Machine learning and deep learning for multi-temporal-spatial assessment of anthropogenic stressors on peatlands – A case study of Ireland
Date:
Presented comprehensive research on applying machine learning and deep learning techniques to assess anthropogenic stressors on peatland ecosystems using multi-temporal-spatial remote sensing data. The case study focused on Irish peatlands and demonstrated how advanced computational methods can detect and quantify human impacts on these critical ecosystems.
Co-authors: W. Habib, J. Connolly, K. McGuinness