| Popis: |
The potential of the blue economy has been widely debated in the past decade for the country's economic growth, improving resource use, creating livelihoods, and protecting the ocean through sustainable use. Satellite Oceanography for a sustainable blue economy has been researched over the past five decades. The last decade of a surge in space technology for coastal regions is driven by new high-resolution satellite sensors and advances in processing capabilities of modern generation computers, especially by applying machine learning algorithms to large amounts of Geo-Hydrospatial data. The significant data processing capabilities offer the advantage of synthesizing existing knowledge from several domains into a unified approach that may boost the blue economy through prediction of accurate bathymetry, estimation of water column parameters (WQP) & bottom composition, and derived products based on WQP. The progress made in the last few years has enhanced the prospect of having more precise, real-time, operational products based on satellite oceanography. However, relatively few applications have been operationalized based solely on satellite oceanography data due to barriers of in-situ data for validation, and constraints raised by sensors & techniques in coastal waters. We investigated the recent satellite oceanographic studies on retrieval of WQP and their application in blue economic activities. The various challenges in deriving WQP for a sustainable blue economy, habitat mapping, and other coastal applications have been discussed to identify the knowledge gaps and challenges. The opportunity areas like Diving Operation, Military Application, etc., where relatively less theoretical knowledge exists, have been elaborated based on the WQP relationship. We have suggested an emerging need for data integration from various sources, overcoming challenges and limitations in WQP retrieval to operationalize blue economy products. |
