SOLAR3 intends to provide farmers, agronomists, and other agricultural experts with actionable intelligence they can use to decide on the amounts and locations of agrochemical doses for precision agriculture as well as to make other operational and strategic decisions. To this end, SOLAR3 is developing analytic maps for various crops during their growing cycles using hyper spectral imaging, satellite imagery, machine learning, and solar powered unmanned aerial vehicles (UAVs). The analytic maps highlight where in a field crops are impacted by biotic (such as weeds, pests, and diseases) and abiotic (such as Phosphorus, Potassium nutrient content and soil compaction) stresses. Additionally, SOLAR3 will provide growers with biomass maps for relative yield assessments, color pictures (RBG images), and NDVI.
SOLAR3 uses machine learning algorithms on hyper spectral and satellite imagery and ground-based data. To efficiently acquire the necessary data, SOLAR3 undertakes the development of the next generation Gamaya hyper spectral camera and next generation ETH Zurich solar powered UAV senseSoar to enable long-endurance aerial imagery capture.
SOLAR3’s targeted users are large industrial growers from Eastern Europe such as in Ukraine. Expansion to other countries and other crops will follow.
Ukrainian and other farmers need to know where in their field they should focus the application of expensive agro-inputs to achieve the highest yields possible year after year.
The SOLAR3 decision support system (DSS) requires frequently updated new data to assist farmers with their management and planning. To this end, SOLAR3 system includes a data acquisition platform: a long endurance unmanned aerial vehicle (pictured below) equipped with a lightweight and data-efficient hyper spectral camera. A set of algorithms that produce the various analytic maps processes these data. The analytics maps are delivered to customers via a cloud-and-web-based user interface (pictured below). Therefore, the SOLAR3 decision support system is an end-to-end solution for improved airborne monitoring and diagnostics of large-scale agricultural areas.
The use of space assets is necessary to fulfil the large-scale airborne hyperspectral agricultural monitoring task proposed within this project in an end-to-end manner, i.e. without assuming extensive pre-existing infrastructure on the ground. The following space technologies are used:
Satellite communication (SatCom) systems provide reliable infrastructure-independent global communication coverage. SatComs enable SOLAR³ to provide safe and easy-to-use agricultural mapping services that cover large-scale agricultural land areas. In SOLAR³ we develop and integrate a SatCom framework for use on lightweight small-scale Unmanned Aerial Systems such as the SOLAR³ aerial sensing system.
To provide stable and reliable aircraft position, attitude and velocity estimates, the aerial sensing platform implements state estimation that uses inertial measurement data which is corrected using GNSS position and velocity information. Support for the European GALILEO constellation is included.
SOLAR³ includes the development of a multi-scale methodology that takes full advantage of the continuously expanding fleet of space-borne remote sensing instruments, i.e. when advantageous, airborne and space-borne sensing methods can be used in a complementary way for situation analysis in the Decisions Support Information system.
SOLAR3 was started in December 2016. Currently, data is being collected during the growing season 2017 in Ukraine. The pilot being performed in 2017 includes HSI data acquisition with a current-generation HSI camera flown on a small-scale UAV platform. These data enable the development of the SOLAR3 analytics maps. Concurrently, the team is designing, assembling, and testing the solar-powered UAV and the next-generation hyper spectral sensor which will be used to collect data in the 2018 Ukrainian growing season.