Early Season Crop Classification and Crop Disease Risk Assessment Application
AUG is developing a unique web-based crop monitoring application with the support from Agriculture and Agri-Food Canada (AAFC) and the Canadian Space Agency (CSA). This application demonstrates interactive crop maps that provide field-by-field crop classification and corresponding growth stage distribution. It will automatically incorporate new satellite data into its analytics when available.
Other issues it covers are:
Management of Crop Fields:
Insurance Fraud Detection:
Due to a lack of regular crop field monitoring data, the inspectors often need to physically travel to crop fields. AUG’s technology addresses this through continuous monitoring of crop fields and by making of past data available to users for analysis.
Early Season Crop Classification:
AUG’s one-of-a-kind technology incorporates Growing Degree Days (GDD) data to ensure the technology is cross-region and cross-year compatible. As a result, there is no need for yearly ground-truth data collection, unlike current practices. The iterative procedure developed by AUG improves its estimates as more satellite data becomes available during crop season. The technology provides great estimates at any point based on all available data, rather than waiting for the end of season. Since the technology can incorporate any image data, its estimates improve as more satellites become available over time.
Crop Growth Stage Estimation and Prediction Technology
AUG’s state-of-the-art crop growth stage (phenological state) estimation and prediction technology is first-of-its-kind to effectively integrate images from space-borne electro-optical and Synthetic Aperture Radar (SAR) sensors, providing accurate phenology estimates for crop fields. This novel technology uses both optical and SAR data that are complementary in nature: optical images provide spectral information, e.g. greenness/yellowness indices, and SAR images provide structural information of crops, which is affected by crop height, stalk, canopy and leaves.
This robust, scalable, and proven technology makes it feasible to segment crop growing seasons and analyze periodic growth conditions (i.e. crop healthiness, dryness, leaf pigment, etc.) to any specific crop field. This technology is applicable for a wide range of crops including, but not limited to, corn, canola, soybeans, and wheat.
Image by Agriculture and Agri-Food Canada