Soil is one of the most important factors that control crop yields and land potentials. There are many possible soils with different properties within a given location. How to correctly identify soils and the subsequent soil properties is critically important for farmers, natural resource managers, policy makers, and scientists to make decisions and predictions regarding land suitability, productivity, profitability, and sustainability.
In our effort to help make soil identification in the field easier, LandPKS has two team members, Zhaosheng Fan and Samira Pakravan, who are working on improving our current LandInfo module, as well as developing a completely new module, SoilColor. Fan and Samira are currently focused on, 1) developing algorithms that can be used to identify correct soils with spatial location (latitude and longitude) and other easily-measured field observations input by LandPKS users (e.g., soil texture by depth), and 2) developing a SoilColor module that can be used to measure soil color in the field with a smartphone camera. Soil color is one of the most important attributes of the soil which provides useful information about many other significant soil properties, such as soil organic carbon content. The SoilColor module will use smartphone camera images of soil samples to measure the soil color. Once complete, LandPKS users will be able to identify soil color without the use of expensive soil color books.
Further, the two efforts mentioned above are tied together – the measured soil color with the SoilColor module can, in turn, be used by the soil-identification algorithms to further improve the accuracy of the identified soils. Once the correct soils are identified, the corresponding soil properties will be used to drive crop models to simulate crop yields, erosion, and crop-failure risks. Please do look for the release of SoilColor in the near future!