CubeSat Multispectral Sea Turbidity/Bathymetry Monitor
Project overview for public website
harmful algal bloom, multispectral imager, turbidi↗
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Results for “HARMFUL ALGAL BLOOMS”
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Recent Seagrass Trends in the Banana River at Kennedy Space Center, Florida
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seagrass↗
Estimating the concentration of total suspended solids in inland and coastal waters from Sentinel-2 MSI: A semi-analytical approach
Inland and coastal waters provide key ecosystem services and are closely linked to human well-being. In this study, we propose a semi-analytical method, which can be applied to Sentinel-2 MultiSpectral Instrument (MSI) images to retrieve high spatial-resolution total suspended solids (TSS) concentration in a broad spectrum of aquatic ecosystems ranging from clear to extremely turbid waters. The presented approach has four main steps. First, the remote sensing reflectance ( R rs ) at a band lacking in MSI (620 nm) is estimated through an empirical relationship from R rs at 665 nm. Second, waters are classified into four types (clear, moderately turbid, highly turbid, and extremely turbid). Third, semi-analytical algorithms are used to estimate the particulate backscattering coefficient ( b bp ) at a reference band depending on the water types. Last, TSS is estimated from bbp at the reference band. Validation and comparison of the proposed method with three existing methods are performed using a simulated dataset ( N = 1000), an in situ dataset collected from global inland and coastal waters ( N = 1265) and satellite matchups ( N = 40). Results indicate that the proposed method can improve TSS estimation and provide accurate retrievals of TSS from all three datasets, with a median absolute percentage error (MAPE) of 14.88 %, 31.50 % and 41.69 % respectively. We also present comparisons of TSS mapping between the Sentinel-3 Ocean and Land Colour Instrument (OLCI) and MSI in Lake Kasumigaura, Japan and the Tagus Estuary, Portugal. Results clearly demonstrate the advantages of using MSI for TSS monitoring in small water bodies such as rivers, river mouths and other nearshore waters. MSI can provide more detailed and realistic TSS estimates than OLCI in these water bodies. The proposed TSS estimation method was applied to MSI images to produce TSS time-series in Lake Kasumigaura, which showed good agreements with in situ and OLCI-derived TSS time-series.
Sentinel-2↗
Validity of the Landsat Surface Reflectance Archive for Aquatic Science: Implications for Cloud-Based Analysis
Originally developed for terrestrial science and applications, the US Geological Survey Landsat surface reflectance (SR) archive spanning ~ 40 yr of observations has been increasingly utilized in large‐scale water‐quality studies. These products, however, have not been rigorously validated using in situ measured reflectance. This letter quantifies and demonstrates the quality of the SR products by harnessing a sizeable global dataset ( N = 1100). We found that the Landsat 8/9 SR in the green and red bands marginally meet the targeted accuracy requirements (30%), whereas the uncertainties in the blue and coastal‐aerosol bands ranged from 48% to 110%. We further observed > +25% biases in the visible bands of Landsat 5/7 SR, which can introduce an apparent downward trend when applied in time‐series analyses combined with Landsat 8/9. Users must exercise caution when using this archive for trend analyses, and progress in atmospheric correction is required to foster advanced applications of the Landsat archive for aquatic science.
Landsat, lakes, harmful algal blooms↗
The Application of Remote Sensing and Machine Learning to Improve Early Warning Systems for Harmful Algal Events in the Highland Lake Chain, TX
Beginning in 2019, harmful algal events have caused canine deaths in both Lady Bird Lake and Lake Travis located near Austin, Texas. These two reservoirs are part of the larger Highland Lakes chain, managed by the City of Austin Department of Watershed Protection (COA DWP) and the Lower Colorado River Authority (LCRA), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable environmental conditions for algal events in central Texas, NASA DEVELOP partnered with LCRA and COA DWP to improve monitoring and early detection of algal events, utilizing satellite remote sensing and machine learning. Spatially and temporally varied chlorophyll a concentrations, cyanobacteria detections, turbidity, and water surface temperature products are used as environmental proxies. Landsat 8 Operational Land Imager (OLI) and the Sentinel-2 MultiSpectral Instrument (MSI) data were used to provide a combined revisit time of up to ~3 days and < 30 m per pixel products. Chlorophyll a concentrations were estimated using a pre-trained Mixture Density Network, and cyanobacteria detection was accomplished using the Broad Wavelength Algae Index, which can differentiate algal blooms from algal proliferations (mats). In situ data were used to validate remotely sensed measurements and quantify uncertainties. Preliminary results show a good fit between the modeled output and in situ observations, suggesting that remote sensing data can be used to retrieve biogeochemical properties and/or inherent optical properties (IOPs) of water columns in these inland human-made lakes. Uncertainties were introduced from the sensitivity to atmospheric correction, inherent mismatch between satellite and sampling data, and a relatively lower signal-to-noise ratio over water. The resulting products enable near real-time monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain, and will ultimately support water management, decision making, and risk communication.
Shuyu Chang↗
Uptake of Phytoplankton-Derived Carbon and Cobalamins by Novel Acidobacteria Genera in Microcystis Blooms Inferred from Metagenomic and Metatranscriptomic Evidence
We report interactions between bacteria and phytoplankton can influence primary production, community composition, and algal bloom development. However, these interactions are poorly described for many consortia, particularly for freshwater bloom-forming cyanobacteria. Here, we assessed the gene content and expression of two uncultivated Acidobacteria from Lake Erie Microcystis blooms. These organisms were targeted because they were previously identified as important catalase producers in Microcystis blooms, suggesting that they protect Microcystis from H 2 O 2 . Metatranscriptomics revealed that both Acidobacteria transcribed genes for uptake of organic compounds that are known cyanobacterial products and exudates, including lactate, glycolate, amino acids, peptides, and cobalamins. Expressed genes for amino acid metabolism and peptide transport and degradation suggest that use of amino acids and peptides by Acidobacteria may regenerate nitrogen for cyanobacteria and other organisms. The Acidobacteria genomes lacked genes for biosynthesis of cobalamins but expressed genes for its transport and remodeling. This indicates that the Acidobacteria obtained cobalamins externally, potentially from Microcystis, which has a complete gene repertoire for pseudocobalamin biosynthesis; expressed them in field samples; and produced pseudocobalamin in axenic culture. Both Acidobacteria were detected in Microcystis blooms worldwide. Together, the data support the hypotheses that uncultured and previously unidentified Acidobacteria taxa exchange metabolites with phytoplankton during harmful cyanobacterial blooms and influence nitrogen available to phytoplankton. Thus, novel Acidobacteria may play a role in cyanobacterial physiology and bloom development.
59 BASIC BIOLOGICAL SCIENCES↗