.ca/recherche/dataset/atlas-hydroclimatique-2018) is archived on Data Québec for reference, for example for old reports or analyses referring to this version of the data. Any new study or analysis should use the most recent data available below or on the Atlas website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Location of the Repentigny boat launch.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset provides wall-to-wall maps of forest structure across Canada's 650 million hectare forested ecosystems for the year 2022, generated at a spatial resolution of 30 m. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Structure estimates include key attributes such as canopy height, canopy cover, and aboveground biomass, derived using a combination of airborne lidar and Landsat-based spectral composites. Structure models were trained using the - lidar-plot framework - (Wulder et al. 2012), which integrates co-located airborne lidar data and ground plot measurements with Landsat time-series composites (Hermosilla et al. 2016). A Nearest Neighbour imputation approach was applied to estimate structural attributes across the full extent of Canada's forested area. These nationally consistent products are intended to support strategic-level forest monitoring and assessment and are not designed for operational forest management. For further details on the methods, accuracy assessment, and source data, see Matasci et al. (2018). Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment, 216, 697-714. https://doi.org/10.1016/j.rse.2018.07.024 (Matasci et al. 2018)

Annual mapping of national level forest harvesting for Canada detected inclusive of 1985 to 2015 from Landsat satellite imagery. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). This dataset is composed of two layers: (1) binary harvest mask, and (2) year of harvest disturbance detection. The information outcomes represent 31 years of harvesting activity in Canada’s forests, derived from a single, consistent, spatially-explicit data source in an automated manner. Time series of Landsat data with 30-m spatial resolution were used to characterize national trends in stand replacing forest disturbances, including those attributed to harvest for the period 1985–2015 for Canada's 650 million hectare forested ecosystems (Hermosilla et al. 2016). See references below for an overview regarding the data, image processing, and time-series change detection methods applied, as well as information on independent accuracy assessment of the data. When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, (2016). Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth. 9(11), 1035-1054. ( Hermosilla et al. 2016) For additional resources on the data used and methods applied, please see: Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., (2015). An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. ( Hermosilla et al. 2015a) Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., (2015). Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. ( Hermosilla et al. 2015b) Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 2017. Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation 63, 104-111.( Hermosilla et al. 2017)

Land uses of the urban plan of the City of Rimouski**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This application allows users to interactively view Crown land interest data layers and explore land parcels. It is intended to be used as a research tool to assist land research on interests on British Columbia Crown land. The tool can be used to view Crown land interest data, imagery, add your own data, and print maps. This application does not include all interests on Crown land. Rather, it provides a curated selection of publicly available data. Only publicly available interest layers are included. No confidential layers are displayed. User-added data is only accessible to the individual who adds it. This data is stored temporarily and will not persist if the user clears their browser cache. Due to volume of data included layers may take time to load. To improve draw time, zoom in as closely as possible to your area of interest. Data is sourced live from the BC Geographic Warehouse, which may occasionally experience temporary outages. The information presented on this map is provided without prejudice for the purposes of land research. It is subject to revision and does not constitute a legal definition.

The Forest Change Type data described here is an update to previously posted open data. The date range for this data is 2012 to 2015. The Forest Change Type data for the prior period from 1985 to 2011 can be found here: https://opendata.nfis.org/mapserver/nfis-change_eng.html or https://gcgeo.gc.ca/geonetwork/search/eng search for “Forest Change” but you must be logged in to see the data. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The forest change data included in this product is national in scope (entire forested ecosystem) and represents the first wall-to-wall characterization of wildfire and harvest in Canada at a spatial resolution commensurate with human impacts. The information outcomes represent 25 years of stand replacing change in Canada’s forests, derived from a single, consistent spatially-explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2010 for Canada's 650 million hectare forested ecosystems (https://authors.elsevier.com/sd/article/S0034425717301360). Landsat data has a 30m spatial resolution, so the change information is highly detailed and is commensurate with that of human impacts. These data represent annual stand replacing forest changes. The stand replacing disturbances types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673). The data available is, 1. a binary change/no-change; 2. Change year; and, 3. Change type. When using this data, please cite as: Hermosilla, T.,Wulder, M. A.,White, J. C.,Coops, N. C.,Hobart, G. W., (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63: 104-111. DOI: 10.1016/j.jag.2017.07.013 White, J.C., M.A. Wulder, T. Hermosilla, N.C. Coops, and G. Hobart. (2017). A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment. 192: 303-321. DOI: 10.1016/j.rse.2017.03.035.