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At least 181 records · Page 10

A remote sensing laser fluorometer

A sensor is reported which is able to identify certain specific substances in water by means of their fluorescence spectra. In particular, the sensor detects oil, ligninsulfonates and chlorophyll. The device is able to measure the fluorescence spectra of water at ranges up to 75 m and to detect oil spills on water at altitudes up to 300 m. Blue light from a laser is used to excite the fluorescence of the target. Any light from the ambient background illumination, from the reflected laser light or from the induced fluorescence is gathered by a small telescope focused on the target. Optical filters are used to block the reflected laser light and to select the wavelengths of interest in the fluorescence spectrum of the target. The remaining light is detected with a photomultiplier tube. The amplitude of the laser induced fluorescence in the wavelength interval selected by the optical filters is displayed on a meter or strip chart recorder.

Oneill, R. A.↗

Sunlight induced 685 nm fluorescence imagery

The capability of a new fluorescence method is evaluated using data from an aircraft fluorescence experiment conducted on the Elbe River on August 10-14, 1981. The technique measures chlorophyll concentrations by monitoring sunlight-induced fluorescence at 685 nm. Upwelling radiance spectra and vertical profiles of upwelling radiances are presented and analyzed. The image-processing algorithm used to retrieve fluorescence signals from raw data is described.

Kim, Hongsuk H.↗

Oceanic Lidar

Instrument concepts which measure ocean temperature, chlorophyll, sediment and Gelbstoffe concentrations in three dimensions on a quantitative, quasi-synoptic basis were considered. Coastal zone color scanner chlorophyll imagery, laser stimulated Raman temperaure and fluorescence spectroscopy, existing airborne Lidar and laser fluorosensing instruments, and their accuracies in quantifying concentrations of chlorophyll, suspended sediments and Gelbstoffe are presented. Lidar applications to phytoplankton dynamics and photochemistry, Lidar radiative transfer and signal interpretation, and Lidar technology are discussed.

Carder, K. L.↗

Principal Component and Machine Learning Approach to Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals can be limited spatially due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals. Despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we developed a spatial gap filling approach applying machine learning approach to hyperspectral instruments to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral components that describe the scattering and absorption of the atmosphere mixed with the surface spectral signatures. The coefficients of the principal components are used to train a neural network to predict ocean color properties derived from a standard MODIS ocean color algorithm. We apply the approach to two hyperspectral UV/VIS sensors, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) onboard upcoming NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the first NASA and Smithsonian geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) spectrometer to better understand diurnal variability in inland and coastal ocean ecology.

Zachary Fasnacht↗

A Principal Component and Machine Learning Approach to Spatially Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals tend to be limited in spatial coverage due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals but despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we propose a spatial gap filling approach using machine learning to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from a standard ocean color algorithm such as the MODIS atmospheric correction algorithm. This machine learning approach is independent of a priori information and does not rely on any radiative transfer modeling. We apply the approach to two hyperspectral UV/VIS instruments, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) which will be onboard NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) ocean color satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the geostationary satellite Tropospheric Emissions: Monitoring of Pollution (TEMPO) to better understand diurnal variability in ocean ecology.

MODIS atmospheric correction algorithm↗

Narragansett Bay Water Resources: Using Earth Observations to Identify Trends in Harmful Algal Blooms in Narragansett Bay

Narragansett Bay in Rhode Island is known for its quahog, or hard-shell clam, shellfisheries. However, increased levels in harmful algal blooms (HABs) and high phytoplankton biomass events pose threats to quahog populations, creating conditions that limit quahog growth and reproduction. Quahog shortages, along with public health concerns associated with contamination of shellfish from HAB-produced neurotoxins, have contributed to shellfishery closures. NASA DEVELOP partnered with the Environmental Protection Agency’s National Health and Environmental Effects Research Laboratory and Rhode Island’s Department of Environmental Management to use Earth observations and the partners’ in-situ data to visualize phytoplankton bloom events within the bay. We used Sentinel-3 Ocean and Land Color Instrument (OLCI), Landsat 8 and 9 Operational Land Imager (OLI)data to track several proxies of phytoplankton biomass from June 2016 to October 2023. Multiple sensors and in situ datasets were used to assess the feasibility of monitoring phytoplankton biomass accurately in the relatively small sized Narragansett Bay. We determined that Phytoplankton fluorescence line height was the best parameter to monitor phytoplankton biomass in the bay. Although the relatively small size of the bay and the optical complexity of these nearshore waters can pose a challenge, this assessment showed that Earth observations can be a useful complement to the in-situ monitoring of phytoplankton biomass in Narragansett Bay.

Sentinel-3↗

Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data

We estimate global terrestrial gross primary production (GPP) based on models that use satellite data within a simplified light-use efficiency framework that does not rely upon other meteorological inputs. Satellite-based geometry-adjusted reflectances are from the MODerate-resolution Imaging Spectroradiometer (MODIS) and provide information about vegetation structure and chlorophyll content at both high temporal (daily to monthly) and spatial (1 km) resolution. We use satellite-derived solar-induced fluorescence (SIF) to identify regions of high productivity crops and also evaluate the use of downscaled SIF to estimate GPP. We calibrate a set of our satellite-based models with GPP estimates from a subset of distributed eddy covariance flux towers (FLUXNET 2015). The results of the trained models are evaluated using an independent subset of FLUXNET 2015 GPP data. We show that variations in light-use efficiency (LUE) with incident PAR are important and can be easily incorporated into the models. Unlike many LUE-based models, our satellite-based GPP estimates do not use an explicit parameterization of LUE that reduces its value from the potential maximum under limiting conditions such as temperature and water stress. Even without the parameterized downward regulation, our simplified models are shown to perform as well as or better than state-of-the-art satellite data-driven products that incorporate such parameterizations. A significant fraction of both spatial and temporal variability in GPP across plant functional types can be accounted for using our satellite-based models. Our results provide an annual GPP value of 140 Pg C year 1 for 2007 that is within the range of a compilation of observation-based, model, and hybrid results, but is higher than some previous satellite observation-based estimates

CO2↗

Contrasting Inherent Optical Properties and Carbon Metabolism Between Five Northeastern (USA) Estuary-plume Systems

We have recently developed the ability to rapidly assess Surface inherent optical properties (IOP), oxygen concentration and pCO2 in estuarine-plume systems using flow-through instrumentation. During the summer of 2004, several estuarine-plume systems were surveyed which include the Pleasant (ME), Penobscot (ME), Kennebec-Androscoggin (ME), Merrimack (NH-MA) and Hudson (NY). Continuous measurements of surface chlorophyll and colored dissolved organic carbon (CDOM) fluorescence, beam attenuation, temperature, salinity, oxygen and pC02 were taken at each system along a salinity gradient from fresh water to near oceanic endmembers. CTD and IOP profiles were also taken at predetermined surface salinity intervals. These were accompanied by discrete determinations of chlorophyll (HPLC and fluorometric), total suspended solids (TSS), dissolved organic carbon (DOC) and alkalinity. IOP data were calibrated using chlorophyll, DOC and TSS data to enable the retrieval of these constituents from IOP data. Considerable differences in the data sets were observed between systems. These ranged from the DOC-enriched, strongly heterotrophic Pleasant River System to the high-chlorophyll autotrophic Merrimack River System. Using pCO2 and oxygen saturation measurements as proxies for water column metabolism, distinct relationships were found between trophic status and inherent optical properties. The nature of these relationships varies between systems and is likely a function of watershed and estuarine attributes including carbon and nutrient loading, in-situ production and related autochthonous inputs of DOC and alkalinity. Our results suggest that IOP data may contain significant information about the trophic status of estuarine and plume systems.

Vandemark, Doug↗

Advances in Fluorescence Sensing Systems for the Remote Assessment of Nitrogen Supply in Field Corn

The studies described herein were conducted to better define changes in fluorescence properties of leaves from field grown corn (Zea mays L.) as they relate to varying levels of nitrogen (N) fertilization. This research was directed toward: 1) providing a remote non-destructive sensing technique to aid in the determination of optimal rates of N fertilization in corn crops and, 2) defining parameters for further development of fluorescence instrumentation to be operated remotely at field canopy levels. Fluorescence imaging bands centered in the blue (450 nm), green (525 nm), red (680 nm), and far-red (740 nm) and ratios of these bands were compared with the following plant parameters: rates of photosynthesis, N:C ratio, pigment concentrations, and grain yields. Both the fluorescence and physiological measures exhibited similar curvilinear responses to N fertilization level while significant linear correlations were obtained among fluorescence bands and band ratios to certain physiological measures of plant productivity. The red / blue, red / green, far-red / blue, far-red /green fluorescence ratios are well suited for remote observation and provided high correlations to grain yield, LAI, N:C, and chlorophyll contents. The results from this investigation indicate that fluorescence technology could aid in the determination of N fertilization requirements for corn. This discussion will also address design concepts and preliminary field trials of a mobile field-based Laser Induced Fluorescence Imaging System (LIFIS) capable of simultaneously acquiring images of four fluorescence emission bands from areas of plant canopies equaling 1 sq m and greater without interference of ambient solar radiation.

Corp, L. A.↗

Interpretation of Observations of Trans-Spectral Phenomena Acquired Using Hyperspectral Sensors Aboard a Remotely Operated Vehicle in Exuma Sound

Hyper-spectral (512-channel) optical data acquired during a relatively deep (102m) dive of our ROSEBUD Remotely Operated Vehicle (ROV) in the clear waters of Exuma Sound, Bahamas provided the opportunity to investigate the trans-spectral shift of photonic energy (inelastic scattering) as a function of water depth. Results show a convolution of several spectral processes (e.g. absorption, scattering) involving water molecules, dissolved material and particulates as well as trans-spectral (inelastic) processes involving fluorescence by water molecules (Raman), dissolved material and chlorophyll. The spectral signatures of these convolved causes and effects allow deconvolution with a hyperspectral approach. Intrinsic to the convolution was the ability to position the vehicle at depths where Raman fluorescence dominated at red wavelengths. Results show that the calculated Raman absorption coefficients are generally consistent with historical values (i.e. 0.9 x 10(sup)-4 at 525 nm excitation) and that an angstrom exponent of 5 is more appropriate than the often cited value of 4.

Costello, D.↗

Three color laser fluorometer for studies of phytoplankton fluorescence

A three-color laser fluorometer has been developed for field work operations. Using two tunable dye lasers (excitation wavelengths at 440 nm and 530 nm), broadband wavelength optical filters were selected to obtain maximum fluorescence sensitivity at wavelengths greater than 675 nm (chlorophyll) and 575 + or - 15 nm (phycoerythrin). The laser fluorometer permits the measurement of phytoplankton pigments under static or flowing conditions and more closely resembles the time scales (ns) and energy levels (mW) of other laser-induced fluorescence instruments.

Phinney, David A.↗

New algae mapping technique by the use of an airborne laser fluorosensor.

An airborne laser fluorosensor for the detection of algae in the sea has been developed. The system transmits dye laser radiation at 590 nm and monitors the fluorescent emission at 685 nm from chlorophyll-a bearing microorganisms. The system was successfully flown over the test areas of Lake Ontario and Chesapeake Bay. The device is sensitive to a fraction of mg/cu-M chlorophyll-a density in the water from an altitude of 30 m.

Kim, H. H.↗

Spectral and Temporal Laser Fluorescence Analysis Such as for Natural Aquatic Environments

An Advanced Laser Fluorometer (ALF) can combine spectrally and temporally resolved measurements of laser-stimulated emission (LSE) for characterization of dissolved and particulate matter, including fluorescence constituents, in liquids. Spectral deconvolution (SDC) analysis of LSE spectral measurements can accurately retrieve information about individual fluorescent bands, such as can be attributed to chlorophyll-a (Chl-a), phycobiliprotein (PBP) pigments, or chromophoric dissolved organic matter (CDOM), among others. Improved physiological assessments of photosynthesizing organisms can use SDC analysis and temporal LSE measurements to assess variable fluorescence corrected for SDC-retrieved background fluorescence. Fluorescence assessments of Chl-a concentration based on LSE spectral measurements can be improved using photo-physiological information from temporal measurements. Quantitative assessments of PBP pigments, CDOM, and other fluorescent constituents, as well as basic structural characterizations of photosynthesizing populations, can be performed using SDC analysis of LSE spectral measurements.

Chekalyuk, Alexander↗

In Vivo and in Vitro Chlorophyll-a and Pheophytin-a Concentration Measurements by Laser Fluorometry

Discussed here is the application of a laser fluorescent technique in in vivo and in vitro phyto- and zooplankton analysis involving popular lasers, an impulse YAG laser (lambda = 532 nm) and a steady state He-Cd (lambda = 440 nm). The YAG laser is widely used in laser remote sensing of seawater photoplankton in situ mode, but here we give special attention to its use in the precise estimation of phytoplankton pigments using laser induced fluorescence. The He-Cd laser is a novice in this field and, we believe, very promising. Our methods enable one to detect, in viro, chlorophyll-a (Chl-a) concentration in the water probe up to 10 nanograms per liter, and to measure, in vitro, Chl-a and pheophytin-a (Ph-a) concentrations in acetone extracts of phyto- and zooplankton up to 1 nanogram per liter.

Demidov, A. A.↗

Expression of the high capacity calcium-binding domain of calreticulin increases bioavailable calcium stores in plants

Modulation of cytosolic calcium levels in both plants and animals is achieved by a system of Ca2+-transport and storage pathways that include Ca2+ buffering proteins in the lumen of intracellular compartments. To date, most research has focused on the role of transporters in regulating cytosolic calcium. We used a reverse genetics approach to modulate calcium stores in the lumen of the endoplasmic reticulum. Our goals were two-fold: to use the low affinity, high capacity Ca2+ binding characteristics of the C-domain of calreticulin to selectively increase Ca2+ storage in the endoplasmic reticulum, and to determine if those alterations affected plant physiological responses to stress. The C-domain of calreticulin is a highly acidic region that binds 20-50 moles of Ca2+ per mole of protein and has been shown to be the major site of Ca2+ storage within the endoplasmic reticulum of plant cells. A 377-bp fragment encoding the C-domain and ER retention signal from the maize calreticulin gene was fused to a gene for the green fluorescent protein and expressed in Arabidopsis under the control of a heat shock promoter. Following induction on normal medium, the C-domain transformants showed delayed loss of chlorophyll after transfer to calcium depleted medium when compared to seedlings transformed with green fluorescent protein alone. Total calcium measurements showed a 9-35% increase for induced C-domain transformants compared to controls. The data suggest that ectopic expression of the calreticulin C-domain increases Ca2+ stores, and that this Ca2+ reserve can be used by the plant in times of stress.

NASA Discipline Plant Biology↗

Fluorescence of dissolved organic matter: A comparison of north Pacific and north Atlantic Oceans during April 1991

Profiles of airborne-laser-induced fluorescence emission from dissolved organic matter in the upper ocean have been produced and compared for the Southern California Bight (SCB) and the Mid-Atlantic Bight (MAB). Findings were as follows. (1) The fluorescent components of dissolved organic matter (FDOM) are present in easily measurable quantities from near shore to well over 300 km offshore in the SCB and are likewise easily measurable in the coastal, shelf, slope, and Gulf Stream waters of the MAB. (2) The reange of FDOM in the MAB is considerably greater than that in the SCB. (3) The lowest FDOM levels observed in the SCB were higher than those found in the Gulf Stream. (4) The onshore-to-offshore spatial gradient of the FDOM was found to be considerably lower in the SCB than in the MAB, with the highest levels of FDOM being found immediately adjacent to the coast in the MAB. This suggests that the water adjacent to the SCB shoreline is not as strongly influenced by terrestrial and estuarine sources of FDOM as the MAB is. (5) The spatial distribution of the FDOM within both the SCB and the MAB is frequently coherent with the spatial distribution of chlorophyll determined form the concurrent airborne- laser- induced phytoplankton pigment fluorescence measurements. However, distinct noncoherency is sometimes observed, especially at water mass boundaries.

Hoge, Frank E.↗

The current status of airborne laser fluorosensing

Airborne laser fluorosensors have been used to identify and quantify specific substances in the aquatic environment. It has been shown that the sensor can identify and classify oil films. If the extinction coefficient is known then the thickness of thinner films (less than 20 micrometers) may be calculated. The intensity of the water Raman signal is proportional to the water volume sampled by the sensor and hence an effective attenuation coefficient for the water can be calculated. The same Raman measurement provides the normalization necessary to map chlorophyll and dye concentrations using the intensity of their respective fluorescence signatures.

Oneil, R. A.↗

Optical Reflectance and Fluorescence for Detecting Nitrogen Needs in Zea mays L.

Nitrogen (N) status in field grown corn (Zea mays L.) was assessed using spectral techniques. Passive reflectance remote sensing and, both passive and active fluorescence sensing methods were investigated. Reflectance and fluorescence methods are reported to detect changes in the primary plant pigments (chlorophylls a and b; carotenoids) in higher plant species. As a general rule, foliar chlorophyll a (Chl a) and chlorophyll b (Chl b) usually exist in approx.3:l ratio. In plants under stress, Chl b content is affected before Chl a reductions occur. For reflectance, a version of the chlorophyll absorption in reflectance index (CARI) method was tested with narrow bands from the Airborne Imaging Spectroradiometer for Applications (ASIA). CARI minimizes the effects of soil background on the signal from green canopies. A modified CARI (MCARI) was used to track total Chl a levels in the red dip of the spectrum from the corn canopy. A second MCARI was used to track the auxiliary plant pigments (Chl b and the carotenoids) in the yellow/orange/red edge part of the reflectance spectrum. The difference between these two MCARI indices detected variations in N levels across the field plot canopies using ASIA data. At the leaf level, ratios of fluorescence emissions in the blue, green, red and far-red wavelengths sensed responses that were associated with the plant pigments, and were indicative of energy transfer in the photosynthetic process. N stressed corn stands could be distinguish from those with optimally applied N with fluorescence emission spectra obtained from individual corn leaves. Both reflectance and fluorescence methods are sensitive in detecting corn N needs and may be especially powerful in monitoring crop conditions if both types of information can be combined.

McMurtrey, J. E.↗