Portable Remote Imaging Spectrometer Research Articles

Detection and Sourcing of CDOM in Urban Coastal Waters With UV-Visible Imaging Spectroscopy

Ultraviolet (UV)-visible imaging spectroscopy is an emerging and highly anticipated technology, expected to improve the remote sensing of coastal waters and expand its range of applications. Upcoming NASA satellite missions including PACE and GLIMR will feature imaging spectrometers capable of measuring hyperspectral remote-sensing reflectance (Rrs) across the visible range and well into the near-infrared and ultraviolet domains. The availability of UV reflectance is expected to facilitate the remote sensing of chromophoric dissolved organic matter (CDOM) in optically complex waters, thereby improving coastal water-quality monitoring. Although this argument is well supported by the dominance of CDOM absorption in the UV domain, few studies have directly evaluated the potential advantages conferred by UV reflectance for monitoring CDOM-related coastal water quality. Here, we took advantage of a 6-week wastewater diversion event in Santa Monica Bay, California in 2015 and the availability of Portable Remote Imaging SpectroMeter (PRISM) imagery acquired during the diversion to assess if UV-visible imaging spectroscopy could facilitate the detection of CDOM and help differentiate wastewater effluent-derived CDOM from other sources. A comparison of local empirical algorithms with varying amounts of spectral information implemented on PRISM data showed that incorporating UV Rrs as a predictor significantly improved retrieval of CDOM absorption coefficients (ag). Optimal performance was reached when combining Rrs(365), Rrs(400), and Rrs(700) as predictors of ag in a multiple linear regression. The use of the entire UV-visible spectrum (365–700 nm) in a partial-least-squares regression (PLSR) did not improve retrievals, indicating that a few carefully chosen predictors in the UV-visible domain were sufficient to empirically differentiate CDOM from phytoplankton in coastal waters minimally influenced by sediments or bottom reflectance. Finally, the development of a new fluorescence-based indicator of effluent-derived CDOM (effluent fluorescence ratio, EFR) helped demonstrate the feasibility of remotely detecting CDOM from wastewater. A PLSR-based algorithm using Rrs(365–700) provided reasonable EFR retrievals and successfully identified effluent-derived CDOM at the wastewater outfall when implemented on PRISM imagery. Although further work should investigate the influence of effluent-CDOM fluorescence on Rrs more mechanistically, these results confirmed that UV-visible imaging spectrometers can facilitate coastal CDOM-related water quality monitoring and expand its range of applications.

Pushing the Limits of Seagrass Remote Sensing in the Turbid Waters of Elkhorn Slough, California

Remote sensing imagery has been successfully used to map seagrass in clear waters, but here we evaluate the advantages and limitations of different remote sensing techniques to detect eelgrass in the tidal embayment of Elkhorn Slough, CA. Pseudo true-color imagery from Google Earth and broadband satellite imagery from Sentinel-2 allowed for detection of the various beds, but retrievals particularly in the deeper Vierra bed proved unreliable over time due to variable image quality and environmental conditions. Calibrated water-leaving reflectance spectrum from airborne hyperspectral imagery at 1-m resolution from the Portable Remote Imaging SpectroMeter (PRISM) revealed the extent of both shallow and deep eelgrass beds using the HOPE semi-analytical inversion model. The model was able to reveal subtle differences in spectral shape, even when remote sensing reflectance over the Vierra bed was not visibly distinguishable. Empirical methods exploiting the red edge of reflectance to differentiate submerged vegetation only retrieved the extent of shallow alongshore beds. The HOPE model also accurately retrieved the water column absorption properties, chlorophyll-a, and bathymetry but underestimated the particulate backscattering and suspended matter when benthic reflectance was represented as a horizontal eelgrass leaf. More accurate water column backscattering could be achieved by the use of a darker bottom spectrum representing an eelgrass canopy. These results illustrate how high quality atmospherically-corrected hyperspectral imagery can be used to map eelgrass beds, even in regions prone to sediment resuspension, and to quantify bathymetry and water quality.

A unified approach to estimate land and water reflectances with uncertainties for coastal imaging spectroscopy

Coastal ecosystem studies using remote visible/infrared spectroscopy typically invert an atmospheric model to estimate the water-leaving reflectance signal. This inversion is challenging due to the confounding effects of turbid backscatter, atmospheric aerosols, and sun glint. Simultaneous estimation of the surface and atmosphere can resolve the ambiguity enabling spectral reflectance maps with rigorous uncertainty quantification. We demonstrate a simultaneous retrieval method that adapts the Optimal Estimation (OE) formalism of Rodgers (2000) to the coastal domain. We compare two surface representations: a parametric bio-optical model based on Inherent Optical Properties (IOPs); and an expressive statistical model that estimates reflectance in every instrument channel. The latter is suited to both land and water reflectance, enabling a unified analysis of terrestrial and aquatic domains. We test these models with both vector and scalar Radiative Transfer Models (RTMs). We report field experiments by two airborne instruments: NASA's Portable Remote Imaging SpectroMeter (PRISM) in an overflight of Santa Monica, California; and NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) in an overflight of the Wax Lake Delta and lower Atchafalaya River, Louisiana. In both cases, in situ validation measurements match remote water-leaving reflectance estimates to high accuracy. Posterior error predictions demonstrate a closed account of uncertainty in these coastal observations.

Remote Sensing of Chlorophyll Fluorescence in the Ocean Using Imaging Spectrometry: Toward a Vertical Profile of Fluorescence

AbstractChlorophyll fluorescence measurements provide valuable information on phytoplankton abundance and physiology. High spectral resolution measurements from the aircraft‐mounted Portable Remote Imaging SpectroMeter (PRISM) allow for a more robust and informative fluorescence measurement than previous methods. An increase in radiation in the fluorescence wavelength range is approximated by a skew‐normal distribution. Positive skew suggests the influence of water attenuation and motivates the use of an inverse retrieval model to solve for the most likely vertical distribution of fluorescence quantum yield. This approach is tested with theoretical fluorescence profiles and applied to a PRISM flightline located in southern Drake Passage, Southern Ocean during austral summer. The resulting profiles suggest vertical structure in fluorescence quantum yield in the upper 10 m, which matches expectations from in situ studies. The framework developed in this paper can be applied to current and future satellite missions, providing more information on phytoplankton concentrations, vertical profiles, and physiology.

Regularization destriping of remote sensing imagery

Abstract. We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (NPP) orbiter, and an airborne grating spectrometer, the Jet Population Laboratory's (JPL) hyperspectral Portable Remote Imaging Spectrometer (PRISM) sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during the destriping process. The target functional penalizes the neighborhood of stripes (strictly, directionally uniform features) while promoting data fidelity, and the functional is minimized by solving the Euler–Lagrange equations with an explicit finite-difference scheme. We show the accuracy of our method from a benchmark data set which represents the sea surface temperature off the coast of Oregon, USA. Technical details, such as how to impose continuity across data gaps using inpainting, are also described.

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

AbstractReducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one‐dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea‐level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView‐2, and hyperspectral airborne imagery. Landsat 8‐derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field‐measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8‐measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing‐based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape‐scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

High-Resolution Remote Sensing of Water Quality in the San Francisco Bay-Delta Estuary.

The San Francisco Bay-Delta Estuary watershed is a major source of freshwater for California and a profoundly human-impacted environment. The water quality monitoring that is critical to the management of this important water resource and ecosystem relies primarily on a system of fixed water-quality monitoring stations, but the limited spatial coverage often hinders understanding. Here, we show how the latest technology in visible/near-infrared imaging spectroscopy can facilitate water quality monitoring in this highly dynamic and heterogeneous system by enabling simultaneous depictions of several water quality indicators at very high spatial resolution. The airborne portable remote imaging spectrometer (PRISM) was used to derive high-spatial-resolution (2.6 × 2.6 m) distributions of turbidity, and dissolved organic carbon (DOC) and chlorophyll-a concentrations in a wetland-influenced region of this estuary. A filter-passing methylmercury vs DOC relationship was also developed using in situ samples and enabled the high-spatial-resolution depiction of surface methylmercury concentrations in this area. The results illustrate how high-resolution imaging spectroscopy can inform management and policy development in important inland and estuarine water bodies by facilitating the detection of point- and nonpoint-source pollution, and by providing data to help assess the complex impacts of wetland restoration and climate change on water quality and ecosystem productivity.

A physics-based method for the remote sensing of seagrasses

Abstract Seagrass meadows are important environments for the blue carbon budget and are potential early indicators for environmental change. Remote sensing is a viable monitoring tool for spatially extensive meadows but most current approaches are limited by the requirement for in situ calibration data or provide categorical level maps rather than quantitative estimates of direct physiological significance. In this paper we present a method for mapping water depth and the leaf area index (LAI, ratio of leaf area to substrate area) of Thalassia testudinum meadows, based on radiative transfer model inversion using an embedded three-dimensional aquatic canopy model. Variations in reflectance due to leaf length, leaf position, sediment coverage on leaves, water depth and solar zenith angle were included in the model to parameterise uncertainty propagation. The model revealed canopy reflectance as a function of LAI decreases exponentially at all wavelengths up to an LAI around four, beyond which increasing canopy density cannot be determined from reflectance. In addition, sediment coverage on leaves has surprisingly little effect on the reflectance of sparse canopies because shading is also a contributor to darkening. The capability of the method for image based mapping was assessed through sensitivity analyses and by application to hyperspectral airborne imagery of Florida Bay collected by the Portable Remote Imaging Spectrometer (PRISM), with the uncertainty propagation providing per-pixel confidence intervals on all the estimated parameters. Results were consistent across the sensitivity and image analyses and the agreement with field data was good, given the challenges in validation of submerged pixels at metre scale. Uncertainties were high for LAIs greater than two in water of depth 8 m, but lower for sparse canopies and shallower water. For water depths approaching 10 m the pixel-to-pixel variation arising from processes at the water surface upwards was greater than the uncertainties arising from the canopy or water column. The physics-based model inversion approach is readily adaptable to any sensor configuration and to different seagrass species and canopy morphologies. No site-specific in situ data is required and the uncertainty estimates can provide an objective basis for interpreting apparent changes in the distribution of seagrasses over time and space, as revealed by remote sensing techniques.

Optimizing irradiance estimates for coastal and inland water imaging spectroscopy

AbstractNext generation orbital imaging spectrometers, with advanced global remote sensing capabilities, propose to address outstanding ocean science questions related to coastal and inland water environments. These missions require highly accurate characterization of solar irradiance in the critical 380–600 nm spectral range. However, the irradiance in this spectral region is temporally variable and difficult to measure directly, leading to considerable variance between different models. Here we optimize an irradiance estimate using data from the NASA airborne Portable Remote Imaging Spectrometer (PRISM), leveraging spectrally smooth in‐scene targets. We demonstrate improved retrievals for both PRISM and the Next Generation Airborne Visible Infrared Imaging Spectrometer.

Hyperspectral discrimination of floating mats of seagrass wrack and the macroalgae Sargassum in coastal waters of Greater Florida Bay using airborne remote sensing

Floating mats of vegetation serve to transfer biomass, nutrients and energy across marine habitats and alter the spectral properties of the sea surface. Here, spectral measurements from the airborne Portable Remote Imaging Spectrometer (PRISM) imagery at 1-m resolution and experimental mesocosms were used to assess the hyperspectral properties of the macroalgae Sargassum and aggregations of the seagrass Syringodium filiforme wrack in Greater Florida Bay. A simple Normalized Difference Vegetative Index (NDVI) effectively discriminated the presence of vegetation floating on the sea surface. The Sargassum Index derived from reflectance ratios at 650 and 630nm was used to effectively discriminate Sargassum from Syringodium wrack. Mesocosm spectral measurements revealed an initial lowering of wrack reflectance over the first 3days followed by a subsequent increase in reflectance over the next 8days. The age of the wrack estimated from 2 to 5days was best characterized using narrowband indices of the water absorption feature at 930 and 990nm potentially from increasing water content in wrack leaves over time. Hyperspectral imagery (<10nm) was necessary to differentiate between these two types of floating vegetation and assess age of the wrack. PRISM imagery revealed seagrass wrack organized in 5–35m spaced windrows caused by Langmuir circulation. Wrack was only detectable at 60mpixel resolution when densities were high and individual windrows were in close proximity.

Portable Remote Imaging Spectrometer coastal ocean sensor: design, characteristics, and first flight results

The design, characteristics, and first test flight results are described of the Portable Remote Imaging Spectrometer, an airborne sensor specifically designed to address the challenges of coastal ocean remote sensing. The sensor incorporates several technologies that are demonstrated for the first time, to the best of our knowledge, in a working system in order to achieve a high performance level in terms of uniformity, signal-to-noise ratio, low polarization sensitivity, low stray light, and high spatial resolution. The instrument covers the 350-1050nm spectral range with a 2.83nm sampling per pixel, and a 0.88mrad instantaneous field of view, with 608 cross-track pixels in a pushbroom configuration. Two additional infrared channels (1240 and 1610nm) are measured by a spot radiometer housed in the same head. The spectrometer design is based on an optically fast (F/1.8) Dyson design form coupled to a wide angle two-mirror telescope in a configuration that minimizes polarization sensitivity without the use of a depolarizer. A grating with minimum polarization sensitivity and broadband efficiency was fabricated as well as a slit assembly with black (etched) silicon surface to minimize backscatter. First flight results over calibration sites as well as Monterey Bay in California have demonstrated good agreement between in situ and remotely sensed data, confirming the potential value of the sensor to the coastal ocean science community.

Development and testing of an innovative two-arm focal-plane thermal strap (TAFTS)

Temperature control of optical focal planes comes with the intrinsic challenge of creating a pathway that is both extremely flexible mechanically and highly conductive thermally. The task is further complicated because science-caliber optical focal planes are extremely delicate, yet time, cost, and their unique nature means that their mechanical resiliency is rarely tested and documented. The mechanical engineer tasked with the thermo-mechanical design must then create a highly conductive thermal link that minimizes the tensile and shear stresses transmitted to the focal plane without design parameters on an acceptable stiffness and without data on the stiffness of previously implemented thermal links.This paper describes the development and testing of the thermal link developed for the Portable Remote Imaging Spectrometer (PRISM) instrument. It will provide experimentally determined mechanical stiffness plots in the three axes of interest. Analytical and experimental thermal conductance results for the two-arm focal-plane thermal strap (TAFTS), from cryogenic to room temperatures, are also presented. The paper also briefly describes some elements of the fabrication process followed in developing a novel design solution, which provides high conductance and symmetrical mechanical loading, while providing enhanced flexibility in all three dimensions.