Abstract

We highlight three emerging NASA optical technologies that enhance our ability to remotely sense , analyze, and explore ocean worlds – FluidCam and fluid lensing, MiDAR, and NeMO-Net. Fluid lensing is the first remote sensing technology capable of imaging through ocean waves without distortions in 3D at sub-cm resolutions. Fluid lensing and the purpose-built FluidCam CubeSat instruments have been used to provide refraction-corrected 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs). Results from repeat 2013 and 2016 airborne fluid lensing campaigns over coral reefs in American Samoa present a promising new tool for monitoring fine-scale ecological dynamics in shallow aquatic systems tens of square kilometers in area. MiDAR is a recently-patented active multispectral remote sensing and optical communications instrument which evolved from FluidCam. MiDAR is being tested on UAVs and autonomous underwater vehicles (AUVs) to remotely sense living and nonliving structures in light-limited and analog planetary science environments. MiDAR illuminates targets with high-intensity narrowband structured optical radiation to measure an object’s spectral reflectance while simultaneously transmitting data. MiDAR is capable of remotely sensing reflectance at fine spatial and temporal scales, with a signal-to-noise ratio 10-103 times higher than passive airborne and spaceborne remote sensing systems, enabling high-framerate multispectral sensing across the ultraviolet, visible, and near-infrared spectrum. Preliminary results from a 2018 mission to Guam show encouraging applications of MiDAR to imaging coral from airborne and underwater platforms whilst transmitting data across the air-water interface. Finally, we share NeMO-Net, the Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment. NeMO-Net is a machine learning technology under development that exploits high-resolution data from FluidCam and MiDAR for augmentation of low-resolution airborne and satellite remote sensing. NeMO-Net is intended to harmonize the growing diversity of 2D and 3D remote sensing with in situ data into a single open-source platform for assessing shallow marine ecosystems globally using active learning for citizen-science based training. Preliminary results from four-class coral classification have an accuracy of 94.4%. Together, these maturing technologies present promising scalable, practical, and cost-efficient innovations that address current observational and technological challenges in optical sensing of marine systems.

Highlights

  • Our planet’s habitability depends on the health and stability of its largest ecosystem, the global ocean

  • As higher-power kWclass MiDAR transmitters are matured, there are a number of potential applications of this technology to Earth and Space Sciences including high-resolution nocturnal and diurnal multispectral imaging from air, space and underwater environments as well as optical communication, bidirectional reflectance distribution function characterization, mineral identification, UV-band imaging, 3D reconstruction using structure from motion, and active fluid lensing for imaging deeper in the water column (Figure 11)

  • The three emerging NASA technologies shared here begin to address some of the ongoing observational, technological, and economic challenges encountered in marine sensing, as they apply to coral reef ecosystems

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Summary

Introduction

Our planet’s habitability depends on the health and stability of its largest ecosystem, the global ocean.

Results
Conclusion

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