Canada imagery and land cover data
＋ Follow new data223 datasets about imagery and land cover in Canada.
uav imagery by Bard College, acquired 2025-12-13 to 2025-12-13, 2.5 cm per pixel, published on OpenAerialMap.
Dates of Images: Post-Event: Pre-Event: Date of Next Image: Unknown Summary: The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. Suggested Use: For NDVI, dark green colors are areas with a lot of green leaf growth which indicates the presence of chlorophyll. Chlorophyll reflects more infrared light and less visible light. Areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are even lighter greens. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus REST Endpoint: See URL on the right. WMS Endpoint:
Includes data managed by the Development Services department, Planning Sections. The data is updated to this site weekly. Click this link for more information
uav imagery by Sean Frey, acquired 2025-10-04 to 2025-10-04, 3.6 cm per pixel, published on OpenAerialMap.
uav imagery by robert howe , acquired 2025-10-04 to 2025-10-04, 2.3 cm per pixel, published on OpenAerialMap.
Orthophotos combine the image characteristics of a photograph with the geometric qualities of a map. The primary digital orthophotoquadrangle (DOQ) is a 1-meter ground resolution, quarter-quadrangle (3.75 minutes of latitude by 3.75 minutes of longitude) image cast on the Universal Transverse Mercator projection (UTM) on the North American Datum of 1983 NAD83). The geographic extent of the DOQ is equivalent to a quarter-quadrangle plus the overage ranges from a minimum of 50 meters to a maximum of 300 meters beyond the extremes of the primary and secondary corner points. The overage is included to facilitate tonal matching for mosaicking and for the placement of the NAD83 and secondary datum corner ticks. The normal orientation of data is by lines (rows) and samples (columns). Each line contains a series of pixels ordered from west to east with the order of the lines from north to south. The radiometric image brightness values are stored as 256 gray levels, ranging from 0 to 255. The standard, uncompressed gray scale DOQ format contains an ASCII header followed by a series of 8-bit image data lines. The keyword-based, ASCII header may vary in the number of data entries. The header is affixed to the beginning of the image and is composed of strings of 80 characters with an asterisk (*) as character 79 and an invisible newline character as character 80. Each keyword string contains information for either identification, display, or registration of the image. Additional strings of blanks are added to the header so that the length of a header line equals the number of bytes in a line of image data. The header line will be equal in length to the length of an image line. If the sum of the byte count of the header is less than the sample count of one DOQ image line, then the remainder of the header is padded with the requisite number of 80 character blank entries, each terminated with an asterisk and newline character. Purpose: DOQs serve a variety of purposes, from interim maps to field references for Earth science investigations and analysis. The DOQ is useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps.
uav imagery by Sean Frey, acquired 2026-05-05 to 2026-05-05, 3.2 cm per pixel, published on OpenAerialMap.
Polygon representation of shadow impact assessment areas as defined in the Regional Centre Land Use By-law.To identify areas as represented in Schedule 27 which fall under the provisions of Appendix 2 of the Regional Centre LUB.Reference to the complete package is required to determine permitted land uses in the Regional Centre Plan and By‐law. Contact HRM Planning & Development. Metadata
Dates of Images: Date of Next Image: Unknown Summary: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Landsat dataset at 10m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. A threshold of the dNBR raster flagged all the pixels that had values of -0.15 or less. This threshold was manually defined through different iterations in an effort to balance the detection of actual burned areas compared to agricultural activities and other unwanted change detections. The resulting vector was clipped to include detections that were near known fires to further reduce noise and false detections. This was done with cloud masked data, which automatically excluded areas obscured by clouds or thick smoke dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Check fire containment and image dates for further context on image timing. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. dNBR is commonly used as a proxy to identify fire-affected areas. Higher dNBR value are statistically correlated with greater burn severity, where negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post-vegetation. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR will not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure), and the interpretation of dNBR values may vary widely based on the type of vegetation burned. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. This dataset has not been validated by independent burn severity assessments. Satellite/Sensor: Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager (OLI-2) Resolution: 30 meters Esri REST Endpoint: See Layers below. WMS Endpoint: See individual pages of layers below.
This dataset is a tile mosaic of 3-foot aerials of the City of Tacoma from 1973. Contact Info: GIS Team GISteam@cityoftacoma.org Company: Fairchild Aerial Surveys, Inc. Flight Time: September, 1973 and June 17, 1974 Scale: 1” = 400
Dates of Images Post-Event: 7/29/2026, 7/30/2026, 8/1/2026, 8/2/2026/ 8/3/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Skysat. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.
NOTE: due to the high resolution, users may need to zoom into individual tiles to view imagery. Open the attribute table, select a layer, and zoom to the tile to view if difficulties arise. Dates of Images Post-Event: 8/9/2026, 8/11/2026, 8/12/2026 Summary SkySat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Planet Labs PBC. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.
aircraft imagery by Hawkinson Aerial Photography, LLC, acquired 2025-04-21 to 2025-04-21, 3.7 cm per pixel, published on OpenAerialMap.
Dates of Images: 20260724T1849, 20260725T1843, 20260727T1901 (GMT) (YYYYMMDDTHHMM) Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at the Jet Propulsion Laboratory, California Institute of Technology produced maximum vegetation anomaly loss and disturbance status, using the OPERA Surface Disturbance Alert from Harmonized Landsat Sentinel-2 (DIST-ALERT-HLS) dataset. The dataset provided includes two product types: Vegetation Disturbance Status maps on individual dates Maximum Vegetation Anomaly loss maps on individual dates Dates and Input Data: Images: June 24, July 25, and July 27, 2026 Products are generated from OPERA DIST-ALERT-HLS satellite imagery and mosaicked across tiles to provide continuous coverage. Product Description: Surface Disturbance, specifically vegetation loss, is identified from optical satellite imagery and mapped at 30 m spatial resolution. The Vegetation Disturbance Status layer indicates the confidence that vegetation loss has occurred, and whether the disturbance is still ongoing or has ended. The Max Vegetation Anomaly loss shows how much vegetation has been lost at each location, based on the largest change observed during the time period. As the number of post-event images increase, the confidence in the detections increases. Note we applied a temporal filter to these products. The temporal filter was used to remove any surface disturbance that occurred prior to the onset of the wildfires. Caveats and Limitations: This product detects vegetation loss due to any reason. Importantly, not all detected changes are due to wildfire on June 28, 2026. These results are intended to support rapid emergency response. All information is provisional for use under emergency response guidelines. These data are provided with absolutely no warranty of any kind. Use at your own risk. Suggested Use: The OPERA DIST-ALERT-HLS maps per pixel vegetation disturbance (specifically, vegetation cover loss) from the Harmonized Landsat Sentinel-2 (HLS) scenes. We provide the (1) maximum vegetation anomaly value (VEG-ANOM-MAX) layer and (2) vegetation disturbance status (VEG-DIST-STATUS). All provided layers have been filtered to include only disturbance detected following the start of the fires. VEG-ANOM-MAX: Difference between 3 year historical baseline and current year observed vegetation cover at the date of maximum decrease (vegetation loss of 0-100%). This layer can be used to threshold vegetation disturbance per a given sensitivity (e.g. disturbance of >=20% vegetation cover loss). Layer Values: 0-100: Maximum loss of percent vegetation (suggested color: white to red gradient) 255: No data (suggested color: transparent) File names: OPERA_L3_DIST-ALERT-HLS_V1_VEG-ANOM-MAX_20260724T1849_mosaic.tif, OPERA_L3_DIST-ALERT-HLS_V1_VEG-ANOM-MAX_20260725T1843_mosaic.tif, OPERA_L3_DIST-ALERT-HLS_V1_VEG-ANOM-MAX_20260727T1901_mosaic.tif VEG-DIST-STATUS: Indication of vegetation cover loss (vegetation disturbance). The status label is based on the maximum anomaly value, confidence level, and whether it is ongoing or finished. ''First'' means the pixel has had an anomaly detection but no subsequent observations whether anomalous or not. ''Provisional'' means there have been two consecutive disturbance detections but not yet with high confidence. ''Confirmed'' means that vegetation disturbance is detected with high confidence. The label ''finished'' is applied to confirmed disturbances that have had two consecutive no-anomaly observations or one 15 days or more after the last anomaly detection. If a new disturbance is detected, it will overwrite those in a ''finished'' state. These labels are reported for both above and below the 50% disturbance threshold based on the maximum anomaly value. Layer Values: 0: No disturbance (suggested color: #121212) 1: first 2: provisional 3: confirmed 4: first >=50% (suggested color: #008888) 5: provisional >=50% (suggested color: #e48727) 6: confirmed >=50% (suggested color: #e01b07) 7: confirmed 8: confirmed >=50%, finished (suggested color: #dddddd) 255: No data (suggested color: transparent) File names: OPERA_L3_DIST-ALERT-HLS_V1_VEG-DIST-STATUS_20260724T1849_mosaic.tif, OPERA_L3_DIST-ALERT-HLS_V1_VEG-DIST-STATUS_20260725T1843_mosaic.tif, OPERA_L3_DIST-ALERT-HLS_V1_VEG-DIST-STATUS_20260727T1901_mosaic.tif Satellite/Sensor/Resolution: Satellite/Sensor: Harmonized Landsat Sentinel-2 (HLS) derived from MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B/2C satellites and Operational Land Imager 2 (OLI-2) on NASA/USGS Landsat 8/9 satellites. Spatial Resolution: 30 meters Temporal Resolution: Sub-weekly Credits: The product contains modified Copernicus Sentinel-2 and NASA Landsat 8/9 data, processed by the European Space Agency and NASA. Data were analyzed by the NASA-JPL/Caltech ARIA/OPERA team. The DIST products are produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group, and managed by NASA's Jet Propulsion Laboratory. The DIST-ALERT-HLS product was developed and produced by the OPERA Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland. NASA JPL-Caltech-UMD ARIA/OPERA Team Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (bato@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov )
