The “Agricultural Major Land Practices Groups of the Canadian Prairies” dataset lays out the areas of the 5 Major Land Practices Groups of the agricultural portions of the Canadian Prairies. They are represented by vector polygons amalgamated (dissolved) from the Version 1.9 SLC polygons sharing common water resources, land use and farming practices as developed in the “Agricultural Land Practices Groups of the Canadian Prairies by SLC Polygon” of this series. The dataset is based upon selected attributes from the Soil Landscapes of Canada (SLC) and the 1996 Census of Agriculture. Typical attributes including: land in pasture, land in summerfallow, crop mixture, farm size and the level of chemical and fertilizer inputs.

The “Prairie Agricultural Landscapes (PAL)” datasets identify areas of the agricultural portions of the Canadian Prairies with similar land and water resources, land use and farming practices. They are represented by vector polygons. Based on selected attributes from the Soil Landscapes of Canada (SLC) and the 1996 Census of Agriculture, the Prairies were classified into 13 (thirteen) classes of Land Practices Group and five (5) Major Land Practices Groups. Typical attributes used to define the Land Practice Groups include: land in pasture, land in summerfallow, crop mixture, farm size and the level of chemical and fertilizer inputs. The five (5) Major Groups were devised to help better understand the relationships between the groups.

The National Ecological Framework for Canada's "Land and Water Area by Province/Territory and Ecoregion” dataset provides land and water area values by province or territory for the Ecoregion framework polygon, in hectares. It includes codes and their English and French descriptions for a polygon’s province or territory, total area, land-only area and large water body area.

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).

This dataset is a rasterized version of the Soil Landscapes of Canada (SLC) dataset. Soil attributes in this dataset have been collated from SLC map polygons and follow the GlobalSoilMap.net standards and specifications at specified depth increments extending over the agricultural portion of Canada. Weighted averages of soil attribute properties are generated from existing soil horizon information to conform to recognized fixed depth increments. Soil attribute weighted means are calculated by using all the soil components based on their areal extent within each SLC polygon. The weighted mean averages of attributes are spatially represented by the grid along with the lowest and highest attribute values found within each polygon.