Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Understanding the state and trends in agriculture production is essential to combat both short-term and long-term threats to stable and reliable access to food for all, and to ensure a profitable agricultural sector. Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based satellite images. Beginning with the 2011 growing season, this activity has been extended to other provinces in support of a national crop inventory. To date this approach can consistently deliver a crop inventory that meets the overall target accuracy of at least 85% at a final spatial resolution of 30m (56m in 2009 and 2010).
In 2010 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) continued the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5, DMC) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Understanding the state and trends in agriculture production is essential to combat both short-term and long-term threats to stable and reliable access to food for all, and to ensure a profitable agricultural sector. Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based satellite images. Beginning with the 2011 growing season, this activity has been extended to other provinces in support of a national crop inventory. To date this approach can consistently deliver a crop inventory that meets the overall target accuracy of at least 85% at a final spatial resolution of 30m (56m in 2009 and 2010).
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Canada Harmonized Agriculture Forest Land Cover 2015 The harmonized land cover (HLC) map is produced from Agriculture and Agri-Food Canada (AAFC) and Canadian Forest Service (CFS) data. The HLC product is exhaustive of all area from the northern edge of Canada’s forested ecosystems to the southern border. The land cover is following Intergovernmental Panel on Climate Change (IPCC) categories, represents the year 2015, and is at 30-m spatial resolution. This harmonized land cover map combines two sector-driven land cover products: the Virtual Land Cover Engine or VLCE from the CFS (Hermosilla et al., 2018), and AAFC's Annual Crop Inventory or ACI (Agriculture and Agri-Food Canada, 2018). The harmonization process was conducted using a Latent Dirichlet Allocation (LDA) model. The LDA model used regionalized class co-occurrences from multiple maps to generate a harmonized class label for each pixel by statistically characterizing land attributes from the class co-occurrences, using the information provided by the error matrices and semantic affinity scores. For a complete overview on the data, methods applied, and information on independent accuracy assessment, see Li et al. (2020). When using this data, please cite as: Li, Z., White, J.C., Wulder, M.A., Hermosilla, T., Davidson, A.M., Comber, A.J., 2020. Land cover harmonization using Latent Dirichlet Allocation. International Journal of Geographical Information Science. DOI: https://doi.org/10.1080/13658816.2020.1796131 (Open access) ( Li et al. 2020). 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., 2018. Disturbance-informed annual land cover classification maps of Canada’s forested ecosystems for a 29-year Landsat time series. Canadia Journal of Remote Sensing 44(1), 67-87. https://doi.org/10.1080/07038992.2018.1437719 (Open access) ( Hermosilla et al. 2018). Agriculture and Agri-Food Canada, 2018. Annual Crop Inventory [WWW Document]. URL https://open.canada.ca/data/en/dataset/ba2645d5-4458-414d-b196-6303ac06c1c9. ( AAFC, 2018. Annual Crop Inventory ).
https://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdfhttps://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdf
Download: hereThe 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. CroplandThis class represents all cultivated areas with crop commodities, including corn, pulse, soybeans, canola, grains, and summer-fallow.2. Native grasslandThis 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 grasslandThis 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. WaterThis class represents permanent water locations such as lakes and rivers.6. ShrubsThis 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. TreesThis 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 areaThis 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 metricsThis 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
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Land cover imagery for the mixed grassland ecoregion of Saskatchewan with a resolution of 10m. Classification was based on machine learning analysis and remote sensing data of Sentinel-1 and Sentinel-2 imagery. The goal of this land cover was to distinguish native from tame grasslands, and is classified into several classes: cropland, native grassland, mixed grassland, tame grassland, water, shrubs and trees. Please also refer to the Prairie Landscape Inventory (PLI) - Mixed Grassland Accuracy raster file, which depicts the estimated level of accuracy for this this classification. Download: Here Land cover imagery for the mixed grassland ecoregion of Saskatchewan with a resolution of 10m. Classification was based on machine learning analysis and remote sensing data of Sentinel-1 and Sentinel-2 imagery. The goal of this land cover was to distinguish native from tame grasslands, and is classified into several classes: cropland, native grassland, mixed grassland, tame grassland, water, shrubs and trees. Badreldin, N.; Prieto, B.; Fisher, R. Mapping Grasslands in Mixed Grassland Ecoregion of Saskatchewan Using Big Remote Sensing Data and Machine Learning. Remote Sens. 2021, 13, 4972. https://doi.org/10.3390/rs13244972The Prairie Landscape Inventory (PLI) working team of Habitat Unit in the Fish, Wildlife and Lands Branch, Ministry of Environment aims to develop improved methods of assessing land cover and land use for conservation. Native grassland, in particular, has been one of the most hard to map at risk ecosystems because of difficulty for imagery classification methods to distinguish native from tame grasslands. Improved classification methods will provide valuable information for habitat suitability, identifying high biodiversity potential and invasion risk potential. The classification map has seven (7) classes: 1. Cropland This class represents all cultivated areas with crop commodities such as corn, Pulses, Soybeans, canola, grains, and summer-fallow. 2. Native This class represents the native grassland areas of the Mixed Grasslands, which are composed primarily of native grass species such as the needle grasses (needle and thread, porcupine grass and green needle grass), wheat grasses (slender wheatgrass, western wheatgrass and awned wheatgrass) along with June grass and blue grama grass. Also includes a variety of additional grass and sedge species, forbs such as pasture sage and some non-vascular species such as selaginella or lichens. 3. Mixed This class represents one or more of the followings cases; o A higher heterogenic grassland terrain with a mix of less than 75% native or/and less than 75% tame; o Native or/and tame grassland affected by high abiotic stresses such as soil salinity and drought; o Native or/and tame grassland affected by soil erosion such as water and wind erosions; o A high disturbed area by livestock and human activities; and o A bare terrain with low vegetation cover < 50% coverage in 100 m2 area. 4. TameThis class represents the tame grassland areas that have in most cases been intentionally modified and seeded or planted with an introduced grass species such as crested wheatgrass and smooth brome. Russian wild rye is encountered typically planted in more saline areas. However, in more recent years’ horticultural varieties of various wheatgrass species have also been introduced. Alfalfa and sweet clover are the most commonly encountered introduced forb species. 5. Water This class represents one of the following hydrological forms: o Lakes; o Rivers; o Water ponds; o Streamflow; o Dugouts; and o Lower elevations in irrigated areas. 6. Shrubs (Modified from ISO 19131 Annual Crop Inventory – Data Product Specifications, Agriculture and Agri-food Canada, 2013.)This class represents the predominantly woody vegetation of relatively low height (generally ±2 m). This class may include grass or wetlands with woody vegetation, and regenerating forest. 7. Trees (Modified from ISO 19131 Annual Crop Inventory – Data Product Specifications, Agriculture and Agri-food Canada, 2013.)This class represents predominantly forest areas such as: o Coniferous trees; o Deciduous trees; o Mixedwood area; and o Other trees > 2 m height. Colour Classes: Value Label Red Green Blue 1 Cropland 255 255 190 2 Native 168 168 0 3 Mixed 199 215 158 4 Tame 245 202 122 5 Water 190 232 255 6 Shrubs 205 102 153 7 Trees 38 115 0 Accuracy:Please refer to the Prairie Landscape Inventory (PLI) - Mixed Grassland Accuracy raster file, which depicts the estimated level of accuracy for this classification.
https://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdfhttps://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdf
Download: HereThe Prairie Landscape Inventory (PLI) working team of Habitat Unit in the Fish and Wildlife Branch, Ministry of Environment aims to develop improved methods of assessing land cover and land use for conservation. Native grassland, in particular, has been one of the most hard to map at risk ecosystems because of difficulty for imagery classification methods to distinguish native from tame grasslands. Improved classification methods will provide valuable information for habitat suitability, identifying high biodiversity potential and invasion risk potential. The classification map has seven (7) classes: 1. CroplandThis class represents all cultivated areas with crop commodities: corn, pulse, soybeans, canola, grains, summer-fallow.2. Native grasslandThis class represents the native grassland areas of the Moist Mixed Grassland ecoregion, which are composed of at least 75% native grass species, such as the needle grasses, wheatgrasses along with June grass and blue grama grass. Also includes additional sedge species, forbs, and some non-vascular species. 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. 3. Mixed grasslandThis class represent a heterogenic grassland with a mix of less than 75% native grass species or less than 75% tame species. 4. Tame grasslandThis class represents the tame grassland areas of the Moist Mixed Grassland ecoregion, which are composed of at least 75% seeded or planted species with introduced grasses and forb species such as crested wheatgrass, smooth brome, alfalfa, sweet clover.5. WaterThis class represents permanent water locations such as lakes and rivers.8. Woody plantsThis class represents the sites dominated by woody vegetation including shrubs and trees with typically more than 20% canopy cover.9. Urban areaThis class was masked using urban/developed area class of the Annual Crop Inventory 2020 (Agriculture Agri-Food Canada), and limited within the urban municipality polygons.Colour Classes:
Value
Label
Red
Green
Blue
1
Cropland
255
255
190
2
Native grassland
168
168
0
3
Mixed grassland
199
215
158
4
Tame grassland
245
202
122
5
Water
190
232
255
8
Woody plants
137
205
102
9
Urban area
128
128
128
Accuracy metricsThis model has an overall accuracy of 70.3 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
74.7
87.1
0.81
Native grassland
61.7
78.3
0.69
Mixed grassland
57.7
26.1
0.36
Tame grassland
66.9
69.8
0.68
Water
96.3
84.4
0.90
Woody plants
81.1
73.2
0.77
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Land cover classification image for the Aspen Parkland 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 2022, and the classification model was built with field data collected in 2020 - 2022. There are eight classes in total: native grassland, tame grassland, mixed/altered 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 eight (8) classes: 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. 3. Mixed/altered grassland This class represents a grassland with a mix of less than 75% native grass, sedge and forb species or less than 75% tame species. These are grassland areas that do not fit into either of the native or tame grassland definitions. 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 3 Mixed/altered grassland 199 215 158 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 73 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 91.2 94.5 0.93 Native grassland 74.8 73.1 0.74 Mixed grassland 44.7 44.1 0.44 Tame grassland 67.9 72.8 0.70 Water 94.8 91.3 0.93 Shrubs 61.2 51.1 0.56 Trees 89.7 94.6 0.92
https://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdfhttps://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdf
Download: HereThe Prairie Landscape Inventory (PLI) working team of Habitat Unit in the Fish and Wildlife Branch, Ministry of Environment aims to develop improved methods of assessing land cover and land use for conservation. Native grassland, in particular, has been one of the most hard to map at risk ecosystems because of difficulty for imagery classification methods to distinguish native from tame grasslands. Improved classification methods will provide valuable information for habitat suitability, identifying high biodiversity potential and invasion risk potential. The classification map has seven (7) classes: 1. CroplandThis class represents all cultivated areas with crop commodities: corn, pulse, soybeans, canola, grains, summer-fallow.2. Native grasslandThis class represents the native grassland areas of the Moist Mixed Grassland ecoregion, which are composed of at least 75% native grass species, such as the needle grasses, wheatgrasses along with June grass and blue grama grass. Also includes additional sedge species, forbs, and some non-vascular species. 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. 3. Mixed grasslandThis class represent a heterogenic grassland with a mix of less than 75% native grass species or less than 75% tame species. 4. Tame grasslandThis class represents the tame grassland areas of the Moist Mixed Grassland ecoregion, which are composed of at least 75% seeded or planted species with introduced grasses and forb species such as crested wheatgrass, smooth brome, alfalfa, sweet clover.5. WaterThis class represents permanent water locations such as lakes and rivers.8. Woody plantsThis class represents the sites dominated by woody vegetation including shrubs and trees with typically more than 20% canopy cover.9. Urban areaThis class was masked using urban/developed area class of the Annual Crop Inventory 2020 (Agriculture Agri-Food Canada), and limited within the urban municipality polygons.Colour Classes:
Value
Label
Red
Green
Blue
1
Cropland
255
255
190
2
Native grassland
168
168
0
3
Mixed grassland
199
215
158
4
Tame grassland
245
202
122
5
Water
190
232
255
8
Woody plants
137
205
102
9
Urban area
128
128
128
Accuracy metricsThis model has an overall accuracy of 70.3 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
74.7
87.1
0.81
Native grassland
61.7
78.3
0.69
Mixed grassland
57.7
26.1
0.36
Tame grassland
66.9
69.8
0.68
Water
96.3
84.4
0.90
Woody plants
81.1
73.2
0.77
https://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdfhttps://gisappl.saskatchewan.ca/Html5Ext/Resources/GOS_Standard_Unrestricted_Use_Data_Licence_v2.0.pdf
Download: hereThe 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 eight (8) classes: 1. CroplandThis class represents all cultivated areas with crop commodities, including corn, pulse, soybeans, canola, grains, and summer-fallow.2. Native grasslandThis 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. 3. Mixed/altered grasslandThis class represents a grassland with a mix of less than 75% native grass, sedge and forb species or less than 75% tame species. These are grassland areas that do not fit into either of the native or tame grassland definitions. 4. Tame grasslandThis 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. WaterThis class represents permanent water locations such as lakes and rivers.6. ShrubsThis 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. TreesThis 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 areaThis 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
3
Mixed/altered grassland
199
215
158
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 metricsThis model has an overall accuracy of 73 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
91.2
94.5
0.93
Native grassland
74.8
73.1
0.74
Mixed grassland
44.7
44.1
0.44
Tame grassland
67.9
72.8
0.70
Water
94.8
91.3
0.93
Shrubs
61.2
51.1
0.56
Trees
89.7
94.6
0.92
Landcover dataset created for the agricultural portion of Saskatchewan. Download: here A satellite imagery classification of Southern Saskatchewan based mainly on 1994 Landsat5 imagery. Developed by the Saskatchewan Research Council after 1997. Background: A group of Provincial and Federal Agencies formed a partnership in March of 1997 to share the cost of obtaining satellite imagery and interpreting this imagery to create a landcover dataset for the agricultural portion of Saskatchewan. The partnership included Saskatchewan Research Council (SRC), Saskatchewan Agriculture and Food (SAF), Saskatchewan Crop Insurance (SCI), Saskatchewan Property Management Corporation (SPMC), Environment Canada, the Prairie Farm Rehabilitation Administration (PFRA) and Saskatchewan Environment Resource Management (SERM). The University of Regina was also involved as an 'in kind' partner providing research services in the area of land cover classifications, accuracy assessment and data conversions. The Partnership Agreement required SRC (partner doing the bulk of data processing) to provide digital files for each of 328 1:50,000 NTS map sheets. The digital files included not only raw imagery, but also one file for each map sheet where the imagery was classified into 24 landcover types. The accuracy of this classification was to be demonstrated by SRC to be at least 90 per cent correct. In addition to the data processing done by SRC, SPMC provided the necessary positional control data (road intersection coordinates) and verified the positional accuracy of the final product. The other partners provided feedback to SRC on classification errors, which improved the overall accuracy of the final product. Classification Value No Data 0 Crop Land 1 Hay Crops (Forage) 2 Native Dominant Grass Lands 3 Tall Shrubs 4 Pasture (Seeded Grass Lands) 5 Hardwoods (Open Canopy) 6 Hardwoods (Closed Canopy) 7 Jack Pine (Closed Canopy) 8 Jack Pine (Open Canopy) 9 Spruce (Close Canopy) 10 Treed Rock 13 Recent Burns 14 Revegetating Burns 15 Cutovers 16 Water Bodies 17 Marsh 18 Herbaceous Fen 19 Mud/Sand/Saline 20 Shrub Fen (Treed Swamp) 21 Treed Bog 22 Open Bog 23 Slopes 25 Slopes 26 0. No Data 1. Crop Land - All lands dedicated to the production of annual cereal, oil seed and other specialty crops, and typically cultivated on an annual basis. 2. Hay Crops (Forage) - Alfalfa and alfalfa/tame grass mixtures. 3. Native Dominant Grass Lands - 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 (Open Canopy) - Corresponds to Provincial Forest Inventory: over 75% hardwoods; 10-30% crown closure. 7. Hardwoods (Closed Canopy) - Corresponds to Provincial Forest Inventory: over 75% hardwoods; 30-100% crown closure. 8. Jack Pine (Closed Canopy) - Similar to Provincial Forest Inventory: 75% or greater Jack Pine; 30-100% crown closure. 9. Jack Pine (Open Canopy) - Similar to Provincial Forest Inventory: 75% or greater Jack Pine; 10-30% crown closure. 10. Spruce (Close Canopy) - Similar to Provincial Forest Inventory: 75% or greater Black and White Spruce; 10-30% crown closure. 11. Spruce: Open Canopy - Similar to Provincial Forest Inventory: 75% or greater Black and White Spruce; 10-30% crown closure. 12. Mixed Woods - All softwood/hardwood mixtures. 13. Treed Rock - Areas of exposed bedrock with generally less then 10% tree cover. Dominant species are Jack Pine and Black Spruce. 14. Recent Burns - All areas that have been recently burned over by wildfires. 15. Revegetating Burns - Burns with a regrowth of commercial timber generally 1-5 metres in height. 16. Cutovers - Areas where commercial timber has been completely or partially removed by logging operations. 17. Water Bodies - Consists of all open water - lakes, rivers, streams, ponds, and lagoons. 18. Marsh - Dominated by sedge and wetland grasses. 19. Herbaceous Fen - Fens dominated by herbaceous species. 20. Mud/Sand/Saline 21. Shrub Fen (Treed Swamp) - Fens dominated by shrubby species. 22. Treed Bog - Peat-covered or peat-filled depressions with a high water table and a surface carpet of moss, chiefly sphagnum. The bogs have 25% or more canopy by trees greater than one metre tall. The primary species is black spruce. 23. Open Bog - Peat-covered or peat-filled depressions with a high water table and a surface carpet of moss, chiefly sphagnum. 24. Farmstead - Farmstead types, towns, cities, Exposed areas with little or no vegetation or Cloud coverage. 25. Slopes - Steep Valley slopes or hill slopes where aspect and slope prohibit classification. 26. Slopes - Steep Valley slopes or hill slopes where aspect and slope prohibit classification.
Download: hereA satellite imagery classification of Southern Saskatchewan based mainly on 1994 Landsat5 imagery. Developed by the Saskatchewan Research Council after 1997. Background: A group of Provincial and Federal Agencies formed a partnership in March of 1997 to share the cost of obtaining satellite imagery and interpreting this imagery to create a landcover dataset for the agricultural portion of Saskatchewan. The partnership included Saskatchewan Research Council (SRC), Saskatchewan Agriculture and Food (SAF), Saskatchewan Crop Insurance (SCI), Saskatchewan Property Management Corporation (SPMC), Environment Canada, the Prairie Farm Rehabilitation Administration (PFRA) and Saskatchewan Environment Resource Management (SERM). The University of Regina was also involved as an 'in kind' partner providing research services in the area of land cover classifications, accuracy assessment and data conversions. The Partnership Agreement required SRC (partner doing the bulk of data processing) to provide digital files for each of 328 1:50,000 NTS map sheets. The digital files included not only raw imagery, but also one file for each map sheet where the imagery was classified into 24 landcover types. The accuracy of this classification was to be demonstrated by SRC to be at least 90 per cent correct. In addition to the data processing done by SRC, SPMC provided the necessary positional control data (road intersection coordinates) and verified the positional accuracy of the final product. The other partners provided feedback to SRC on classification errors, which improved the overall accuracy of the final product.
Classification
Value
No Data
0
Crop Land
1
Hay Crops (Forage)
2
Native Dominant Grass Lands
3
Tall Shrubs
4
Pasture (Seeded Grass Lands)
5
Hardwoods (Open Canopy)
6
Hardwoods (Closed Canopy)
7
Jack Pine (Closed Canopy)
8
Jack Pine (Open Canopy)
9
Spruce (Close Canopy)
10
Treed Rock
13
Recent Burns
14
Revegetating Burns
15
Cutovers
16
Water Bodies
17
Marsh
18
Herbaceous Fen
19
Mud/Sand/Saline
20
Shrub Fen (Treed Swamp)
21
Treed Bog
22
Open Bog
23
Slopes
25
Slopes
26
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Landcover dataset created for the agricultural portion of Saskatchewan. Download: here A satellite imagery classification of Southern Saskatchewan based mainly on 1994 Landsat5 imagery. Developed by the Saskatchewan Research Council after 1997. Background: A group of Provincial and Federal Agencies formed a partnership in March of 1997 to share the cost of obtaining satellite imagery and interpreting this imagery to create a landcover dataset for the agricultural portion of Saskatchewan. The partnership included Saskatchewan Research Council (SRC), Saskatchewan Agriculture and Food (SAF), Saskatchewan Crop Insurance (SCI), Saskatchewan Property Management Corporation (SPMC), Environment Canada, the Prairie Farm Rehabilitation Administration (PFRA) and Saskatchewan Environment Resource Management (SERM). The University of Regina was also involved as an 'in kind' partner providing research services in the area of land cover classifications, accuracy assessment and data conversions. The Partnership Agreement required SRC (partner doing the bulk of data processing) to provide digital files for each of 328 1:50,000 NTS map sheets. The digital files included not only raw imagery, but also one file for each map sheet where the imagery was classified into 24 landcover types. The accuracy of this classification was to be demonstrated by SRC to be at least 90 per cent correct. In addition to the data processing done by SRC, SPMC provided the necessary positional control data (road intersection coordinates) and verified the positional accuracy of the final product. The other partners provided feedback to SRC on classification errors, which improved the overall accuracy of the final product. Classification Value No Data 0 Crop Land 1 Hay Crops (Forage) 2 Native Dominant Grass Lands 3 Tall Shrubs 4 Pasture (Seeded Grass Lands) 5 Hardwoods (Open Canopy) 6 Hardwoods (Closed Canopy) 7 Jack Pine (Closed Canopy) 8 Jack Pine (Open Canopy) 9 Spruce (Close Canopy) 10 Treed Rock 13 Recent Burns 14 Revegetating Burns 15 Cutovers 16 Water Bodies 17 Marsh 18 Herbaceous Fen 19 Mud/Sand/Saline 20 Shrub Fen (Treed Swamp) 21 Treed Bog 22 Open Bog 23 Slopes 25 Slopes 26 0. No Data 1. Crop Land - All lands dedicated to the production of annual cereal, oil seed and other specialty crops, and typically cultivated on an annual basis. 2. Hay Crops (Forage) - Alfalfa and alfalfa/tame grass mixtures. 3. Native Dominant Grass Lands - 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 (Open Canopy) - Corresponds to Provincial Forest Inventory: over 75% hardwoods; 10-30% crown closure. 7. Hardwoods (Closed Canopy) - Corresponds to Provincial Forest Inventory: over 75% hardwoods; 30-100% crown closure. 8. Jack Pine (Closed Canopy) - Similar to Provincial Forest Inventory: 75% or greater Jack Pine; 30-100% crown closure. 9. Jack Pine (Open Canopy) - Similar to Provincial Forest Inventory: 75% or greater Jack Pine; 10-30% crown closure. 10. Spruce (Close Canopy) - Similar to Provincial Forest Inventory: 75% or greater Black and White Spruce; 10-30% crown closure. 11. Spruce: Open Canopy - Similar to Provincial Forest Inventory: 75% or greater Black and White Spruce; 10-30% crown closure. 12. Mixed Woods - All softwood/hardwood mixtures. 13. Treed Rock - Areas of exposed bedrock with generally less then 10% tree cover. Dominant species are Jack Pine and Black Spruce. 14. Recent Burns - All areas that have been recently burned over by wildfires. 15. Revegetating Burns - Burns with a regrowth of commercial timber generally 1-5 metres in height. 16. Cutovers - Areas where commercial timber has been completely or partially removed by logging operations. 17. Water Bodies - Consists of all open water - lakes, rivers, streams, ponds, and lagoons. 18. Marsh - Dominated by sedge and wetland grasses. 19. Herbaceous Fen - Fens dominated by herbaceous species. 20. Mud/Sand/Saline 21. Shrub Fen (Treed Swamp) - Fens dominated by shrubby species. 22. Treed Bog - Peat-covered or peat-filled depressions with a high water table and a surface carpet of moss, chiefly sphagnum. The bogs have 25% or more canopy by trees greater than one metre tall. The primary species is black spruce. 23. Open Bog - Peat-covered or peat-filled depressions with a high water table and a surface carpet of moss, chiefly sphagnum. 24. Farmstead - Farmstead types, towns, cities, Exposed areas with little or no vegetation or Cloud coverage. 25. Slopes - Steep Valley slopes or hill slopes where aspect and slope prohibit classification. 26. Slopes - Steep Valley slopes or hill slopes where aspect and slope prohibit classification.
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Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Understanding the state and trends in agriculture production is essential to combat both short-term and long-term threats to stable and reliable access to food for all, and to ensure a profitable agricultural sector. Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based satellite images. Beginning with the 2011 growing season, this activity has been extended to other provinces in support of a national crop inventory. To date this approach can consistently deliver a crop inventory that meets the overall target accuracy of at least 85% at a final spatial resolution of 30m (56m in 2009 and 2010).