Information from above

The quest is on to obtain more detailed soil type and topography data on Ontario croplands from satellites

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If farm agencies in Ontario were to make an information wish list, it would likely include detailed and up-to-date soil and topographical data.

This information would, among other things, help farmers to achieve higher yields through better crop management, says Ontario Federation of Agriculture President Keith Currie.

Why it matters: Ontario’s soil maps are many years out of date and better data are needed to help with precision farming applications.

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At the provincial level, Currie says that this data would also improve understanding of primary areas for growing various crops and certain programs might then be tailored to certain areas.

“It might also help with better management of DON outbreaks, for example, and better tailoring of crop insurance.”

The data would also help urban planners decide where buildings should be placed.

Some municipalities and conservation authorities already have local soil and topographical data collected, and Currie says OMAFRA (the Ontario Ministry of Agriculture, Food & Rural Affairs) also has some.

“Getting data together for the entire growing area of Ontario is somewhat of a provincial matter, but perhaps Agriculture and Agri-Food Canada (AAFC) could play a role in gathering and aggregating data,” he says.

The previous Liberal government had started to fund a long-term project to create new soil maps for Ontario.

Federal government plays a role, with an eye in the sky

Dr. Andrew Davidson, manager of Earth Observation (EO) Operations at AAFC agrees that detailed soil survey and topographical mapping would be valuable on many levels.

Davidson says the federal government is creating high-resolution elevation (topographical) data coverage for Canada using various satellite and airborne remote sensing techniques.

“But Canada is a big country and this is neither cheap nor easy,” he says.

In the southern part of Canada, where more accurate elevation data are needed for forest inventory, flood plain mapping and precision agriculture, the mapping of elevation primarily relies upon airborne LiDAR (Light Detection and Ranging).

Here, Davidson says the federal government is working with the provinces and territories to free-up existing airborne LiDAR data and to participate in new acquisitions.

There is also a lot of soil-and-crop-related AAFC satellite data that is already accessed by farmers, indirectly. It’s provided free of charge to Statistics Canada and other governmental agencies and distributed through reports to the public.

It is also provided for free to private companies, such as farm media firms and precision agriculture providers, which use it in their publications and services.

This includes data used in the Statistics Canada Crop Condition Assessment Tool (measurements of various portions of the electromagnetic spectrum allows for distinguishing vegetation from water, bare soil, snow and also to some extent, for determining the condition of vegetation) and weekly AAFC vegetation index (NDVI) maps of Canadian growing regions throughout the growing season.

It also includes data that goes into the weekly AAFC national maps of surface soil moisture, and the Canadian Crop Yield Forecasting Model, which is used to produce in-season crop production estimates.

Xiaoyuan Geng, head soil scientist at the Canadian Soil Information Service (CanSIS) of AAFC’s Science and Technology Branch, says that AAFC has attempted with provincial partners, to create provincial seamless digital soil type maps to replace the many individual detailed map sheets that have been produced at a range of scales and cover local, county or rural municipal jurisdictions.

However, he notes that soil is a dynamic natural resource and soil information needs to be up-to-date and customized if it is going to be useful for farmers, especially for use in precision farming.

To that end, during the last decade, the traditional soil surveys have been gradually replaced with software-based predictive soil mapping (PSM) approaches that involve powerful software programs (machine learning), statistics and satellite imagery.

Geng says that PSM software takes results of soil tests at various geographical points and predicts what types of soil will be found in other nearby areas, using soil-related factors such as climate, vegetation and topography.

More data, however, could come from farmers themselves.

Geng points to a free crowd-sourcing platform for farmers in Europe call OneSoil, where farmers can access information about their soils from machine learning analysis of satellite images, and also share data about their soils and what they are adding to them. Geng hopes that a similar user-friendly platform could be developed for Canada.

There is also the possibility that someday, data gathered by individual farmers about their soil through their use of precision services could be shared with AAFC and more for the benefit of all.

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