Remote Sensing of Cyanobacteria in Case II Waters Using Optically Active Pigments, Chlorophyll a and Phycocyanin

Indiana University-Purdue University Indianapolis (IUPUI)Nuisance blue-green algal blooms contribute to aesthetic degradation of water resources and produce toxins that can have serious adverse human health effects. Current field-based methods for detecting blooms are costly and time consuming, delaying management decisions. Remote sensing techniques which utilize the optical properties of blue-green algal pigments (chlorophyll a and phycocyanin) can provide rapid detection of blue-green algal distribution. Coupled with physical and chemical data from lakes, remote sensing can provide an efficient method for tracking cyanobacteria bloom occurrence and toxin production potential to inform long-term management strategies. In-situ field reflectance spectra were collected at 54 sampling sites on two turbid, productive Indianapolis reservoirs using ASD Fieldspec (UV/VNIR) spectroradiometers. Groundtruth samples were analyzed for in-vitro pigment concentrations and other physical and chemical water quality parameters. Empirical algorithms by Gitelson et al. (1986, 1994), Mittenzwey et al. (1991), Dekker (1993), and Schalles et al. (1998), were applied using a combined dataset divided into a calibration and validation set. Modified semi-empirical algorithms by Simis et al. (2005) were applied to all field spectra to predict phycocyanin concentrations. Algorithm accuracy was tested through a least-squares regression and residual analysis. Results show that for prediction of chlorophyll a concentrations within the range of 18 to 170 ppb, empirical algorithms yielded coefficients of determination as high as 0.71, RMSE 17.59 ppb, for an aggregated dataset (n=54, p2). A strong correlation between measured phycocyanin concentrations and blue-green algal biovolume measurements was also observed (r2=0.95, p<0.0001)

Optical measurements of small deeply penetrating bubble populations generated by breaking waves in the Southern Ocean

Bubble size distributions ranging from 0.5 to 125 μm radius were measured optically during high winds of 13 m s−1 and large-scale wave breaking as part of the Southern Ocean Gas Exchange Experiment. Very small bubbles with radii less than 60 µm were measured at 6–9 m depth using optical measurements of the near-forward volume scattering function and critical scattering angle for bubbles (∼80°). The bubble size distributions generally followed a power law distribution with mean slope values ranging from 3.6 to 4.6. The steeper slopes measured here were consistent with what would be expected near the base of the bubble plume. Bubbles, likely stabilized with organic coatings, were present for time periods on the order of 10–100 s at depths of 6–9 m. Here, relatively young seas, with an inverse wave age of approximately 0.88 and shorter characteristic wave scales, produced lower bubble concentrations, shallower bubble penetration depths, and steep bubble size distribution slopes. Conversely, older seas, with an inverse wave age of 0.70 and longer characteristic wave scales, produced relatively higher bubble concentrations penetrating to 15 m depth, larger bubble sizes, and shallower bubble size distribution slopes. When extrapolated to 4 m depth using a previously published bubble size distribution, our estimates suggest that the deeply penetrating small bubbles measured in the Southern Ocean supplied ∼36% of the total void fraction and likely contributed to the transfer and supersaturation of low-solubility gases

Optical Measurements of Whitecaps and Bubbles During Large Scale Wave Breaking in the Southern Ocean

Wave breaking contributes to climate relevant processes, such as the production of sea salt aerosols and the exchange of gas (e.g. CO2, CH4, DMS, water vapor) and heat between the ocean and atmosphere. Quantifying these processes, however, has been hampered by the lack of field data under high wind conditions and the inherent challenges in measuring whitecaps. Here, optical tools were developed to estimate metrics of whitecaps and bubbles associated with wave breaking along the polar front zone of the Atlantic sector of the Southern Ocean. In this study, wind speeds exceeded 15 m s-1, significant wave heights routinely surpassed 4 m, fractional whitecap coverage exceeded 5%, and bubble plumes penetrated to over 10 m depth in the water column. With a single channel above-water radiometer mounted on a ship, metrics were developed to quantify wave breaking intensity, duration and decay rate, and fractional whitecap coverage. Radiometric estimates of whitecap coverage followed a cubic dependence with wind speed and captured more of the decaying bubble plume area than methods using high-resolution digital imagery. Optical measurements of the near forward volume scattering function and the critical scattering angle for bubbles (~80°) were used to detect deeply penetrating bubbles ranging from 0.5 to 125 μm radius. When extrapolated to 4 m depth, our estimates suggest that the small bubbles here could be supplying ~36% of the total void fraction and likely contributed to the supersaturation of low solubility gases. Finally, preliminary results from a least-squares inversion technique applied to measurements of the bulk optical volume scattering function suggest that a persistent, small (mode radius~0.2 μm) bubble population with a narrow size distribution contributed between 5% (low wind) and 20% (high wind) to the total backscattering during the experiment. Under high wind conditions, foam and bubbles serve to enhance the magnitude and alter the spectral distribution of light leaving the surface ocean, which can impact penetration of light to depth and associated heating rates. These optical tools can be used to better quantify air-sea processes related to wave breaking throughout the ocean and the potential impact on global climate

Clothing Durability: Shein vs. Sustainability

How often do you have to repurchase online clothing due to lack of durability? With the fashion industry always changing and weighing in on what the "next big thing" is in design and aesthetics, the question of quality in production has raised major concerns for consumers. Retrospectively, consumers want their money to go toward items that are durable and will last them a long time. However, the rise in media and consumerism has exposed the public to faster-moving trend cycles, which means a faster moving production cycle. Therefore, the production cycle has to sacrifice things such as sustainability and ethical issues. One way to see the change in durability would be to compare fabric compositions from today's trends to the trends of the 1970s. This research aims to determine if clothing today is as durable as clothing produced fifty years ago

Remote Sensing of Seagrass Leaf Area Index and Species: The Capability of a Model Inversion Method Assessed by Sensitivity Analysis and Hyperspectral Data of Florida Bay

The capability for mapping two species of seagrass, Thalassia testudinium and Syringodium filiforme, by remote sensing using a physics based model inversion method was investigated. The model was based on a three-dimensional canopy model combined with a model for the overlying water column. The model included uncertainty propagation based on variation in leaf reflectances, canopy structure, water column properties, and the air-water interface. The uncertainty propagation enabled both a-priori predictive sensitivity analysis of potential capability and the generation of per-pixel error bars when applied to imagery. A primary aim of the work was to compare the sensitivity analysis to results achieved in a practical application using airborne hyperspectral data, to gain insight on the validity of sensitivity analyses in general. Results showed that while the sensitivity analysis predicted a weak but positive discrimination capability for species, in a practical application the relevant spectral differences were extremely small compared to discrepancies in the radiometric alignment of the model with the imagery—even though this alignment was very good. Complex interactions between spectral matching and uncertainty propagation also introduced biases. Ability to discriminate LAI was good, and comparable to previously published methods using different approaches. The main limitation in this respect was spatial alignment with the imagery with in situ data, which was heterogeneous on scales of a few meters. The results provide insight on the limitations of physics based inversion methods and seagrass mapping in general. Complex models can degrade unpredictably when radiometric alignment of the model and imagery is not perfect and incorporating uncertainties can have non-intuitive impacts on method performance. Sensitivity analyses are upper bounds to practical capability, incorporating a term for potential systematic errors in radiometric alignment may be advisable. While T. testudinium and S. filiforme were too spectrally similar to be discriminated purely on spectral grounds, mapping of these, and other species may be achievable by exploiting co-incident factors based on ecological zonation

Novel methods for optically measuring whitecaps under natural wave-breaking conditions in the Southern Ocean

Traditional methods for measuring whitecap coverage using digital video systems mounted to measure a large footprint can miss features that do not produce a high enough contrast to the background. Here, a method for accurately measuring the fractional coverage, intensity, and decay time of whitecaps using above-water radiometry is presented. The methodology was developed using data collected in the Southern Ocean under a wide range of wind and wave conditions. Whitecap quantities were obtained by employing a magnitude threshold based on the interquartile range of the radiance or reflectance signal from a single channel. Breaking intensity and decay time were produced from the integration of and the exponential fit to radiance or reflectance over the lifetime of the whitecap. When using the lowest magnitude threshold possible, radiometric fractional whitecap coverage retrievals were consistently higher than fractional coverage from high-resolution digital images, perhaps because the radiometer captures more of the decaying bubble plume area that is difficult to detect with photography. Radiometrically obtained whitecap measurements are presented in the context of concurrently measured meteorological (e.g., wind speed) and oceanographic (e.g., wave) data. The optimal fit of the radiometrically estimated whitecap coverage to the instantaneous wind speed, determined using robust linear least squares, showed a near-cubic dependence. Increasing the magnitude threshold for whitecap detection from 2 to 4 times the interquartile range produced a wind speed–whitecap relationship most comparable to the concurrently collected fractional coverage from digital imagery and previously published wind speed–whitecap parameterizations

The O2/N2 Ratio and CO2 Airborne Southern Ocean Study

The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings

The O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) Study

The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings