# Advances in Remote Sensing and Propulsion Systems for Earth Observation Nanosatellites
## 3 Earth Observation
### Oceanography Monitor
Furthermore, the high spatial resolution of Dove sensors provides valuable insights into near-shore areas, enabling detailed analyses of water quality and oceanic features previously inaccessible with coarser-resolution sensors. [PERSON] et al. [35] propose a method using PS imagery for accurately mapping the distribution of Submerged Aquatic Vegetation (SAV) and estimating Sargassum biomass in An Chan coastal waters, Tuy An district, Phu Yen province, Vietnam. The authors' approach integrates Sagawa's Bottom Reflectance Index (BRI) algorithm with Tassan's concept of discriminating light attenuation coefficients, achieving remarkable accuracy in mapping SAV, including Sargassum meadows, with an overall accuracy of 92.52% and a Kappa coefficient of 0.8957. The results show that the BRI red band has the highest accuracy, with R\({}^{2}\) = 0.9707 and RMSE = \(\pm\) 109.21 g/m\({}^{2}\). [PERSON] et al. [36] propose a methodology for monitoring and assessing rapid changes in coral reef ecosystems within the Spratly archipelago of the South China Sea. The authors utilize daily coverage from the Planet Dove satellite constellation at 3-5 m resolution to accurately map coral reef extent and identify key habitat features in remote atolls. The results verify the feasibility of using Planet Dove data to monitor observable deep reef cover, shallow reef cover, and sand, which are essential for informed conservation efforts and natural resource management. [PERSON] et al. [37] used the PS CubeSats to calculate Satellite-derived Bathymetry (SDB). The authors evaluate the efficacy of PS CubeSats in generating SDB and assess its compliance with the International Hydrographic Organization's standards for navigation map inclusion. Furthermore, the results obtained through an empirical method show promising accuracy, particularly in shallow waters, meeting the stringent requirements set by maritime regulatory bodies. [PERSON] and [PERSON] [38] conducted an assessment of PS multi-temporal images for mapping benthic habitat and seagrass species. PS's images have high spatial resolution, radiometric resolution, and near-daily temporal coverage, and PS offers a robust tool for monitoring dynamic changes in coastal ecosystems. The results show consistent performance across different images and highlight its utility in minimizing temporal bias, which is crucial for mapping dynamic objects in tropical regions. However, the accuracy of benthic habitat mapping needs to catch up to comparable platforms, and the results for seagrass species mapping are on par with established high-resolution satellites like Quickbird and WorldView-2. SO has evolved significantly over the past four decades, deepening our understanding of the world's oceans and improving our ability to monitor them effectively. Ongoing innovation in the field, including improvements in sensor accuracy and mapping of oceanic features, has practical applications in conservation, resource management, and environmental protection efforts. Innovating and collaborating in SO is essential for a sustainable future. Table 6 summarizes the methods used and evaluation metrics for each study regarding oceanography monitoring.