Quantification and application of blue carbon by remote sensing: By reviewing current status of seagrass extraction using deep learning and toward its application to future forecasting

Abstract

Consideration of blue carbon is rapidly progressing, and mapping of seagrass/macroalgal beds on a broad scale is essential as a basis for these studies. Here, I introduce quantitative evaluation methods using remote sensing, and review recent applications of deep learning to seagrass beds. In addition, I would like to address the case studies how such mapped information can be addressed to predict future distribution of macrophyte beds in different socio economic and/or climate scenarios that includes carbon sequestration. Not only for the initiatives by UNFCC, these aspects will contribute on the international achievements of biodiversity targets and disclosures such as Kunming-Montreal Global biodiversity framework (KMGBF) and The Taskforce on Nature-related Financial Disclosures (TNFD). If it comes with the monitoring of the biodiversity and ecosystem services.