# Advances in Remote Sensing and Propulsion Systems for Earth Observation Nanosatellites
## 3 Earth Observation
### Oceanography Monitor  
Oceanography monitoring has traditionally relied on large, costly satellites to gather data for climate studies, maritime surveillance, and ocean health assessments. However, nanosatellites offer a promising alternative, providing high spatial resolution and near-real-time data for coastal and offshore environments. This Section highlights studies that utilize nanosatellites to monitor oceanic features such as water quality, bathymetry, coral reefs, and benthic habitats. Satellite Oceanography (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. [PERSON] and [PERSON] [33] have proposed a comprehensive historical technical research study on SO evolution over the past four decades. This study has significantly advanced our understanding and monitoring of the world's oceans. With the capability to provide near real-time support for operational oceanography and climate change studies, SO has become instrumental in mitigating the negative impacts of climate change and safeguarding industries such as aquaculture, fisheries, and environmental protection. Furthermore, SO enhances maritime situational awareness and surveillance, aiding in monitoring shipping routes and combating illegal activities like piracy. The future of satellite oceanography lies not only in the intricacies of space engineering or the size of satellites but also in the continuous innovation and deployment of new technologies. [PERSON] et al. [34] proposed a method to improve the accuracy of normalized water-leaving radiance (nLw) estimates from commercial nanosatellite-based Earth-observing \begin{table}
\begin{tabular}{c c c} \hline \hline
**Method Used** & **Evaluation Metric** & **Reference** \\ \hline Feasibility analysis of Copernicus and Hyperspectral data for coastal water quality monitoring. & Nanosatellite solution suitable for short-term, Broadering market perspectives. & [27] \\ \hline Design and analysis of nanosatellite constellation for Baltic Sea water quality monitoring. & Efficient coverage achieved, Increased measurement frequency. & [28] \\ \hline Assessment of CubeSat Rrs for inland water studies, focusing on fine-scale monitoring. & Significant correlations with water quality parameters, Potential for fine-scale monitoring. & [29] \\ \hline Monitoring subseasonal Arctic-Boreal surface water fluctuations using CubeSat sensors. & Significance in capturing local-scale phenomena highlighted. & [30] \\ \hline Tracking river ice floes with PS constellation, advancing understanding of river dynamics. & Significant advancement in river dynamics sensing, Promise for integrated river system understanding. & [31] \\ \hline Mapping water turbidity with CubeSats, using DSF method for accurate retrieval. & Excellent agreement with in situ measurements, Promising for turbidity estimation. & [32] \\ \hline \hline \end{tabular}
\end{table} 
Table 5: EO methods used for inland monitoring. sensors, focusing mainly on Planet nanosatellite sensors. The absence of a second near-infrared band makes atmospheric correction over oceanographic regions challenging. However, the study demonstrates the successful vicarious calibration of Planet sensors and the duplication of their red band for aerosol model selection and bio-optical ocean product algorithms. Although the sample size and data availability are limited, the study highlights the effectiveness of the proposed approach in improving nLw measurements. The results show promising avenues for future research, including using upcoming sensors with increased wavelength bands for improved calibration and validation.