The Manitoba Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF). Together, these datasets describe the spatial distribution of soils and associated landscapes for nearly all agricultural areas in southern Manitoba, as well as some parts of northern and eastern Manitoba.

The Saskatchewan Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF). Together, these datasets describe the spatial distribution of soils and associated landscapes for nearly all agricultural areas in southern Saskatchewan.

The British Columbia Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF). Together, these datasets describe the spatial distribution of soils and associated landscapes for nearly all agricultural areas for the Lower Fraser Valley, British Columbia.

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.

The Nova Scotia Detailed Soil Survey dataset series at a scale of 1:50 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF). Together, these Version 1 datasets describe the spatial distribution of soils and associated landscapes in Pictou County.

The Yukon Detailed Soil Survey dataset series consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF). Together, these datasets describe the spatial distribution of soils and associated landforms in the major valleys of the Yukon.

The Prince Edward Island Detailed Soil Survey is a dataset series describing the spatial distribution of soils and associated landscapes in the Canadian province of Prince Edward Island. Soil landscape information compiled and published over the previous several decades provided the basis for the development of this relational database. The graphic soil landscape polygons are intended to be represented at a scale of 1:75,000. The associated soil landscape information and soil characteristics are described in a standard format in the Component (CMP), Soil Name File (SNF) and Soil Layer File (SLF) tables.

A soil survey is an inventory of soils and their spatial distribution over a landscape. Soil survey reports contain two parts. The first part is a soil map or series of maps at a particular scale with coding for each soil. Soil survey reports also include a supporting document that contains background information such as how the soil survey was conducted, and an explanation of interpretive criteria and a summary of the area occupied by various soil types. The detailed soil surveys identify more of the variation in soil types across smaller landscapes, as compared to Generalized (1:100 000, i.e. provincial overview) and Reconnaissance or General (1:125 000, or 1/2 inch to 1 mile.) soil surveys. Detailed soil survey information is much more accurate and reliable for making decisions at the farm-level. Soil surveys have been published for most of the agricultural areas, and many surrounding areas, across Canada. Data from these surveys comprise the most detailed soil inventory information in the National Soil Database (NSDB). Version 3 was created by Agriculture and Agri-Food Canada in the 2010's by amalgamating version 2 data. It introduced some minor refinements to the version 2 data structure to provide closer alignment with the Soil Landscapes of Canada data structure.

This data product is currently under evaluation and review. It may contain inaccuracies or be subject to change. Users should exercise caution and discretion when interpreting or relying on this information. The government assumes no liability for any errors or decisions based on this preliminary data. For more details, please see the Government of Canada's Open Commons license (https://open.canada.ca/en/open-government-licence-canada). The Canadian Soil Information Service has developed a detailed dataset of Canada's soils and associated properties using advanced machine learning techniques. The Soil Landscape Grids of Canada is produced using a combination of historical and current data from both soil sampling and remote sensing. The machine learning model is trained using over 10,000 pedon locations from across Canada as well as 70 covariate datasets. This new dataset is pivotal in addressing the gaps left by legacy soil surveys and facilitates more comprehensive assessments nationwide. As new data becomes available and machine learning techniques advance, this information can be updated much faster than with traditional soil surveying methods.