In addition to our rainfall feature, which helps you assess the rain potential and risk from the sky above, our soil maps have a similar purpose for the soil below. By having a view of the behavior and characteristics of soil in a region, we begin to understand what regions may be better for certain farming objectives. This Feature can help buyers and lenders build up their knowledge and identify high-risk or low-risk areas. The soil feature includes a handful of soil attributes: sand, silt clay, organic carbon, pH, and available water captivity. These attributes are great if you are an agronomist, but, for everyone else, how do we know which is "better"?
A good rule of thumb guide is:
On Agtuary's national map, users can filter these values by using the following soil layers:
But what about sand, silt, and clay? How do we know what the best values are for them?
"Loam soils are best for plant growth because sand, silt, and clay together provide desirable characteristics… ...the different-sized particles leave spaces in the soil for air and water to flow and roots to penetrate" - Geographies of the United States
At Agtuary, we invented the 'Loamyness' soil value. Loamyness is an abstraction of the combination of sand, silt, and clay to make a 1D scale where 0 is least loamy and 100 is the loamiest; defined, in our case, as a perfect balance of sand, silt, and clay.
By selecting Loamyness, a special insight appears on our national map. Most regions with higher Loamyness share their occupation within the Australian wheat belt! This correlation shows that growers have tended toward these areas and succeeded because of the ideal soil conditions.
We should mention the limitations of this Feature. This Feature is not a replacement for a sub-paddock-level understanding of soil. Instead, it provides a macro-level snapshot of the typical soil characteristics in the region. The data that is used to build up these maps and plots comes from this global gridded soil information.
A 250m grid of machine-learning predicted soil attributes. Because the soil attributes values come from models, the values are limited to the predictions. Therefore, it's best to use the data to get a general understanding of the area rather than a detailed view of the soil.
As more Agtuary features come down the pipeline, we are looking to build up our metrics dashboard so that users can compare properties easily based on these underlying features. If you'd like to come on this journey with us, check out the product so far and give us your opinion, sign up here!
