Application of Landsat 8 for Monitoring Impacts of Wastewater Discharge on Coastal Water Quality

Trinh, Rebecca; Fichot, Cédric G.; Gierach, M. M.; Holt, Benjamin; Malakar, N. K.; Hulley, Glynn; Smith, J. L.

doi:10.3389/fmars.2017.00329

Cited by 51 publications

(46 citation statements)

References 87 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We first evaluate the retrieval using a PRISM flight on a high altitude ER-2 aircraft over Santa Monica Bay, California, on October 262,015. Santa Monica is a near-shore bay in the Southern California Bight that is semi-enclosed and influenced by the populated Los Angeles basin (Trinh et al, 2017). It is an interesting test case due to its high productivity and diverse aquatic ecosystem (Hickey, 1992;Corcoran and Shipe, 2011).…”

Section: Experimental Methodsmentioning

confidence: 99%

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

Thompson

Cawse‐Nicholson

Erickson

et al. 2019

Remote Sensing of Environment

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Experimental Methodsmentioning

confidence: 99%

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

Thompson

Cawse‐Nicholson

Erickson

et al. 2019

Remote Sensing of Environment

Self Cite

View full text Add to dashboard Cite

show abstract

“…About one third of all the images were discarded because of cloud coverage. The surface chlorophyll-a concentrations were derived by applying a local empirical algorithm to the Rrs(488)/Rrs(547) remote-sensing reflectance ratio [30]. This local empirical algorithm was parameterized specifically for MODIS using in situ measurements made in the coastal waters off the Los Angeles, CA area (i.e., our region of study).…”

Section: Satellite Imagerymentioning

confidence: 99%

Dynamics and interactions of highly resolved marine plankton via automated high-frequency sampling

et al. 2018

Self Cite

View full text Add to dashboard Cite

Short timescale observations are valuable for understanding microbial ecological processes. We assessed dynamics in relative abundance and potential activities by sequencing the small sub-unit ribosomal RNA gene (rRNA gene) and rRNA molecules (rRNA) of Bacteria, Archaea, and Eukaryota once to twice daily between March 2014 and May 2014 from the surface ocean off Catalina Island, California. Typically Ostreococcus, Braarudosphaera, Teleaulax, and Synechococcus dominated phytoplankton sequences (including chloroplasts) while SAR11, Sulfitobacter, and Fluviicola dominated non-phytoplankton Bacteria and Archaea. We observed short-lived increases of diatoms, mostly Pseudo-nitzschia and Chaetoceros, with quickly responding Bacteria and Archaea including Flavobacteriaceae (Polaribacter & Formosa), Roseovarius, and Euryarchaeota (MGII), notably the exact amplicon sequence variants we observed responding similarly to another diatom bloom nearby, 3 years prior. We observed correlations representing known interactions among abundant phytoplankton rRNA sequences, demonstrating the biogeochemical and ecological relevance of such interactions: (1) The kleptochloroplastidic ciliate Mesodinium 18S rRNA gene sequences and a single Teleaulax taxon (via 16S rRNA gene sequences) were correlated (Spearman r = 0.83) yet uncorrelated to a Teleaulax 18S rRNA gene OTU, or any other taxon (consistent with a kleptochloroplastidic or karyokleptic relationship) and (2) the photosynthetic prymnesiophyte Braarudosphaera bigelowii and two strains of diazotrophic cyanobacterium UCYN-A were correlated and each taxon was also correlated to other taxa, including B. bigelowii to a verrucomicrobium and a dictyochophyte phytoplankter (all r > 0.8). We also report strong correlations (r > 0.7) between various ciliates, bacteria, and phytoplankton, suggesting interactions via currently unknown mechanisms. These data reiterate the utility of high-frequency time series to show rapid microbial reactions to stimuli, and provide new information about in situ dynamics of previously recognized and hypothesized interactions.

show abstract

“…PRISM uses a push-broom design and observes a cross-track angular field of view spanning approximately 30 • , and is designed to observe coastal ocean environments in the 350-1050 nm spectral range at approximately 3 nm spectral sampling. The instrument was mounted onboard a high-altitude ER-2 aircraft which overflew Santa Monica, USA, in October 2015 at 20 km above sea level (Thompson et al, 2018b;Trinh et al, 2017). At this altitude, the instrument measured the scene through nearly all of Earth's atmospheric scattering and absorption, providing a challenging test case with relevance to future orbital instruments.…”

Section: Neural Rtm Emulation For Prismmentioning

confidence: 99%

“…Remote visible-shortwave infrared (VSWIR) imaging spectroscopy, also known as hyperspectral imaging, is a powerful approach to map the composition, health, and biodiversity of Earth's ecosystems (ESAS, 2018). Remote sensing of the solar-reflected spectrum from 380 to 2500 nm reveals physics and chemistry of many processes in Earth's surfaceatmosphere system (Schaepman et al, 2009), including terrestrial plant health and traits (Asner et al, 2017;Ustin et al, 2004); biodiversity (Jetz et al, 2016); the condition and composition of aquatic, benthic, and nearshore ecosystems (Fichot et al, 2015;Hochberg, 2011); geology (Swayze et al, 2014); and trace greenhouse gases (Frankenberg et al, 2016). While Earth scientists aim to measure these geophysical variables, remote sensors can only measure the incident light at the sensor.…”

Section: Introductionmentioning

confidence: 99%

Neural network radiative transfer for imaging spectroscopy

et al. 2019

View full text Add to dashboard Cite

Abstract. Visible–shortwave infrared imaging spectroscopy provides valuable remote measurements of Earth's surface and atmospheric properties. These measurements generally rely on inversions of computationally intensive radiative transfer models (RTMs). RTMs' computational expense makes them difficult to use with high-volume imaging spectrometers, and forces approximations such as lookup table interpolation and surface–atmosphere decoupling. These compromises limit the accuracy and flexibility of the remote retrieval; dramatic speed improvements in radiative transfer models could significantly improve the utility and interpretability of remote spectroscopy for Earth science. This study demonstrates that nonparametric function approximation with neural networks can replicate radiative transfer calculations and generate accurate radiance spectra at multiple wavelengths over a diverse range of surface and atmosphere state parameters. We also demonstrate such models can act as surrogate forward models for atmospheric correction procedures. Incorporating physical knowledge into the network structure provides improved interpretability and model efficiency. We evaluate the approach in atmospheric correction of data from the PRISM airborne imaging spectrometer, and demonstrate accurate emulation of radiative transfer calculations, which run several orders of magnitude faster than first-principles models. These results are particularly amenable to iterative spectrum fitting approaches, providing analytical benefits including statistically rigorous treatment of uncertainty and the potential to recover information on spectrally broad signals.

show abstract

Application of Landsat 8 for Monitoring Impacts of Wastewater Discharge on Coastal Water Quality

Cited by 51 publications

References 87 publications

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

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

Dynamics and interactions of highly resolved marine plankton via automated high-frequency sampling

Neural network radiative transfer for imaging spectroscopy

Contact Info

Product

Resources

About