Algorithm for Identifying Agricultural Practices
Function
The Algorithm for Identifying Agricultural Practices is a cutting-edge tool designed to detect and classify agricultural activities such as cover cropping, crop residue management, and land-use changes using satellite image time series. By leveraging spectral indices derived from Sentinel-2 imagery, the algorithm supports climate-smart agriculture by enhancing Measurement, Reporting, and Verification (MRV) systems for greenhouse gas (GHG) flux estimation and carbon farming initiatives.
This tool enables precise monitoring of sustainable farming practices, empowering farmers and policymakers to make data-driven decisions that align with carbon neutrality goals and promote regenerative agriculture.
Utility
Practical application:
- Precision Agriculture: Farmers can use the algorithm to monitor crop health, optimize irrigation schedules, and implement cover cropping strategies to improve soil carbon content
- Policy Implementation: Policymakers can utilize the tool to track compliance with environmental regulations and incentivize sustainable practices through subsidies or carbon credit programs
- Research and Development: Researchers can analyze large-scale agricultural trends, validate field observations, and develop predictive models for climate resilience planning
Beneficiaries
- Farmers: Gain actionable insights into their agricultural practices to enhance productivity and sustainability
- Policymakers: Access reliable data to design evidence-based policies and track progress toward climate goals
- Researchers and Agronomists: Use the tool to study land-use changes, GHG emissions, and the effectiveness of regenerative practices
Status
Completed and in use.
Last update: November 2024
Access
Follow this link to access. Open
access