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DOE OSTI2020

Development of Lipid-Coated Semiconductor Nanosensors for Recording of Membrane Potential in Neurons

In the past decade, optical imaging methods have significantly improved our understanding of the information processing principles in the brain. Although many promising tools have been designed, sensors of membrane potential are lagging behind the rest. Semiconductor nanoparticles are an attractive alternative to classical voltage indicators, such as voltage-sensitive dyes and proteins. Such nanoparticles exhibit high sensitivity to external electric fields via the quantum-confine Stark effect. Here we report the development of semiconductor voltage-sensitive nanorods (vsNRs) that self-insert into the neuronal membrane. To facilitate interaction of the nanorods with the membrane, we functionalized their surface with the lipid mixture derived from brain extract. We describe a workflow to detect and process the photoluminescent signal of vsNRs after widefield time-lapse recordings. We also present data indicating that vsNRs are feasible for sensing membrane potential in neurons at a single-particle level. This shows the potential of vsNRs for the detection of neuronal activity with unprecedentedly high spatial and temporal resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor system play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. Nonetheless, challenges emerge as distances grow due to signal attenuation and noise interference resulting in measurement errors. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond 10’s of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. This approach proves particularly advantageous in BOTDA systems, where accurate measurement of Brillouin scattering signals is paramount for long-range sensing, while concurrently safeguarding high spatial resolutions. In summary, this research has shown a holistic exploration of extending BOTDA's distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗

NASA NTRS2012

Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (εn) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of εn suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.

Kazakhstan↗

NASA NTRS2014

Infrared Spectral Radiance Intercomparisons With Satellite and Aircraft Sensors

Measurement system validation is critical for advanced satellite sounders to reach their full potential of improving observations of the Earth's atmosphere, clouds, and surface for enabling enhancements in weather prediction, climate monitoring capability, and environmental change detection. Experimental field campaigns, focusing on satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft, are an essential part of the validation task. Airborne FTS systems can enable an independent, SI-traceable measurement system validation by directly measuring the same level-1 parameters spatially and temporally coincident with the satellite sensor of interest. Continuation of aircraft under-flights for multiple satellites during multiple field campaigns enables long-term monitoring of system performance and inter-satellite cross-validation. The NASA / NPOESS Airborne Sounder Testbed - Interferometer (NAST-I) has been a significant contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This presentation gives an overview of benefits achieved using airborne sensors such as NAST-I utilizing examples from recent field campaigns. The methodology implemented is not only beneficial to new sensors such as the Cross-track Infrared Sounder (CrIS) flying aboard the Suomi NPP and future JPSS satellites but also of significant benefit to sensors of longer flight heritage such as the Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) on the AQUA and METOP-A platforms, respectively, to ensure data quality continuity important for climate and other applications. Infrared spectral radiance inter-comparisons are discussed with a particular focus on usage of NAST-I data for enabling inter-platform cross-validation.

Larar, Allen M.↗

NASA NTRS2019

How Well Does NASA GEOS Model Perform in Simulating Dust Deposition into the Tropical Atlantic Ocean?

Massive dust emitted from North Africa can transport long distances across the tropical Atlantic Ocean, reaching the Americas. Dust deposition along the transit adds microorganisms and essential nutrients to marine ecosystem, which has important implications for biogeochemical cycle and climate. However, assessing the dust-ecosystemclimate interactions has been hindered in part by the paucity of dust deposition measurements and large uncertainties associated with oversimplified representations of dust processes in current models. We have recently produced a unique dataset of seasonal dust deposition flux and dust loss frequency into the tropical Atlantic Ocean at a nominal resolution of 200 km x 500 km by using the decade-long (2007-2016) record of aerosol three-dimensional distribution from four satellite sensors, namely CALIOP, MODIS, MISR, and IASI. On the basis of the ten-year average, the yearly dust deposition into the tropical Atlantic Ocean is estimated at 98-153 Tg. The dust deposition shows large spatial and temporal (on seasonal and interannual scale) variability. The satellite observations also yield an estimate of annual mean dust loss frequency of 0.052 ~ 0.078 d-1, a useful diagnostic that makes it possible to disentangle the dust transport and removal processes from the dust emissions when identifying the major factors contributing to the uncertainties and biases in the model simulated dust deposition. In this study, we use the dataset along with in situ and remote sensing observations to assess how well NASA GEOS model performs in simulating trans-Atlantic dust transport and deposition. We found that the GEOS modeling of dust deposition falls within the range of satellite-based estimates. However, this reasonable agreement in dust deposition is a compensation of the model's underestimate of dust emissions and overestimate of dust removal efficiency. Further, the overestimate of dust removal efficiency results largely from the model's overestimate of rainfall rate. Our results provide insights into the model's deficiencies at process level, which could better guide model improvements.

Yu, Hongbin↗

NASA NTRS2023

Shape from spectra

We introduce a new unified atmospheric–topographic correction approach that estimates surface geometry directly from the radiance measurement. Surface topography influences the at-sensor radiance measurement, making precise topography modeling critical in applications like vegetation or snow studies in mountainous terrain. Currently, elevation maps are used to derive topographic variables such as the slope and sky-view factor. This process is error-prone since static global digital elevation models do not generally achieve the accuracy required, and even minor mismatches in spatial resolution can introduce significant artifacts in downstream processing. Here we demonstrate that it is possible to estimate topographic parameters directly from spectral data, ensuring perfect physical consistency, temporal coincidence, and spatial alignment. We present experiments estimating topographic slope in two scenes in Southern California, with data from NASA’s Next Generation Airborne Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG). We compared our radiance-based estimates against high-resolution lidar datasets. Our initial validation result showed a correlation of R 2 = 0.864 (n = 160) over the homogeneous surface of Beckman Auditorium’s cone-shaped roof on the Caltech campus in Pasadena, California. We then validate the model over a larger study site near Santa Clarita, California, finding R 2 = 0.923 (n = 40,000) in a 350 x 350m area. The accuracy of our model estimates, combined with its systematic advantages over the alternative, show the potential of the approach for use in both airborne campaigns and orbital missions.

Nimrod Carmon↗

NASA NTRS2012

Thermographic Imaging of the Space Shuttle During Re-Entry Using a Near Infrared Sensor

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter s hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASA s next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness. Keywords: HYTHIRM, Space Shuttle thermography, hypersonic imaging, near infrared imaging, histogram analysis, singular value decomposition, eigenvalue image sharpness

Zalameda, Joseph N.↗

DOE OSTI2021

Studying drought-induced forest mortality using high spatiotemporal resolution evapotranspiration data from thermal satellite imaging

Drought can have pervasive and wide-spread impacts to forest health, as evidenced in several severe events occurring over the recent decades. Extensive forest die-off due to drought can impair the ecological functioning of forests, impacting habitat, water yield and quality from forested lands, and altering forest fire dynamics and intensity. Satellite remote sensing provides an effective means for detecting and monitoring spatial patterns of forest mortality over large areas, exploiting free and open long-term image archives available at a range in spatial and temporal resolutions. While remotely sensed surface reflectances and vegetation indices have been widely used to study optical response of forest canopies to drought events, retrievals of evapotranspiration (ET) derived from thermal satellite imagery – particularly at resolutions approaching crown scale - can provide insights into cumulative tree stresses that can incite disease and trigger mortality. In this study, we applied a multi-sensor satellite data fusion approach to estimate daily 30-m resolution ET and an associated Evaporative Stress Index (ESI) to study drought-induced mortality in a temperate forest at the Missouri Ozark AmeriFlux (MOFLUX) site, located in the central United States. The study covered the period from 2010 to 2014, including an exceptional drought year of 2012. Modeled ET agreed well with eddy flux measurements from the MOFLUX tower, with average monthly relative errors of 15%. Plot-scale ESI, describing temporal anomalies in the ratio of actual-to-reference ET, was used as an index of relative forest health to investigate relationships between forest mortality and drought severity. ESI showed good agreement with observed predawn leaf water potential, especially during the drought year. Furthermore, plot-scale ESI was also correlated with the subsequent year's tree mortality, suggesting the importance of considering the forest health condition prior to drought when studying drought-induced forest impacts. This study demonstrates the utility of multi-year ET remote sensing data at the stand or plot scale as an indicator of forest health and as a predictor of future mortality due to drought.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Satellites: New global observing techniques for ice and snow

The relation of aereal extent of snow cover to the average monthly runoff in a given watershed was investigated by comparing runoff records with a series of snowcover maps. Studies using the high spatial resolution available with ERTS-1 imagery were carried out for the Wind River Mountains watersheds in Wyoming, where it was found that the empirical relationship varied with mean elevation of the watershed. In addition, digital image enhancement techniques are shown to be useful for identifying glacier features related to extent of snowcover, moraine characteristics, and debris average. Longer wavelength observations using sensors on board the Nimbus 5 Satellite are shown to be useful for indicating crystal size distributions and onset of melting on glacier snow cover.

Gloersen, P.↗

NASA NTRS2004

First Results of the Athena Microscopic Imager Investigation

The Athena science payload on the Mars Exploration Rovers (MER) includes the Microscopic Imager (MI). The MI is a fixed-focus camera mounted on an extendable arm, the Instrument Deployment Device (IDD). The MI acquires images at a spatial resolution of 30 microns/pixel over a broad spectral range (400 - 700 nm). The MI uses the same electronics design as the other MER cameras but its optics yield a field of view of 31 x 31 mm across a 1024 x 1024 pixel CCD image. The MI acquires images using only solar or skylight illumination of the target surface. A contact sensor is used to place the MI slightly closer to the target surface than its best focus distance (about 69 mm), allowing concave surfaces to be imaged in good focus. Coarse focusing (approx. 2 mm precision) is achieved by moving the IDD away from a rock target after contact is sensed. The MI optics are protected from the Martian environment by a retractable dust cover. This cover includes a Kapton window that is tinted orange to restrict the spectral bandpass to 500 - 700 nm, allowing crude color information to be obtained by acquiring images with the cover open and closed. The MI science objectives, instrument design and calibration, operation, and data processing were described by Herkenhoff et al. Initial results of the MI experiment on both MER rovers ('Spirit' and 'Opportunity') are described below.

Herkenhoff, K.↗

NASA NTRS2010

Ten Years of MISR Observations from Terra: Looking Back, Ahead, and in Between

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its nine along-track view angles, four visible/near-infrared spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space. The more than 10-year (and counting) MISR data record provides unprecedented opportunities for characterizing long-term trends in aerosol, cloud, and surface properties, and includes 3-D textural information conventionally thought to be accessible only to active sensors.

remote sensing↗

NASA NTRS1989

The use of aircraft and satellite remote sensing of phytoplankton chlorophyll concentrations in case 2 estuarine waters of the Chesapeake Bay

Two projects using remote sensing of phytoplankton chlorophyll concentrations in the Chesapeake Bay estuary were proposed. The first project used aircraft remote sensing with a compact radiometer system developed at NASA's Goddard Space Flight Center (GSFC), the Ocean Data Acquisition System (ODAS). ODAS includes three radiometers at 460, 490, and 520 nm, an infrared temperature sensor (PRT-5), Loran-C for navigation, and a data acquisition system using a PC and mass storage device. This instrument package can be flown in light aircraft at relatively low expense, permitting regular and frequent flights. Sixteen flights with ODAS were completed using the Virginia Institute of Marine Science's De Havilland 'Beaver'. The goal was to increase spatial and temporal resolution in assaying phytoplankton pigment concentrations in the Chesapeake. At present, analysis is underway of flight data collected between March and July 1989. The second project focused on satellite data gathered with the Nimbus-7 Coastal Zone Color Scanner (CZSC) between late 1978 and mid 1986. The problem in using CZSC data for the Chesapeake Bay is that the optical characteristics of this (and many) coastal and estuarine waters are distinct from those of the open ocean for which algorithms for computing pigment concentrations were developed. The successful use of CZCS data for the estuary requires development of site-specific algorithms and analytical approaches. Of principal importance in developing site-specific procedures is the availability of in-situ data on pigment concentrations. A significant data set was acquired from EPA's Chesapeake Bay Program in Annapolis, Maryland, and clear satellite scenes are being analyzed for which same-day sea truth measurements of pigment were obtained. Both the University of Miami and GSFC Seapak systems are being used in this effort. The main finding to date is an expected one, i.e., the algorithms developed for oceanic waters are inadequate to compute pigment concentrations for the Case 2 waters of the Chesapeake Bay. One reason is the overestimation of aerosol radiances by assuming that water-leaving radiance in Band 4 of CZCS (670 nm) is zero, an assumption that is invalid for the Bay. This prompted any attempts to iterative procedures for estimating the proportion of the Band 4 radiance that is actually attributable to aerosol by estimating the water-leaving component using optical data. A cruise on the Chesapeake the week of 7 August 1989 was conducted to collect additional optical data necessary to this task.

Harding, Lawrence W., Jr.↗

NASA NTRS1992

Radar interferometry studies of the earth's topography

Digital elevation models (DEMs) which have been acquired using the TOPSAR interferometric radar sensor are directly applicable to geological and geophysical studies. Attention is presently given to three illustrative examples of the use of DEMs: the correction of remote-sensing observations for local slope and topographic effects, topographic expressions of erosion and uplift in alluvial fans, and volcanology. The greatest advantages of TOPSAR over conventional photogrammetry include rapidity of data collection, high spatial and vertical resolution, and the ability to obtain contiguous data independent of cloud cover.

Evans, Diane L.↗

NASA NTRS1997

PMMW Camera TRP

Passive millimeter wave (PMMW) sensors have the ability to see through fog, clouds, dust and sandstorms and thus have the potential to support all-weather operations, both military and commercial. Many of the applications, such as military transport or commercial aircraft landing, are technologically stressing in that they require imaging of a scene with a large field of view in real time and with high spatial resolution. The development of a low cost PMMW focal plane array camera is essential to obtain real-time video images to fulfill the above needs. The overall objective of this multi-year project (Phase 1) was to develop and demonstrate the capabilities of a W-band PMMW camera with a microwave/millimeter wave monolithic integrated circuit (MMIC) focal plane array (FPA) that can be manufactured at low cost for both military and commercial applications. This overall objective was met in July 1997 when the first video images from the camera were generated of an outdoor scene. In addition, our consortium partner McDonnell Douglas was to develop a real-time passive millimeter wave flight simulator to permit pilot evaluation of a PMMW-equipped aircraft in a landing scenario. A working version of this simulator was completed. This work was carried out under the DARPA-funded PMMW Camera Technology Reinvestment Project (TRP), also known as the PMMW Camera DARPA Joint Dual-Use Project. In this final report for the Phase 1 activities, a year by year description of what the specific objectives were, the approaches taken, and the progress made is presented, followed by a description of the validation and imaging test results obtained in 1997.

Source record↗

NASA NTRS2004

Neural Network for Image-to-Image Control of Optical Tweezers

A method is discussed for using neural networks to control optical tweezers. Neural-net outputs are combined with scaling and tiling to generate 480 by 480-pixel control patterns for a spatial light modulator (SLM). The SLM can be combined in various ways with a microscope to create movable tweezers traps with controllable profiles. The neural nets are intended to respond to scattered light from carbon and silicon carbide nanotube sensors. The nanotube sensors are to be held by the traps for manipulation and calibration. Scaling and tiling allow the 100 by 100-pixel maximum resolution of the neural-net software to be applied in stages to exploit the full 480 by 480-pixel resolution of the SLM. One of these stages is intended to create sensitive null detectors for detecting variations in the scattered light from the nanotube sensors.

Decker, Arthur J.↗

NASA NTRS1982

The MLA program at NASA

The Thematic Mapper (TM) on Landsat-D represents a significant improvement compared to the Multispectral Scanner (MSS) of the current Landsat satellites. However, there is a need for even higher spatial and spectral resolution. Such developments would, for instance, provide a significantly greater capability for mineral identification and the detection of vegetation stress. The pushbroom mode of imaging utilizing solid state linear or area arrays is widely regarded as the best approach to overcome the inherent limitations of a scanning type system. The Multispectral Linear Array (MLA) has become the generic term for the sensor concept and the technology associated with solid state electronically scanned arrays operating in the pushbroom mode. A brief review is provided of the MLA instrument concepts, associated technology developments, program status, and future plans.

Ando, K. J.↗

NASA NTRS1998

Arctic Sea Ice Motion from Wavelet Analysis of Satellite Data

Wavelet analysis of DMSP SSM/I (Special Sensor Microwave/Imager) 85 GHz and 37 GHz radiance data, SMMR (Scanning Multichannel Microwave Radiometer) 37 GHz, and NSCAT (NASA Scatterometer) 13.9 GHZ data can be used to obtain daily sea ice drift information for both the northern and southern polar regions. The derived maps of sea ice drift provide both improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing data from satellite synthetic aperture radars (SAR). Examples of derived ice-drift maps in the Arctic illustrate large-scale circulation reversals within a period of a couple weeks. Comparisons with ice displacements derived from buoys show good quantitative agreement. NASA Scatterometer (NSCAT) 13.9 GHZ data have been also used for wavelet analysis to derive sea-ice drift. First, the 40' incidence-angle, sigma-zero (surface roughness) daily map of whole Arctic region with 25 km of pixel size from satellite's 600 km swath has been constructed. Then, the similar wavelet transform procedure to SSM/I data can be applied. Various scales of wavelet transform and threshold have been tested. By overlaying , neighbor filtering, and block-averaging the results of multiscale wavelet transforms, the final sea ice drift vectors are much smooth and representative to the sea ice motion. This wavelet analysis procedure is robust and can make a major contribution to the understanding of ice motion over large areas at relatively high temporal resolutions. The results of wavelet analysis of SSM/I and NSCAT images and buoy data can be merged by some data fusion techniques and will help to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model.

Liu, Antony K.↗

NASA NTRS2017

Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

MODIS BRDF OMI clouds NO2 GLER↗