Mapping Ontario's Soils
Look back on Ontario's historic legacy soil surveys, and dig into the science behind remapping Ontario's soils.
1. Ontario's Soil Survey
Ontario’s Legacy Soil Surveys hold valuable information for producers, but new technologies can create higher precision soil maps that are important tools for a much wider range of stakeholders making land management decisions.
OMAFRA wants to make it easier for the public to access Legacy Soil Surveys as well as up-to-date soil information as it becomes available so knowledge about building healthy soils can reach the people who can best use it.
This StoryMap will review Ontario’s Legacy Soil Surveys, including where to view legacy soil data, followed with current drivers of soil mapping and an overview of the technologies and science involved in predictive digital soil mapping (PDSM). We explain the ties between precision agriculture and predictive digital soil mapping with a focus on soil management applications and environmental stewardship.
You can navigate to a specific section of the StoryMap by selecting one of the seven navigation links that remain visible at the top of the page as you scroll.
Soil Legacy Maps & Reports
The collection of soil information in Ontario began in the 1920s with the start of the Ontario Soil Survey Program. The soil report of Norfolk County was the first publication completed, with other counties bordering Lake Erie closely following suit.
These reports were created in collaboration with numerous parties, including the University of Guelph (formerly the Ontario College of Agriculture), the Ontario Institute of Pedology (disbanded), the Soil Research Institute (disbanded), and the Canadian Department of Agriculture (currently Agriculture and Agri-Food Canada). Over 20 different authors contributed to the Ontario Soil Legacy Reports that began in the 1920s and continued into the late 1990s. During this period the science of pedology evolved along with mapping techniques and the system used to classify soils in Canada (currently the Canadian System of Soil Classification).
The demand for soil information was historically based on the need for soil data focusing on Southern Ontario’s prime agricultural soils. Much of Ontario’s vast Northern soils were mapped sporadically and in much less detail.
In total there are 147 catalogued reports and maps available in the Ontario Soil Survey Collection.
A compilation of Ontario's Legacy Soil Maps by county and year of publication.
Due to their vastly ranging publication dates, some maps are more detailed than others. Generally, the traditional methods of soil data acquisition involved using topographic maps, aerial photographs, sample analyses and reliance on the experience of pedologists of the day to create maps with hand-drawn soil boundaries at scales of about 1:50 000 (typically 1:63,360 or 1 inch to 1 mile).
An example aerial photograph with red and blue pen marking the soil property boundaries.
A drainage map (left) and a topographic map (right) from the Soil Survey of York County.
Even given their age, soil legacy reports and maps are still a useful resource for farmers, agronomists, crop advisors, and planners. Soil legacy reports and maps identify the names of soil, describe the chemical and physical soil properties, as well as classify the soil taxonomically.
Canada Land Inventory (CLI) ratings are available in these reports along with drainage and glacial deposit details. All of this information was used to determine prime agricultural areas for land use planning. Protecting prime agricultural land is important for food security, however, planning practices of the past did not require highly detailed map units.
Soil Surveys ranging from No.1-9 do not have both the soil map and report available on the CanSIS (Canadian Soil Information Service) website, however, both the soil map and report can be viewed for reports No. 10 onward. These Maps and Reports were originally hard copies, but digital copies can be accessed as scans of their originals.
Soil Survey Report covers for Essex County (1949), York County (1955), Wellington County (1963), and Niagara (1989).
OMAFRA's Ag Maps is a webpage you can access to view the Agricultural Information Atlas; Canada Land Inventory; OMAFRA Program Dataset Descriptions; Map Gallery and more.
The soil data from the legacy maps and reports are also available for viewing as layers on the OMAFRA Agricultural Information Atlas interactive web map.
AgMaps allows users to view soil data such as:
The Agriculture Information Atlas also holds the capacity to allow users to create downloadable maps of their properties using rural aerial imagery that is much better than Google Earth. Try launching this easy to use interactive online application here:
Geocortex Viewer for HTML5
An alternative way to view soil data is through GeoHub. This website hosts land inventory data for Ontario, through which you can access the Soil Survey Complex for mapped regions of Ontario by downloading the data or viewing an interactive web map.
The major issue with legacy maps is that they are hand-drawn hardcopies, and while they can be digitized, they do not fully meet the needs of modern agriculture, land-use planning, and stewardship initiatives. County boundary changes have occurred and within the Legacy Soil Surveys there are some soil classification inconsistencies, therefore, soil data needs to be updated.
Additionally, there is a new demand for soil map products that are easily accessible through smart devices. With new machine learning techniques legacy soil county maps can be recreated with increased visual detail and accuracy. Map users also need to be able to access the digital database that houses all the spatial soil data accompanying the map to create tailored products that meet the needs of the end user.
2. Drivers of Soil Mapping
Other recent initiatives are motivating the renewal of Ontario’s Legacy Soil Maps and Reports.
Ontario’s Agricultural Soil Health and Conservation Strategy aims to conserve healthy agricultural soils for future generations.
“This strategy is a long-term framework to guide collaborative soil health research, investments and activities until 2030. The strategy’s vision is: Healthy agricultural soils contribute to a vibrant agricultural sector, productive economy, sustainable environment and thriving society. The strategy’s goals, objectives and actions are divided into four theme areas to address different aspects of the issues: Soil Management, Soil Data and Mapping, Soil Evaluation and Monitoring and Soil Knowledge and Innovation.” - Agricultural Soil Health and Conservation Strategy
Under the second theme, Soil Data and Mapping, the goal is to make reliable soil data and tools available for informed decision-making and analysis by producers, industry, government, and the public.
To learn more about the actions under the Soil Data and Mapping goal look at pages 28-32 of the Soil Health Strategy .
OMAFRA also has a database in development that will securely house digital soil data in an easily searchable, and organized manner. The Ontario Agricultural Soil Information System (OASIS) will structure the soil information collected by specialists to help streamline digital soil mapping analysis.
Essentially, good soil management decisions rely on sound soil data that is publicly available. The current work being done by OMAFRA soil mapping staff is helping to reach the objectives of creating comprehensive and replicable soil data that can be used for analysis and decision making. New soil data and maps can be used on a small scale by farmers who, for example, want to examine the carbon content of their fields, or on a large scale for land use planning initiatives.
3. New Soil Mapping Technology
Since the completion of the soil legacy maps new advanced technologies have been developed that increase the efficiency and accuracy of soil mapping. The technologies that make modern soil mapping possible are listed below.
Using these technologies, we can predict detailed soil properties for areas that have not been field sampled.
LiDAR provides continuous high-resolution data about the environment that is being sampled, which when combined with a collection of field soil samples and other environmental data, can be used to generate a machine learning model to predict soil properties. Scientists have determined multiple factors contribute to the development of soil.
The relationship between soil and its environment have long been established. If a soil found in the landscape occurs in response to a certain set of environmental conditions (soil forming factors) then these conditions can be used to predict the occurrence of the same soil in other areas having the same environment. This is the theory that modern soil mapping is based upon.
The soil forming factors.
The initiative to acquire high resolution LiDAR digital elevation data at a 50 cm resolution has played a key role in increasing the detail of modern digital soil maps.
R programing software and non-parametric statistics are tools used for to create virtual models that predict soil properties. Modern GIS software is used to display, modify and input the data for modeled relationships of a chosen geography, i.e. a sampled area. This process is formally known as Predictive Digital Soil Mapping (PDSM).
4. PDSM
OMAFRA is currently using the Predictive Digital Soil Mapping (PDSM) process to renew the soil maps for The Regional Municipality of Ottawa; The County of Peterborough and other similar sized areas of the Province. The following is an outline of the steps involved in PDSM.
(1) Organization and collection of environmental information to decide the location of soil field samples. This procedure is used to maximize the probability that soil sampling captures all variation in soil types and properties within a study area.
(2) At each field site chosen by the computer model, soil horizon descriptions are recorded, then field samples are collected and analyzed in the lab where soil chemical and physical properties are determined (e.g., C, N, CEC, exchangeable Ca K Mg and Na, pH and texture). The results are organized into a database used in a machine learning model.
(3) All environmental information is combined with the soil sample dataset and run through a variety of statistical models. A percentage of the soil sample data is withheld from the model, and then compared to the model results to determine how accurate the model was at predicting soil properties for the entire region in question.
(4) The predictions from the most accurate model are chosen to generate final predictive maps. These digital maps created with GIS software can be engineered to highlight a specific soil property, such as soil carbon content or combined and interpreted for field management decisions.
Below is an example of a soil carbon map created with legacy data (left) compared to a soil carbon map created with predictive digital soil mapping (right). Slide the arrows left and right to view the difference in detail.
PDSM can provide a much higher level of detail in map products.
The following are some digital soil maps for the Regional Municipality of Ottawa
Ottawa soil texture maps from depths 0 - 5 cm, 5 - 15 cm, 15 - 30 cm, 30 - 60 cm, and 60 - 100 cm.
Ottawa soil texture map from depths 0 - 5 cm at a regional scale.
Aside from soil texture class, detailed predictive soil property maps can be created for a preferred scale and depth. The following are two map comparisons showing soil pH, soil organic carbon, cation exchange capacity, sand content, silt content, and clay content from a depth of 0 - 5 cm at the 1:20,000 v.s. 1:10,000 scale and the 1:10,000 v.s. 1:4,000 scale. These map comparisons illustrate the level of detail at both the regional and field scale that can be provided by PDSM.
Soil pH, soil organic carbon, cation exchange capacity, sand content, silt content, and clay content from a depth of 0 - 5 cm at the 1:20,000 v.s. 1:10,000 scale.
Soil pH, soil organic carbon, cation exchange capacity, sand content, silt content, and clay content from a depth of 0 - 5 cm at the 1:10,000 v.s. 1:4,000 scale.
5. PDSM Applications
OMAFRA uses predictive digital soil maps to create CLI updates, soil health assessments, nutrient loss and erosion models for Ontario. Their most important application is to provide sound information for land management decisions.
Predictive digital soil maps are important tools for:
- Producers
- Certified Crop Advisors
- Municipal Land Use Planners
- Agronomists
- Academia
- Realtors
PDSM has also become a powerful tool used to make crop management decisions. It is a valued asset in the field of Precision Agriculture, which aims to distinguish site specific management practices for farms so that economic gains can be maximized, while maintaining soil productivity. Sensory and GPS technologies are attached to farm machinery and collect precise information about crop health and yield. Information and maps gained from PDSM, in combination with yield maps, can be compared to determine relationships between soil properties and profitability or return on investment across that field.
Map courtesy Zonesmart - Author: Doug Aspinall.
For example, with detailed soil information at depth across a farm field, you can look at water availability by soil type and prescribe a more appropriate seeding rate for a field. For example, in landscape positions that are higher and drier with less topsoil perhaps due to erosion factors, less seed planted could reduce the competition for water and produce a more uniformly maturing crop.
For more information and examples of precision agriculture prescription maps click the links below. The first link is for a StoryMap displaying prescription maps for various farm fields, which includes elevation, soil conductivity, yield, target nitrogen rates, soil samples, and yield potential index layers. The second link is for a Field Crop News article that explains the context of the three year Grain Farmers Ontario - Precision Ag Advancement for Ontario Project.
Using PDSM and precision agriculture can assist a farmer in understanding the limitations of the soil in specific soil-landscape positions across a farm field and then change crop inputs to suit those areas in a more profitable manner. With the detail provided in PDSM, producers gain a deeper understanding of the nature of their field and best management practices (BMPs) can be implemented in areas to improve soil health.
To learn about how you can implement precision agriculture or BMPs seek out your local Certified Crop Advisor.
6. Interpreted Maps
Predictive mapping of soil properties opens the door to new interpreted map products. New innovative ways that soil maps can be used include:
- Soil moisture content and texture maps can improve how drainage and irrigation is done in fields.
- Bulk densities can be interpolated from soil texture maps to predict porosity and soil compaction risk.
A Land Classification System Designed for Agriculture
New PDSM maps can also be used to critically look at CLI ratings, which is an older system of land classification, and implement a system similar to Land Suitability Rating System (LSRS) that is a more powerful decision making tool for producers and municipal planners. The LSRS can be more effective at protecting prime agricultural land for sustainability by eliminating bias against what may be deemed a poorly suited agricultural soil. A soil good for growing a specific crop can also be unsuitable for growing a different type of crop.
7. Environmental Stewardship
Predictive digital soil maps promote environmental stewardship and sustainability. Through understanding the nutrients, water, and seed requirements of soils in a pin pointed location, the soil in the landscape can be supplemented precisely. This avoids issues like topsoil erosion, nutrient run off and organic carbon depletion that degrade a once healthy soil. It also aids to protect against the consequences of improper soil management leading to adverse environmental issues such as water eutrophication, increased atmospheric carbon dioxide, and soil compaction.
Advanced soil information also allows producers to grow crops in a wide range of soil environments, because if you know exactly what agricultural soil is lacking, precise inputs can be made.
Fertile soil is the foundation of Ontario’s agri-food industry. Conserving and improving the quality of Ontario’s agricultural soils is a way to ensure food security for Canadians.
