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Fish, Wildlife and Lands Branch
Saskatchewan Ministry of Environment
Regina
Saskatchewan
CA
20241122
ArcGIS Metadata
1.0
Prairie Landscape Inventory (PLI) Classification
2021-04-07T00:00:00
raster digital data
Fish, Wildlife and Lands Branch
Saskatchewan Ministry of Environment
Fish, Wildlife and Lands Branch
Regina
Saskatchewan
CA
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The 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. </SPAN></P><P><SPAN>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.</SPAN></P><P><A href="https://doi.org:443/10.3390/rs13244972" STYLE="text-decoration:underline;"><SPAN>https://doi.org/10.3390/rs13244972</SPAN></A></P><P><SPAN>The classification map has nine (9) classes: </SPAN></P><P><SPAN STYLE="font-weight:bold;">1. Cropland </SPAN><SPAN /></P><P><SPAN>This class represents all cultivated areas with crop commodities such as corn, Pulses, Soybeans, canola, grains, and summer-fallow. </SPAN></P><P><SPAN STYLE="font-weight:bold;">2. Native </SPAN><SPAN /></P><P><SPAN>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. </SPAN></P><P><SPAN STYLE="font-weight:bold;">3. Mixed </SPAN><SPAN /></P><P><SPAN>This class represents one or more of the followings cases; </SPAN></P><P><SPAN>o A higher heterogenic grassland terrain with a mix of less than 75% native or/and less than 75% tame; </SPAN></P><P><SPAN>o Native or/and tame grassland affected by high abiotic stresses such as soil salinity and drought; </SPAN></P><P><SPAN>o Native or/and tame grassland affected by soil erosion such as water and wind erosions; </SPAN></P><P><SPAN>o A high disturbed area by livestock and human activities; and </SPAN></P><P><SPAN>o A bare terrain with low vegetation cover < 50% coverage in 100 m2 area. </SPAN></P><P><SPAN STYLE="font-weight:bold;">4. Tame </SPAN><SPAN /></P><P><SPAN>This 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. </SPAN></P><P><SPAN STYLE="font-weight:bold;">5. Water </SPAN><SPAN>This class represents one of the following hydrological forms: </SPAN></P><P><SPAN>o Lakes; </SPAN></P><P><SPAN>o Rivers; </SPAN></P><P><SPAN>o Water ponds; </SPAN></P><P><SPAN>o Streamflow; </SPAN></P><P><SPAN>o Dugouts; and </SPAN></P><P><SPAN>o Lower elevations in irrigated areas. </SPAN></P><P><SPAN STYLE="font-weight:bold;">6. Shrubs </SPAN><SPAN>(Modified from ISO 19131 Annual Crop Inventory – Data Product Specifications, Agriculture and Agri-food Canada, 2013.)</SPAN></P><P><SPAN>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. </SPAN></P><P><SPAN STYLE="font-weight:bold;">7. Trees </SPAN><SPAN>(Modified from ISO 19131 Annual Crop Inventory – Data Product Specifications, Agriculture and Agri-food Canada, 2013.)</SPAN></P><P><SPAN>This class represents predominantly forest areas such as: </SPAN></P><P><SPAN>o Coniferous trees; </SPAN></P><P><SPAN>o Deciduous trees; </SPAN></P><P><SPAN>o Mixedwood area; and </SPAN></P><P><SPAN>o Other trees > 2 m height. </SPAN></P><P><SPAN STYLE="font-weight:bold;">8. Woody plants </SPAN></P><P><SPAN>This class represents the sites dominated by woody vegetation including shrubs and trees with typically more than 20% canopy cover.</SPAN></P><P><SPAN STYLE="font-weight:bold;">9. Urban area </SPAN></P><P><SPAN>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).</SPAN></P><P><SPAN STYLE="font-weight:bold;">Colour Classes:</SPAN></P><P><SPAN>Value Label Red, Green, Blue</SPAN></P><P><SPAN>1 Cropland 255, 255, 190</SPAN></P><P><SPAN>2 Native 168, 168, 0</SPAN></P><P><SPAN>3 Mixed 199, 215, 158</SPAN></P><P><SPAN>4 Tame 245, 202, 122</SPAN></P><P><SPAN>5 Water 190, 232, 255</SPAN></P><P><SPAN>6 Shrubs 205, 102, 153</SPAN></P><P><SPAN>7 Trees 38, 115, 0</SPAN></P><P><SPAN>8 Woody 137, 205, 102</SPAN></P><P><SPAN>9 Urban 128, 128, 128</SPAN></P><P><SPAN STYLE="font-weight:bold;">Year:</SPAN></P><P><SPAN>The Year field represents the year the analysis was undertaken. </SPAN></P><P><SPAN STYLE="font-weight:bold;">Accuracy:</SPAN></P><P><SPAN>Please also refer to the R_PLI_MixedGrasslandAccuracy raster , which depicts the estimated level of accuracy for the Mixed Grassland map layer.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Accuracy metrics: </SPAN></P><P><SPAN>The Moist Mixed Grassland 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.</SPAN></P><TABLE><TBODY><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Class</SPAN></SPAN></P></TD><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>User’s accuracy (%)</SPAN></SPAN></P></TD><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Producer’s accuracy (%)</SPAN></SPAN></P></TD><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>F1-score</SPAN></SPAN></P></TD></TR><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Cropland</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>74.7</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>87.1</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.81</SPAN></SPAN></P></TD></TR><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Native grassland</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>61.7</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>78.3</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.69</SPAN></SPAN></P></TD></TR><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Mixed grassland</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>57.7</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>26.1</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.36</SPAN></SPAN></P></TD></TR><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Tame grassland</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>66.9</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>69.8</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.68</SPAN></SPAN></P></TD></TR><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Water</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>96.3</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>84.4</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.90</SPAN></SPAN></P></TD></TR><TR><TD><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Woody plants</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>81.1</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>73.2</SPAN></SPAN></P></TD><TD><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.77</SPAN></SPAN></P></TD></TR></TBODY></TABLE><P><SPAN>The Cypress Upland 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.</SPAN></P><TABLE STYLE="margin:0 0 0 0;"><TBODY><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Class</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>User’s accuracy (%)</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Producer’s accuracy (%)</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>F1-score</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Cropland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>96</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>96</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.96</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Native grassland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>90</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>93</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.92</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Tame grassland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>93</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>71</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.82</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Water</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>100</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>100</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>1.00</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Shrubs</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>77</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>88</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.83</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Trees</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>96</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>996</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.96</SPAN></SPAN></P></TD></TR></TBODY></TABLE><P><SPAN>The Aspen Parkland 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.</SPAN></P><TABLE STYLE="margin:0 0 0 0;"><TBODY><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Class</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>User’s accuracy (%)</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Producer’s accuracy (%)</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>F1-score</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Cropland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>91.2</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>94.5</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.93</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Native grassland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>74.8</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>73.1</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.74</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Mixed grassland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>44.7</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>44.1</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.44</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Tame grassland</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>67.9</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>72.8</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.70</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Water</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>94.8</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>91.3</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.93</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Shrubs</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>61.2</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>51.1</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.56</SPAN></SPAN></P></TD></TR><TR><TD STYLE="padding:0 8 0 8;"><P STYLE="font-weight:bold;margin:0 0 0 0;"><SPAN><SPAN>Trees</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>89.7</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>94.6</SPAN></SPAN></P></TD><TD STYLE="padding:0 8 0 8;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>0.92</SPAN></SPAN></P></TD></TR></TBODY></TABLE><P><SPAN /></P><P><SPAN /></P></DIV></DIV></DIV>
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 R_PLI_MixedGrasslandAccuracy raster , which depicts the estimated level of accuracy for this map layer.
Land cover imagery for the Moist 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 in Google Earth Engine platform. The goal of this land cover was to distinguish native from tame grasslands, and is classified into several classes: native grassland, tame grassland, mixed grassland, cropland, woody plants, water, and urban area.
Habitat Unit in the Fish, Wildlife and Lands Branch, Ministry of Environment
Fish, Wildlife and Lands Branch
Saskatchewan Ministry of Environment
Regina
Saskatchewan
CA
Beatriz Prieto Diaz
Ministry of Environment
Terrestrial Ecologist
Regina
Saskatchewan
CA
ISO 19115 Topic Categories
biota
environment
Prairie
Landscape
Inventory
PLI
Grassland
Mixed Grassland
Ecoregion
Machine Learning
Native Prairie
Landcover
Habitat
Raster
biota
environment
Prairie
Landscape
Inventory
PLI
Grassland
Mixed Grassland
Ecoregion
Machine Learning
Native Prairie
Landcover
Habitat
Raster
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