Landcover dataset created for the northern part of Saskatchewan based on a combination of Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM+) data representing circa 2000 conditions. Download: here It is a priority of the Saskatchewan and Canadian government to assess and monitor the health and sustainability of Canada's Forest. The North Digital Land Cover Classification (NDLC) will provide Saskatchewan's contribution to Canada's Earth Observation for Sustainable Development of Forests (EOSD) initiative, helping Canada fulfill it's obligation to the Kyoto Protocol. The NDLC supports the mission and directives of the Saskatchewan provincial government by providing an essential dataset which will enable researchers, natural resource managers and government to assess the health and sustainability of our forests, perform research in the area of climate change, manage natural resources and create policy. The NDLC will be based on a combination of Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM+) data representing circa 2000 conditions. The NDLC is being produced through a collaboration of federal, provincial, and territorial governments, agencies and industry. Classification Value Background 0 Agriculture 1 Not Assigned 2 Pasture Upland Herbaceous Graminoid 3 Not Assigned 4 Not Assigned 5 Hardwood Open Canopy 6 Hardwood Closed Canopy 7 Jack Pine Closed Canopy 8 Jack Pine Open Canopy 9 Spruce Closed Canopy 10 Spruce Open Canopy 11 Mixed Hardwoods/Softwoods, Softwood/Hardwood Open and Closed Canopy 12 Treed Rock 13 Recent Burn 14 Revegetating/Regenerating Burn 15 Cutovers 16 Water 17 Marsh 18 Herbaceous Fen 19 Mud Sand Saline 20 Shrub Fen 21 Treed Bog 22 Open Bog 23 Not Assigned 24 Settlements/Roads 25 Barren Land 26 Mixed Softwoods Open and Closed 27 Cloud/Shadow/Haze 28 Unclassified 29 0. Background: Where pixels values are equal to 0 in all channels of satellite image data.  1. Agriculture: Cropland and agricultural clearing areas  2. Not Assigned: Empty Class  3. Pasture Upland Herbaceous Graminoid: Lands containing known pastures, tame or native grasses and herbaceous vegetation. May contain low-lying shrubs with less then 10% tree cover. 4. Not Assigned: Empty Class  5. Not Assigned: Empty Class  6. Hardwood Open Canopy: Trembling Aspen, White Birch, Balsam Poplar composes greater than 75% of species by area, Crown Closure: greater than 10% and less than or equal to 55% (SE crown closure classes A and B).  7. Hardwood Closed Canopy: Trembling Aspen, White Birch, Balsam Poplar composes greater than 75% of species by area, Crown Closure: greater than 55% (SE crown closure classes C and D).  8. Jack Pine Closed Canopy: Jack Pine composes greater than 75% of species by area, Crown Closure: greater than 55% (SE crown closure classes C and D).  9. Jack Pine Open Canopy: Jack Pine composes greater than 75% of species by area, Crown Closure: greater than 10 and less than or equal to 55% (SE crown closure classes C and D).  10. Spruce Closed Canopy: White Spruce, Black Spruce composes greater than 75% of species by area, Crown Closure: greater than 55% (SE crown closure classes C and D).  11. Spruce Open Canopy: White Spruce, Black Spruce composes greater than 75% of species by area, Crown Closure: greater than 10 and less than or equal to 55% (SE crown closure classes C and D).  12. Mixed Hardwoods/Softwoods, Softwood/Hardwood Open and Closed Canopy: An area of hardwood and softwood combinations in which neither hardwood nor softwood account for greater than 75% of species by area and where the crown closure is greater than 10%.  13. Treed Rock: Forest vegetation less than 10%.  14. Recent Burn: An area showing evidence of recent burning natural or prescribed and there is little to no regeneration or revegetation visible.  15. Revegetating/Regenerating Burn: An area showing evidence of natural or prescribed burning and where regeneration or revegetation is visible.  16. Cutovers: An area of deforestation, vegetated and non-vegetated. Ancillary data required to correctly classify due to the anthropogenic land cover/land use class.  17. Water: These areas include lakes, rivers, streams, and reservoirs.  18. Marsh: A periodically wet or continually flooded but non peat-forming area supporting grasses, sedges and reeds.  19. Herbaceous Fen: A wetland area consisting of nutrient rich water and decomposing peat supporting vascular and nonvascular plants grasses, sedges, and reeds.  20. Mud Sand Saline: Water saturated soil, salt water and sand containing no vegetation.  21. Shrub Fen: A wetland area consisting of nutrient rich water and decomposing peat supporting low shrubs, forbs, grass, moss, and a sparse tree cover.  22. Treed Bog: A wetland area consisting of decomposing peat moss, lichen and shrubs with 10% to 25% tree cover of stunted black spruce and tamarack.  23. Open Bog: A wetland area consisting of low nutrient water and decomposing peat moss, lichen, and sparse tree cover.  24. Not Assigned: Empty Class  25. Settlements/Roads: Anthropogenic land cover consisting of urban, commercial, industrial, major roads, highways, surface mines, gravel pits and spoil piles.  26. Barren Land: With the exception of the settlements and Roads class, any area of exposed rock, soil or non-vegetated land.  27. Mixed Softwoods Open and Closed: Jack Pine/Spruce, Spruce/Jack Pine Open and Closed, an area of softwood combinations in which neither Jack Pine or Spruce account for greater than 75% of species by area and where crown closure is greater than 10%.  28. Cloud/Shadow/Haze: An area of cloud, shadow, haze.  29. Unclassified: An area of unidentifiable land cover, indicates no work done/not classified, wrong information, missing data and possible new class greater than 3 pixels. 

Land cover classification image for the Cypress Upland ecoregion of Saskatchewan with a spatial resolution of 10m. The goal of this land cover classification was to distinguish native from tame grasslands. The classification was based on Sentinel-1 and Sentinel-2 imagery using machine learning analysis in the Google Earth Engine platform. The classification was conducted on imagery acquired in 2023, and the classification model was built with field data collected in 2023. There are seven classes in total: native grassland, tame grassland, cropland, shrubs, trees, water, and urban area. Download: here The Prairie Landscape Inventory (PLI) aims to develop improved methods of assessing land cover and land use for conservation. Native grassland has historically been one of the hardest to map at-risk ecosystems because of the challenges in distinguishing native grassland from tame grassland land cover using remotely sensed imagery. This classification distinguishes native grassland from tame grassland and will provide valuable information for habitat suitability for native grassland species, identifying high biodiversity potential and invasion risk potential.   The classification map has seven (7) classes. The mixed grassland class included in the PLI land cover classification for other prairie ecoregions was not modelled in the Cypress Upland. 1. Cropland This class represents all cultivated areas with crop commodities, including corn, pulse, soybeans, canola, grains, and summer-fallow. 2. Native grassland This class represents the native grassland areas that are composed of at least 75% native grass, sedge and forb species, such as the needle grasses and wheatgrasses along with June grass and blue grama grass. Unbroken grassland that is invaded by species like Kentucky bluegrass, crested wheatgrass or smooth brome, such that native cover is less than 75%, is not considered native for the purpose of this project.  4. Tame grassland This class represents the tame grassland areas that are composed of at least 75% seeded or planted species with introduced grasses and forb species such as crested wheatgrass, smooth brome, Kentucky bluegrass, alfalfa, and sweet clover. 5. Water This class represents permanent water locations such as lakes and rivers. 6. Shrubs This class represents the sites dominated by woody vegetation of relatively low height (generally +/-2 meters) with shrub canopy typically >20% of total vegetation cover. 7. Trees This class represents the coniferous/deciduous trees, mixed-wood area, and other trees >2 meters height with tree canopy typically >20% of total vegetation cover. 9. Urban area This class represents both urban municipalities and buffered roads. Urban municipalities was used to mask the urban/developed area class of the Annual Crop Inventory 2021 (Agriculture Agri-Food Canada). Colour Classes: Value Label Red Green Blue 1 Cropland 255 255 190 2 Native grassland 168 168 0 4 Tame grassland 245 202 122 5 Water 190 232 255 6 Shrubs 205 102 153 7 Trees 66 128 53 9 Urban area 128 128 128 Accuracy metrics This model has an overall accuracy of 92 per cent. The table below summarizes the user’s accuracy, producer’s accuracy, and F1-score of the model on the validation dataset. Class User’s accuracy (%) Producer’s accuracy (%) F1-score Cropland 96 96 0.96 Native grassland 90 93 0.92 Tame grassland 93 71 0.82 Water 100 100 1.00 Shrubs 77 88 0.83 Trees 96 996 0.96

Since 1988, the governments of Canada and Quebec have been working together to conserve, restore, protect and develop the St. Lawrence River under the St. Lawrence Action Plan (SLAP). One of the projects identified under the theme of biodiversity conservation is the development of an integrated plan for the conservation of the natural environments and biodiversity of the St. Lawrence River. The identification of priority sites for conservation has been the first step of this planning exercise. Conservation planning of natural environments requires a reliable, accurate and up-to-date image of the spatial distribution of ecosystems in the study area. In order to produce an Atlas of Priority Sites for Conservation in the St. Lawrence Lowlands, an updated cartography of the land cover of this vast territory was undertaken. This project required obtaining reliable information on the natural environments of the St. Lawrence Lowlands. Although several land cover mapping projects have been conducted for specific types of habitats, it was particularly important to obtain a homogeneous product that would cover the entire territory and that would provide the most detailed information on its various thematic components: agricultural, aquatic, human-modified and forest environments, wetlands as well as old fields and bare ground. The methodology used to produce the land cover mapping of the St. Lawrence Lowlands thus relied mainly on combining and enhancing the best existing products for each theme. This project was made in collaboration with MDDELCC as part of the St. Lawrence Action Plan (SLAP).

The 1 cm resolution vegetation digital height model was extracted using a bare earth model and digital surface model (DSM) derived from unmanned aerial vehicle (UAV) imagery acquired from a single day survey on July 28th 2016, in Cambridge Bay, Nunavut. The mapping product covers 525m2 and was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008

The 2000 AAFC Land Use is a culmination and curated metaanalysis of several high-quality spatial datasets produced between 1990 and 2021 using a variety of methods by teams of researchers as techniques and capabilities have evolved. The information from the input datasets was consolidated and embedded within each 30m x 30m pixel to create consolidated pixel histories, resulting in thousands of unique combinations of evidence ready for careful consideration. Informed by many sources of high-quality evidence and visual observation of imagery in Google Earth, we apply an incremental strategy to develop a coherent best current understanding of what has happened in each pixel through the time series.

Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) files for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistered. For this dataset, the spatial resolutions are: 25 cm for the year 1950, 50 cm for the year 1959, 50 cm for the year 1967, 50 cm for the year 1972, 50 cm for the year 1978 and 70 cm for the year 1982. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

This collection is a legacy product that is no longer supported. It may not meet current Government standards. The National Topographic Data Base (NTDB) comprises digital vector data sets that cover the entire Canadian landmass. The NTDB includes features such as watercourses, urban areas, railways, roads, vegetation, and relief. The organizational unit for the NTDB is the National Topographic System (NTS), based on the North American Datum of 1983 (NAD83). Each file (data set) consists of one NTS unit at either the 1:50,000 or 1:250,000 scale. Related Products: [NTDB Correction Matrices, 2003-2009](https://ouvert.canada.ca/data/en/dataset/b6d0c19c-27e3-4392-b21f-49b1eec95653)

The Saskatchewan Digital Land Cover was created to be used in the interim. The National Land Cover Project plans to integrate land cover information compiled by Natural Resources Canada, Canadian Forest Service, and Agriculture and Agri-Food Canada. The Saskatchewan Digital Land Cover raster provides a seamless provincial coverage of the province and was created by combining the Saskatchewan Research Council's Northern Digital Land Cover (NDLC) with the Southern Digital Land Cover (SDLC).  With exception to the SDLC's value 2 (i.e. Hay Crops) and value 3 (i.e. Native Dominant Grass Lands), the NDLC takes precedence over the SDLC in areas that the two rasters overlap because the NDLC is more current than the dated SDLC. The SDLC's values 2 and 3 were preserved because these land covers are not specifically represented in the NDLC. For the purpose of this dataset, some of the SDLC and NDLC values were reclassified to new values to reconcile varying definitions.  It should also be noted that because the NDLC's 30 x 30 metre pixels do not align with the SDLC's 30 x 30 metre pixels, this raster was snapped to the NDLC. Last, as is with the SDLC and the NDLC, the extent of this raster does not extend all of the way to the Saskatchewan boundary, specifically, the Information Services Corporation's SaskGIS Provincial Boundary dataset, in numerous areas along the west, south and southeast borders: There are gaps of up to 500 m wide of "no data" between the provincial boundary and the raster along these areas of the Saskatchewan boundary. Classification Value AGRICULTURE 1 HAY CROPS 2 NATIVE DOMINANT GRASSLANDS 3 TALL SHRUBS 4 PASTURE 5 HARDWOODS (OPEN CANOPY) 6 HARDWOODS (CLOSED CANOPY) 7 JACKPINE (CLOSED CANOPY) 8 JACKPINE (OPEN CANOPY) 9 SPRUCE (CLOSED CANOPY) 10 SPRUCE (OPEN CANOPY) 11 MIXED WOODS 12 TREED ROCK 13 RECENT BURNS 14 REVEGETATING/REGENERATION BURN 15 CUTOVERS 16 WATER 17 MARSH 18 HERBACEOUS FEN 19 MUD/SAND/SALINE 20 SHRUB FEN (TREED SWAMP) 21 TREED BOG 22 OPEN BOG 23 FARMSTEAD 24 UNCLASSIFIED 25 BARREN LAND 26 MIXED SOFTWOODS (OPEN & CLOSED) 27 PASTURE UPLAND HERBACEOUS GRAMINOID 30 1. AGRICULTURE - Cropland, including all lands dedicated to the production of annual cereal, oil seed, and other specialty crops, and typically cultivated on an annual basis; and agricultural clearing areas.  2. HAY CROPS (Forage) - Alfalfa and alfalfa/tame grass mixtures.  3. NATIVE DOMINANT GRASSLANDS - Native dominant grasslands. (May contain tame grasses and herbs.)  4. TALL SHRUBS - Communities containing both low and tall shrub, snowberry, saskatoon, chokecherry, buffaloberry, and willow.  5. PASTURE (Seeded Grass Lands) - Grassland dominated by tame grass species.  6. HARDWOODS (I.E. OPEN CANOPY) - Greater than 75% hardwoods by area, including trembling aspen, white birch, balsam poplar; 10 - 55% crown closure.  7. HARDWOODS (I.E. CLOSED CANOPY) - Greater than 75% hardwoods by area, including trembling aspen, white birch, balsam poplar; Greater than 55% crown closure.  8. JACKPINE (I.E. CLOSED CANOPY) - Greater than 75% of Jack Pine by area; Greater than 55% crown closure.  9. JACKPINE (I.E. OPEN CANOPY) - Greater than 75% of Jack Pine by area; 10 - 55% crown closure.  10. SPRUCE (I.E. CLOSED CANOPY) - Greater than 75% or greater Black and White Spruce; Greater than 55% crown closure.  11. SPRUCE (I.E. OPEN CANOPY) - Greater than 75% Black and White Spruce; 10-55% crown closure.  12. MIXED WOODS - All softwood/hardwood mixtures; open and closed canopy (i.e. An area of hardwood and softwood combinations in which neither hardwood nor softwood account for greater than 75% of species by area, and where the crown closure is greater than 10%).  13. TREED ROCK - Areas of exposed bedrock with generally less then 10% tree cover.  14. RECENT BURNS - An area showing evidence of recent burning natural or prescribed and there is little to no regeneration or revegetation visible.  15. REVEGETATING/REGENERATION BURN - An area showing evidence of natural or prescribed burning and where regeneration or revegetation is visible.  16. CUTOVERS - An area of deforestation, vegetated and non-vegetated.  17. WATER - These areas include lakes, rivers, streams and reservoirs  18. MARSH - A periodically wet or continually flooded but non peat-forming area supporting grasses, sedges, and reeds.  19. HERBACEOUS FEN - A wetland area consisting of decomposing peat supporting vascular and nonvascular plants (i.e. grasses, sedges, reeds).  20. MUD/SAND/SALINE - Water saturated soil, sand containing no vegetation, and salt water.  21. SHRUB FEN (I.E. TREED SWAMP) - A wetland area consisting of decomposing peat supporting low shrubs, forbs, grass, moss, and a sparse tree cover.  22. TREED BOG - A wetland area consisting of decomposing peat moss, lichen, and shrubs, with 10% or more canopy by trees (i.e. primarily black spruce and tamarack).  23. OPEN BOG - A wetland area consisting of decomposing peat moss, lichen, and sparse tree cover.  24. FARMSTEAD - Farmsteads, towns, cities, exposed areas with little or no vegetation.  25. UNCLASSIFIED  26. BARREN LAND - Any area of exposed rock, soil, or non-vegetated land.  27. MIXED SOFTWOODS (OPEN & CLOSED) - Jack Pine/Spruce, Spruce/Jack Pine Open and Closed, an area of softwood combinations in which neither Jack Pine or Spruce account for greater than 75% of species by area, and where crown closure is greater than 10%.  30. PASTURE UPLAND HERBACEOUS GRAMINOID - Lands containing known pastures, tame or native grasses, and herbaceous vegetation. These lands may contain low-lying shrubs with less then 10% tree cover.

This data publication contains a set of files in which areas affected by fire or by harvest from 1984 to 2015 are identified at the level of individual 30m pixels on the Landsat grid. Details of the product development can be found in Guindon et al (2018). The change detection is based on reflectance-corrected yearly summer (July and August) Landsat mosaics from 1984 to 2015 created from individual scenes developed from USGS reflectance products (Masek et al, 2006; Vermote et al, 2006). Briefly, the change detection method uses a six-year temporal signature centered on the disturbance year to identify fire, harvest and no change. The signatures were derived from visually-interpreted disturbance or no-change polygons that were used to fit a decision tree model. The method detects about 91% of the areas harvested and 85% of the areas burned across Canada’s forests over the study period, but overestimates areas disturbed in the two initial and mostly in the two final years of the 1985 to 2015 time series. This is caused by the absence of appropriate pre-disturbance and post-disturbance data for the model-based detection and attribution. Disturbance coverage in those four years should therefore be used with caution. As in Guindon et al (2014), the method was designed to minimize commission errors and has a disturbance class attribution success rate of about 98%. The attribution success rate of disturbance year for fire is of about 69% for the exact year and of about 99% when attribution to the following year is also considered as a success. This common one-year lag is mostly due to the use of mid-summer Landsat mosaics for the analysis that will cause spring and fall events of the same year to be attributed to successive years. For example, a fire that occurred in the fall of 2004 (after July and August), will be detected and attributed to 2005, while for a fire that occurred in the spring of 2004 will be detected and attributed to 2004. The presence of clouds and shadows or image availability causes 10% of missing data annually and therefore can too delay the capture of events. The data provides uniform spatial and temporal information on fire and harvest across all provinces and territories of Canada and is intended for strategic-level analysis. Since no attention was given to other minor disturbances such as mining, road or flooding, the product should not be used for their identification. Finally, calibration datasets were developed for only three major forest pests (mountain pine beetle, eastern spruce budworm and forest tent caterpillar), but were folded within the “no-change” class in order to minimize commission errors for fire and harvest . Less common pests for which validation datasets are hard to develop were not considered and therefore could in rare circumstances generate false fire events. Considering that area having two (3.3%) to three disturbances (less than 1%) events are not common, only the most recent disturbance is provided, overlapping older disturbances in these rare case. ## Please cite this dataset as: Guindon, L., P. Villemaire, R. St-Amant, P.Y. Bernier, A. Beaudoin, F. Caron, M. Bonucelli and H. Dorion. 2017. Canada Landsat Disturbance (CanLaD): a Canada-wide Landsat-based 30-m resolution product of fire and harvest detection and attribution since 1984. https://doi.org/10.23687/add1346b-f632-4eb9-a83d-a662b38655ad ## Scientific article citation: The creation, validation and limitations of the CanLaD product are described in the Supplementary Material file associated with the following article: Guindon, L.; Bernier, P.Y.; Gauthier, S.; Stinson, G.; Villemaire, P.; Beaudoin, A. 2018. Missing forest cover gains in boreal forests explained. Ecosphere, 9 (1) Article e02094. doi:10.1002/ecs2.2094. ## Cited references: Masek, J.G., Vermote, E.F., Saleous N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., and Lim, T-K. (2006). A Landsat surface reflectance dataset for North America, 1990–2000. IEEE Geoscience and Remote Sensing Letters 3(1):68-72. http://dx.doi.org/10.1109/LGRS.2005.857030. Vermote, E., Justice, C., Claverie, M., & Franch, B. (2016). Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sensing of Environment. http://dx.doi.org/10.1016/j.rse.2016.04.008.

The 1 cm resolution digital surface model (DSM) was created from unmanned aerial vehicle (UAV) imagery acquired from a single day survey, July 28th 2016, in Cambridge Bay, Nunavut. Five control points taken from a Global Differential Positioning System were positioned in the corners and the center of the vegetation survey. The DSM covering 525m2 was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008