The LiDAR Point Clouds is a product that is part of the CanElevation Series created to support the National Elevation Data Strategy implemented by NRCan.This product contains point clouds from various airborne LiDAR acquisition projects conducted in Canada. These airborne LiDAR acquisition projects may have been conducted by NRCan or by various partners. The LiDAR point cloud data is licensed under an open government license and has been incorporated into the National Elevation Data Strategy.Point cloud files are distributed by LiDAR acquisition project without integration between projects.The point cloud files are distributed using the compressed .LAZ / Cloud Optimized Point Cloud (COPC) format. The COPC open format is an octree reorganization of the data inside a .LAZ 1.4 file. It allows efficient use and visualization rendering via HTTP calls (e.g. via the web), while offering the capabilities specific to the compressed .LAZ format which is already well established in the industry. Point cloud files are therefore both downloadable for local use and viewable via URL links from a cloud computing environment.The reference system used for all point clouds in the product is NAD83(CSRS), epoch 2010. The projection used is the UTM projection with the corresponding zone. Elevations are orthometric and expressed in reference to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013).

Cet ensemble de données fournit des informations complètes sur les établissements de garderies éducatives agréés au Nouveau-Brunswick. Il comprend des détails essentiels tels que la région, le district, le numéro d'agrément, le nom de l'établissement, le nom du site de garderies éducatives, le type d'établissement (à temps plein, à temps partiel ou à milieu familial) et l'adresse de l'établissement. En outre, l'ensemble de données précise le nombre de places autorisées, y compris celles pour les nourrissons, les enfants d'âge préscolaire et les enfants d'âge scolaire. Il précise également la langue de service, l'identifiant et le nom de la personne exploitante, et si l'établissement est désigné. À des fins d'analyse spatiale et de cartographie, les coordonnées de latitude et de longitude de chaque établissement sont incluses.

Cet ensemble de données fournit des informations complètes sur les établissements de garderies éducatives agréés au Nouveau-Brunswick. Il comprend des détails essentiels tels que la région, le district, le numéro d'agrément, le nom de l'établissement, le nom du site de garderies éducatives, le type d'établissement (à temps plein, à temps partiel ou à milieu familial) et l'adresse de l'établissement. En outre, l'ensemble de données précise le nombre de places autorisées, y compris celles pour les nourrissons, les enfants d'âge préscolaire et les enfants d'âge scolaire. Il précise également la langue de service, l'identifiant et le nom de la personne exploitante, et si l'établissement est désigné. À des fins d'analyse spatiale et de cartographie, les coordonnées de latitude et de longitude de chaque établissement sont incluses.

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.

Difference from Normal Temperature values are computed by subtracting the normal monthly average temperature from the average monthly temperature of the month. The average monthly temperature is computed by obtaining the mean value of average daily temperatures for a month. If the month was colder than normal the value computed will be negative and if it was warmer the value will be positive.Long-term average is 1991-2020.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

Difference from Average Precipitation represents the accumulated precipitation value for a location, subtracted by the long-term average value. A negative value indicates that the location has received less than the normal amount of precipitation (mm) for that timeframe. A positive value indicates that the location has received more than the normal amount of precipitation (mm).Time periods calculated for difference from average precipitation are 1, 2, 3, 6, 9, 12, 18, 24 months.Long-term average is 1991-2020. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

This dataset provides refined monthly climatological projections for six key ocean variables: surface and bottom temperature, surface and bottom salinity, mixed layer depth, and bottom current speed. The projections are provided for six Maritime Marine Protected Areas: the Gully, the Laurentian Channel, St. Anns Bank, Musquash Estuary, Banc-des-Américains, and Basin Head. These projections are based on downscaled outputs from 22 CMIP6 models under four emissions scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) for four 20-year periods spanning 2020 to 2099 (2020–2039, 2040–2059, 2060–2079, and 2080–2099).For each model and scenario, 20-year climatological means were computed for each future period. These climatologies were then aggregated to produce ensemble means and ensemble standard deviations for all variables. The released dataset includes only these ensemble summary fields and is provided as gridded data with dimensions longitude × latitude × scenario × time.Cite this data as: Wang., Z. Data of High-resolution climate projection data for Marine Protected Areas in the Maritimes. Published: May 2026. Ocean Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/fb4b3212-bca3-4192-8401-687faccc534b

Description:Night-time sea surface temperature (SST) was acquired from the AVHRR Pathfinder project, with data distributed by NOAA, and averaged into monthly climatological composites. The data span late 1981 through 2010 at 4 km pixel resolution.Methods:AVHRR Pathfinder version 5.3 Level 3C night Sea Surface Temperature (SST) was acquired from NOAA at 4 km spatial resolution. The monthly mean value at all pixels was calculated for individual years, then all years were combined to produce final maps of monthly mean and monthly standard deviation of SST, and the number of occurrences of valid data at each pixel over the period of observation. The quality level of all satellite observations was also acquired with this dataset, and used to remove any pixels with a quality level lower than 4. Further, pixels with fewer than two occurrences over the period 1981-2010 were removed from these maps, and set to a NaN value in the tif files. All resulting rasters were cropped to the Canadian Exclusive Economic Zone and assigned to the NAD83 geographic coordinate reference system (EPSG:4269), and have a final pixel resolution of approximately 0.0417 degrees. The monthly mean, monthly standard deviation, and number of occurrences for all pixels are provided.Uncertainties:Satellite values have been evaluated against global datasets, and datasets of samples in the Pacific region (see references). However, uncertainties are introduced when averaging together images over time as each pixel has a differing number of observations. Short-lived or spatially limited events may be missed.

Description:Night-time sea surface temperature (SST) was retrieved from the MODIS instrument on the Aqua satellite, with data distributed by the NASA Ocean Biology Processing Group, and averaged into monthly climatological composites. The data span the years 2003-2020; records were created at 1 km pixel resolution to be consistent with other satellite products.Methods:MODIS-Aqua night long-wave Sea Surface Temperature (SST) images were acquired from the NASA Ocean Biology Processing Group at processing Level-2 (version 2018), 1-km resolution, spanning the period 2003-01-01 to 2020-12-31. Image pixels were aligned and mapped to a regular grid using the SeaDAS program, retaining all pixels with a quality level of ‘1’ or lower, which is recommended for scientific analysis. The monthly mean value at all pixels was calculated for individual years, and used to produce maps of the monthly climatological mean and standard deviation of SST. Additionally, the number of occurrences of valid data at each pixel over the period of observation were calculated. Pixels with fewer than two occurrences over the entire period of observation were removed from these maps, and set to a NaN value in the tif files. A few small gaps between pixels (near the edges of individual images) were filled using the median value of surrounding pixels, provided there were greater than 4 values. Finally, all rasters were cropped to the Canadian Exclusive Economic Zone and assigned to the NAD83 geographic coordinate reference system (EPSG:4269), and have a final pixel resolution of approximately 0.01 degrees. The monthly mean, monthly standard deviation, and number of occurrences for all pixels are provided.Data Sources:NASA Ocean Biology Processing Group. (2017). MODIS-Aqua Level 2 Ocean Color Data Version R2018.0. NASA Ocean Biology Distributed Active Archive Center. https://doi.org/10.5067/AQUA/MODIS/L2/OC/2018Uncertainties:Satellite values have been evaluated against global datasets, and datasets of samples in the Pacific region (see references). However, uncertainties are introduced when averaging together images over time as each pixel has a differing number of observations. Short-lived or spatially limited events may be missed.