Abstract
Ocean observation is one of the major parts of the global integrated observation system, where ocean remote sensing (or satellite oceanography) takes a key position. Nowadays, there are stronger requirements than ever that ocean remote sensing technology should make direct detection of three-dimensional (3D) stratification structure of the upper ocean. Traditional two-dimensional (2D) remote sensing, based on ocean color (OC), thermal infrared, and microwave sensors (radiometer, scatterometer, altimeter, and SAR, etc.), can only detect sea-surface or sea-skin properties, and then retrieve or deduce the profile-structures of the water body. Global Climate Observing System (GCOS) has defined 31 ocean variables as ECVs (Essential Climate Variables), which is identical to the EOVs (Essential Ocean Variables) defined by the Global Ocean Observation System (GOOS). But, only 11 in those 31 variables can be measured by traditional 2D remote sensing technologies, and yet with some accuracy or uncertainty problems. If 3D remote sensing technology could be developed, half a dozen more variables (namely the subsurface ones) would be acquired from space, which could bring forth great benefits to the ocean and earth observation system. Besides the observation subsurface variables, other critical defects of traditional 2D sensors are the inability of measuring the ecosystem activities and changes under low-light conditions, as that in the arctic ocean, and the incapability of monitoring the vast diel-vertical-migration of zooplankton at dawn/dusk and night. It seems that the active optical sensing system, i.e., the ocean profiling lidar or oceanographic lidar (not the ones for shallow water bathymetry or mapping), is currently the only feasible technology that can make direct 3D detection for the upper ocean profiles and work in a whole diel cycle to monitor the plankton activities to facilitate the studies of the life system in ocean. This paper aims to give an overall but concise review of the progress of ocean profiling lidar technology for the past 50 years, especially those of recent 15 years, including the theory, models, techniques, and preliminary experiments and applications practiced in-lab, in-situ and by airborne or spaceborne systems. The airborne oceanic lidar systems mainly refer to elastic polarimetric lidar or HSRL ones from NOAA or NASA, and the spaceborne lidars and their ocean profiling applications, refer mainly to the CALIOP onboard CALIPSO and the ATLAS onboard ICESat-II, though with limited sensing capability and coarse resolution. Some of the key issues of oceanographic lidar sensing are discussed, including the Mueller matrix, volume scattering function (VSF) of complex water constituents, blue-green dual-bands elastic polarimetric, the maximum detecting depth, inelastic scatterings (Brillouin, Raman), and the stringent engineering restraints, etc. The methods and mechanisms of oceanic lidar to probe the stratified bio-optic properties, NPP and carbon stocks of the euphotic layer, thermal structures of the upper ocean, plankton migration, fish flocks, air-sea interface properties, internal waves, etc., are given in the view of applications other than in that of instrumentation. The specific and effective applications, based on LiDAR's unique profiling and night-time sensing ability, include the sensing of changes in the arctic ocean ecosystem during the polar nights, and the vertical-diel-migration of zooplanktons, these are largely missing in traditional ocean color. Monte Carlo (MC) models are powerful and versatile tools for the researches and system designs of oceanic lidars. Lidar MCs are capable of dealing with ray-tracing and polarimetric radiative transfer in a real-3D time and space frame. The MC models from distinguished research groups in ocean optics and lidar sensing are briefly reviewed. From the early 1990s, though left behind by international counterparts in some degree, Chinese experts on oceanographic lidar technology have also made many achievements in almost every aspect concerned, which are reviewed also in this paper. One of the outstanding achievements is the ~90m world record of the deepest detection depth in May 2019, obtained in the Southern China Sea by an airborne lidar system-the blue-green dual-bands oceanic lidar, developed jointly by SIOM/CAS and other institutes. The successful launch of CALIPSO-CALIOP in 2006 was the dawn of spaceborne oceanographic lidar technology. With CALIOP's residual subsurface signals of backscattering, some tremendous oceanic applications have tried out and well demonstrated the necessity and revolutionary contributions of dedicated future spaceborne missions of oceanic lidar sensing. The technology of lasers and receivers for spaceborne system is much more matured and feasible than 15 years before, at least for the elastic polarimetric profiling lidar. As simulated by various Monte Carlo models, the detection depth of an affordable and engineeringly reliable oceanic lidar, no matter elastic, HSRL, or inelastic, is quite limited within 100m to 150 m with a vertical resolution of 1m or less. This depth may not be satisfactory to those serious oceanographers, but the ability of upper ocean profiling is definitely a break-through of the three dimensional ocean sensing technology. This depth may penetrate over 80% of the global euphotic zone or photosynthetic depth in which most of the ocean-NPP is originated. Along with the introduction of the Guanlan (means watching the waters) satellites project, an ocean science mission focused on three dimensional sensing of the upper ocean and sub-mesoscale phenomena, proposed and initiated by the National Laboratory of Marine Science & Technology (Qingdao), a road-map of oceanographic profiling lidar series is suggested in 4 stages, from elastic, HSRL, Brillouin and multi-beam push-broom. As the primary and promising candidate sensor of 3D ocean sensing, spaceborne oceanic profiling lidar can be realized in near future. Technically, China has the ability and chance to be the leading runner.
Author supplied keywords
Cite
CITATION STYLE
Tang, J., Chen, G., Chen, W., Zhao, C., He, Y., Wu, S., … Gu, Y. (2021). Three dimensional remote sensing for oceanography and the Guanlan ocean profiling Lidar. National Remote Sensing Bulletin, 25(1), 460–500. https://doi.org/10.11834/jrs.20210495
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.