AgriTrack Full DSS Stack is a project co-funded by the European Space Agency aiming to develop an innovative product on the frontier of Farm Management Systems. The Full DSS will be an advanced Decision Support System (DSS) able to combine modeling and remote sensing historical information to diagnose the hot spots of vegetative stress highlighted by remote sensing.
The goals
The ambition is to overcome the two main problems of agricultural DSS:
- information overload;
- lack of spatial information and practical prescription.
The central idea behind this product lies in its ability to integrate traditional DSS with spatialization. As a matter of fact, satellite data collected and elaborated by AgTech platforms can typically identify general issues within the field (such as areas with reduced vigor), but often fall short in providing precise diagnoses on the gravity of the problem and its underlying causes.
On the other hand, traditional DSS can provide specific information on single issues, such as field water or nutrients needs, pest risks, but referring to the whole field lack differentiation between the areas, which may present different issues.
With the advanced DSS, all the information will be integrated, providing tempestive feedback on what is happening in the field, where it is happening and why, along with explanations and agronomic advice.
The ambition is to overcome the two main problems of agricultural DSS:
- information overload;
- lack of spatial information and practical prescription.
The central idea behind this product lies in its ability to integrate traditional DSS with spatialization. As a matter of fact, satellite data collected and elaborated by AgTech platforms can typically identify general issues within the field (such as areas with reduced vigor), but often fall short in providing precise diagnoses on the gravity of the problem and its underlying causes.
On the other hand, traditional DSS can provide specific information on single issues, such as field water or nutrients needs, pest risks, but referring to the whole field lack differentiation between the areas, which may present different issues.
With the advanced DSS, all the information will be integrated, providing tempestive feedback on what is happening in the field, where it is happening and why, along with explanations and agronomic advice.
Advantages for the actors of the agrifood chain
AgriTrack Full DSS Stack will be able to support a wide range of stakeholders with direct and indirect benefits. In an environment characterized by ever-evolving environmental and economic conditions, stakeholders in the agronomic sector increasingly require the ability to identify critical areas within fields and deploy immediate interventions.
Farmers will be able to enhance farm profitability through optimized input usage and reduce environmental impact; associations, cooperatives, and consortia will be able to leverage the tool for data collection, field monitoring, and agronomic support across several farms.
On this regard, AgriTrack Full DSS Stack will be able to respond to their need to take agronomic decision making based on reliable and spatialized information, improve the monitoring and data collection from several fields and farms, while being able to obtain tangible and reported results.
On the technical point of view, the Full DSS will leverage both existing and new model outputs and collected data (such as satellite and in-situ sensors) to generate a probabilistic diagnosis of agronomic issues affecting specific areas within identified critical fields. This entails testing various Machine Learning and data fusion approaches as predictive tools, drawing from Agricolus’ extensive smart farming experience.
