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DOE OSTI2024

In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots

Abstract Background Nitrate (NO 3 − ) is one of the two major forms of inorganic nitrogen absorbed by plant roots, and the tissue nitrate concentration in roots is considered important for optimizing developmental programs. Technologies to quantify the expression levels of nitrate transporters and assimilating enzymes at the cellular level have improved drastically in the past decade. However, a technological gap remains for detecting nitrate at a high spatial resolution. Using extraction-based methods, it is challenging to reliably estimate nitrate concentration from a small volume of cells (i.e., with high spatial resolution), since targeting a small or specific group of cells is physically difficult. Alternatively, nitrate detection with microelectrodes offers subcellular resolution with high cell specificity, but this method has some limitations on cell accessibility and detection speed. Finally, optical nitrate biosensors have very good ( in-vivo ) sensitivity (below 1 mM) and cellular-level spatial resolution, but require plant transformation, limiting their applicability. In this work, we apply Raman microspectroscopy for high-dynamic range in-vivo mapping of nitrate in different developmental zones of Arabidopsis thaliana roots in-situ . Results As a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5–10 mM). These results were validated through destructive measurement of nitrate concentration. Conclusions We present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.

Fernández González, Alma↗

NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗

NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗

DOE OSTI2023

NANCY: Next-generation All-sky Near-infrared Community surveY

The Nancy Grace Roman Space Telescope is capable of delivering an unprecedented all-sky, high-spatial resolution, multi-epoch infrared map to the astronomical community. This opportunity arises in the midst of numerous ground- and space-based surveys that will provide extensive spectroscopy and imaging together covering the entire sky (such as Rubin/LSST, Euclid, UNIONS, SPHEREx, DESI, SDSS-V, GALAH, 4MOST, WEAVE, MOONS, PFS, UVEX, NEO Surveyor, etc.). Roman can uniquely provide uniform high-spatial-resolution (~0.1 arcsec) imaging over the entire sky, vastly expanding the science reach and precision of all of these near-term and future surveys. This imaging will not only enhance other surveys, but also facilitate completely new science. By imaging the full sky over two epochs, Roman can measure the proper motions for stars across the entire Milky Way, probing 100 times fainter than Gaia out to the very edge of the Galaxy. Here, we propose NANCY: a completely public, all-sky survey that will create a high-value legacy dataset benefiting innumerable ongoing and forthcoming studies of the universe. NANCY is a pure expression of Roman's potential: it images the entire sky, at high spatial resolution, in a broad infrared bandpass that collects as many photons as possible. The majority of all ongoing astronomical surveys would benefit from incorporating observations of NANCY into their analyses, whether these surveys focus on nearby stars, the Milky Way, near-field cosmology, or the broader universe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2012

From Radio with Love: An Overview of the Role of Radio Observations in Understanding High-Energy Emission from Active Galaxies

The gamma-ray satellite Fermi and the ground based TeV facilities MAGIC, VERITAS and HESS have ushered in a new era in the observation of high-energy emission from active galaxies. The energy budgets of these objects have a major contribution from gamma-rays and it is simply not possible to understand their physics without high-energy observations. Though the exact mechanisms for high-energy production in galaxies remains an open question, gamma-rays typically result from interactions between high-energy particles. Via different interactions these same particles can produce radio emission. Thus the non-thermal nature of gamma-ray emission practically guarantees that high-energy emitters are also radio loud. Aside from their obvious role as a component of multiwavelength analysis, radio observations provide two crucial elements essential to understanding the source structure and physical processes of high-energy emitters: very high timing resolution and very high spatial resolution. A brief overview of the unique role played by radio observations in unraveling the mysteries of the high energy Universe as presented here.

Ojha, Roopesh↗

NASA NTRS1999

Preliminary Correlations of Gravity and Topography from Mars Global Surveyor

The Mars Global Surveyor (MGS) spacecraft is currently in a 400-km altitude polar mapping orbit and scheduled to begin global mapping of Mars in March of 1999. Doppler tracking data collected in this Gravity Calibration Orbit prior to the nominal mapping mission combined with observations from the MGS Science Phasing Orbit in Spring - Summer 1999 and the Viking and mariner 9 orbiters has led to preliminary high resolution gravity fields. Spherical harmonic expansions have been performed to degree and order 70 and are characterized by the first high spatial resolution coverage of high latitudes. Topographic mapping by the Mars Orbiter Laser Altimeter on MGS is providing measurements of the height of the martian surface with sub-meter vertical resolution and 5-30 m absolute accuracy. Data obtained during the circular mapping phase are expected to provide the first high resolution measurements of surface heights in the southern hemisphere. The combination of gravity and topography measurements provides information on the structure of the planetary interior, i.e. the rigidity and distribution of internal density. The observations can also be used to address the mechanisms of support of surface topography. Preliminary results of correlations of gravity and topography at long planetary wavelengths will be presented and the implications for internal structure will be addressed.

Zuber, M. T.↗

NASA NTRS2001

Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.

Bingham, G. E.↗

NASA NTRS1996

Evolutionary status of the pre-protostellar core L1498

L1498 is a classic example of a dense cold pre-protostellar core. To study the evolutionary status, the structure, dynamics, and chemical properties of this core we have obtained high spatial and high spectral resolution observations of molecules tracing densities of 10(3)-10(5) cm-3. We observed CCS, NH3, C3H2, and HC7N with NASA's DSN 70 m antennas. We also present large-scale maps of C18O and 13CO observed with the AT&T 7 m antenna. For the high spatial resolution maps of selected regions within the core we used the VLA for CCS at 22 GHz, and the Owens Valley Radio Observatory (OVRO) MMA for CCS at 94 GHz and CS (2-1). The 22 GHz CCS emission marks a high-density [n(H2) > 10(4) cm -3] core, which is elongated with a major axis along the SE-NW direction. NH3 and C3H2 emissions are located inside the boundary of the CCS emission. C18O emission traces a lower density gas extending beyond the CCS boundary. Along the major axis of the dense core, CCS, NH3 and C3H2 emission show evidence of limb brightening. The observations are consistent with a chemically differentiated onion-shell structure for the L1498 core, with NH3 in the inner and CCS in the outer parts of the core. The high angular resolution (9"-12") spectral line maps obtained by combining NASA Goldstone 70 m and VLA data resolve the CCS 22 GHz emission in the southeast and northwest boundaries into arclike enhancements, supporting the picture that CCS emission originates in a shell outside the NH3 emitting region. Interferometric maps of CCS at 94 GHz and CS at 98 GHz show that their emitting regions contain several small-scale dense condensations. We suggest that the differences between the CCS, CS, C3H2, and NH3 emission are caused by a time-dependent effect as the core evolves slowly. We interpret the chemical and physical properties of L1498 in terms of a quasi-static (or slowly contracting) dense core in which the outer envelope is still growing. The growth rate of the core is determined by the density increase in the CCS shell resulting from the accretion of the outer low-density gas traced by C18O. We conclude that L1498 could become unstable to rapid collapse to form a protostar in less than 5 x 10(6) yr.

NASA Discipline Exobiology↗

NASA NTRS1991

A new technique for enlargement and reconstruction of digital sensor imagery

A new image enlargement and reconstruction routine, the digital image enlarging balanced reconstruction algorithm (DIEBRA), is described. Using a highly modified form of 'balanced' two-dimensional polynomial interpolation, this program enlarges digital imagery, creating synthetic high spatial resolution images. Statistical analysis shows the DIEBRA-generated imagery to be significantly closer to true high spatial resolution imagery at all frequencies than imagery generated by a cubic convolutional reconstruction filter.

Rhea, W. Joseph↗

DOE OSTI2026

Spatially Resolved Domicile Charging Demands for Light-, Medium-, and Heavy-Duty Electric Vehicles in Virginia

The use of plug-in electric vehicles (PEVs) and resulting grid impacts are likely to grow rapidly, and evaluation of optimal smart charge management and grid integration strategies is warranted now. Evaluating distribution grid impacts requires fine-grained models of PEV operations to estimate charging loads across diverse vehicles at high spatial resolution. We propose such a model and consider a high-electrification scenario in Richmond and Newport News, Virginia. Our framework considers four categories of vehicle that are amenable to early aggressive electrification: light-duty passenger vehicles (LDV), trucks and vans with a focus on delivery or other local operations, school buses, and transit buses. These vehicles have a relatively consistent domicile, reducing the need for public charging infrastructure rollout to electrify. We apply a recent LDV model and propose new models for each vocation of medium- and heavy-duty vehicle, leveraging telematics data. We demonstrate our framework in Virginia and find energy demands in the region may total 15 GWh day, with most consumed by LDV. However, considering power demand at high spatial resolution reveals a different trend: LDVs have relatively small peak loads at specific sites (peak site demand around 800 kW) compared to average and high demand medium- and heavy-duty vehicle charging sites (peak site demand around 6,000 kW at a transit bus depot, 1,500 kW at a local freight hub, and 1,000 kW at a school). Our framework yields insights on the relative impacts of each vocation and enables future work to tailor grid integration strategies to each vehicle category.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1982

Advances in solar radio astronomy

The status of the observations and interpretations of the sun's radio emission covering the entire radio spectrum from millimeter wavelengths to hectometer and kilometer wavelengths is reviewed. Emphasis is given to the progress made in solar radio physics as a result of recent advances in plasma and radiation theory. It is noted that the capability now exists of observing the sun with a spatial resolution of approximately a second of arc and a temporal resolution of about a millisecond at centimeter wavelengths and of obtaining fast multifrequency two-dimensional pictures of the sun at meter and decameter wavelengths. A summary is given of the properties of nonflaring active regions at millimeter, centimeter, and meter-decameter wavelengths. The properties of centimeter wave bursts are discussed in connection with the high spatial resolution observations. The observations of the preflare build-up of an active region are reviewed. High spatial resolution observations (a few seconds of arc to approximately 1 arcsec) are discussed, with particular attention given to the one- and two-dimensional maps of centimeter-wavelength burst sources.

Kundu, M. R.↗

NASA NTRS2005

Generic Sensor Modeling Using Pulse Method

Recent development of high spatial resolution satellites such as IKONOS, Quickbird and Orbview enable observation of the Earth's surface with sub-meter resolution. Compared to the 30 meter resolution of Landsat 5 TM, the amount of information in the output image was dramatically increased. In this era of high spatial resolution, the estimation of spatial quality of images is gaining attention. Historically, the Modulation Transfer Function (MTF) concept has been used to estimate an imaging system's spatial quality. Sometimes classified by target shapes, various methods were developed in laboratory environment utilizing sinusoidal inputs, periodic bar patterns and narrow slits. On-orbit sensor MTF estimation was performed on 30-meter GSD Landsat4 Thematic Mapper (TM) data from the bridge pulse target as a pulse input . Because of a high resolution sensor s small Ground Sampling Distance (GSD), reasonably sized man-made edge, pulse, and impulse targets can be deployed on a uniform grassy area with accurate control of ground targets using tarps and convex mirrors. All the previous work cited calculated MTF without testing the MTF estimator's performance. In previous report, a numerical generic sensor model had been developed to simulate and improve the performance of on-orbit MTF estimating techniques. Results from the previous sensor modeling report that have been incorporated into standard MTF estimation work include Fermi edge detection and the newly developed 4th order modified Savitzky-Golay (MSG) interpolation technique. Noise sensitivity had been studied by performing simulations on known noise sources and a sensor model. Extensive investigation was done to characterize multi-resolution ground noise. Finally, angle simulation was tested by using synthetic pulse targets with angles from 2 to 15 degrees, several brightness levels, and different noise levels from both ground targets and imaging system. As a continuing research activity using the developed sensor model, this report was dedicated to MTF estimation via pulse input method characterization using the Fermi edge detection and 4th order MSG interpolation method. The relationship between pulse width and MTF value at Nyquist was studied including error detection and correction schemes. Pulse target angle sensitivity was studied by using synthetic targets angled from 2 to 12 degrees. In this report, from the ground and system noise simulation, a minimum SNR value was suggested for a stable MTF value at Nyquist for the pulse method. Target width error detection and adjustment technique based on a smooth transition of MTF profile is presented, which is specifically applicable only to the pulse method with 3 pixel wide targets.

Helder, Dennis L.↗

DOE OSTI2021

Nanoscale imaging of Gilbert damping using signal amplitude mapping

Ferromagnetic resonance force microscopy (FMRFM) is a powerful scanned probe technique that uses sub-micrometer-scale, spatially localized standing spin wave modes (LMs) to perform local ferromagnetic resonance (FMR) measurements. In this work, we show the spatially resolved imaging of Gilbert damping in a ferromagnetic material (FM) using FMRFM. Typically damping is measured from the FMR linewidth. We demonstrate an approach to image the spatial variation of Gilbert damping utilizing the LM resonance peak height to measure the LM resonance cone angle. This approach enables determination of damping through field-swept FMRFM at a single excitation frequency. The extreme force sensitivity of similar to 2 fN at room temperature can resolve changes of Gilbert damping as small as ~2 x 10 -4 at 2GHz, corresponding to ~0.16Oe in FMR linewidth resolution. This high sensitivity, high spatial resolution, and single frequency imaging of Gilbert damping creates the opportunity to study spin interactions at the interface between an insulating FM and a small volume of nonmagnetic material such as atomically thin two-dimensional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRSDate not supplied

Illustrating the Spatiotemporal Complexity of No2 Columns Using A Multi-Perspective Observing System: Moving Toward Geostationary Product Validation and Applications

As a precursor to secondary pollutants like ozone and PM2.5, nitrogen dioxide (NO2) is crucial to understand when addressing air quality issues. However, due to NO2’s short lifetime during the daytime and complexity of emission sources in urbanized regions, interpreting datasets from ground or satellite perspectives alone are challenged by variance in spatial and temporal resolutions. High resolution airborne mapping (< 1 km) of NO2 column densities across morning, midday, and afternoon add a unique perspective toward interpreting satellite data with respect to ground-measurements. This presentation focuses on the interpretation of spatiotemporal complexity of NO2 columns from the Synergistic TEMPO Air Quality Science Study (STAQS). The mission’s goal is to integrate geostationary observations from Tropospheric Emissions: Monitoring of Pollution (TEMPO) with traditional and enhanced air quality monitoring to improve the understanding of air quality science for increased societal benefit. We will demonstrate the interweaved perspective of NO2 columns from ground-based Pandora spectrometers and satellite-based observations (e.g., TROPOMI) as compared to high spatial resolution airborne observations from the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS). This includes the evaluation of each dataset through comparison to each other to identify potential biases in data products and the impact of heterogeneity on these comparisons. Airborne data will also be used as a proxy for geostationary observations with morning, midday, and afternoon raster maps collected over four cities (Los Angeles, Chicago, Toronto, and New York City). Finally, recent research outcomes will be presented to demonstrate how airborne and geostationary observations can be used to evaluate emission inventories and air quality models.

Laura Judd↗

DOE OSTI2021

Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution

Laser ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging method that has the potential to transform the field of metabolomics. This is in part due to LAESI-MS being an ambient ionization method that requires minimal sample preparation and uses (endogenous) water for in situ analysis. This application note details the employment of the ‘LAESI microscope’ source to perform spatially resolved MS analysis of cells and MS imaging (MSI) of tissues at high spatial resolution. This source configuration utilizes a long-working distance reflective objective that permits both visualization of the sample and a smaller LAESI laser beam profile than conventional LAESI setups. In this work, we analyzed 200 single cells of Allium cepa (red onion) and imaged Fittonia argyroneura (nerve plant) in high spatial resolution using this source coupled to a Fourier transform mass spectrometer for high mass resolution and high mass accuracy metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

The retrieval algorithms used for optical remote sensing satellite data to estimate Earth's geophysical properties have specific requirements for spatial resolution, temporal revisit, spectral range and resolution, and instrument signal-to-noise ratio (SNR) performance to meet biogeoscience objectives. Studies to estimate surface properties from hyperspectral data use a range of algorithms sensitive to various sources of spectroscopic uncertainty, which are in turn influenced by mission architecture choices. Retrieval algorithms vary across scientific fields and may be more or less sensitive to mission architecture choices that affect spectral, spatial, or temporal resolutions and spectrometer SNR. We used representative remote sensing algorithms across terrestrial and aquatic study domains to inform aspects of mission design that are most important for impacting accuracy in each scientific area. We simulated the propagation of uncertainties in the retrieval process including the effects of different instrument configuration choices. We found that retrieval accuracy and information content degrade consistently at >10 nm spectral resolution, >30 m spatial resolution, and >8-day revisit. In these studies, the noise reduction associated with lower spatial resolution improved accuracy vis à vis high spatial resolution measurements. The interplay between spatial resolution, temporal revisit, and SNR can be quantitatively assessed for imaging spectroscopy missions and used to identify key components of algorithm performance and mission observing criteria.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

A neural network approach to cloud classification

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

Lee, Jonathan↗

NASA NTRS1991

An overview of the results of the FIFE-87 and FIFE-89 campaigns

Results of a major land surface-atmosphere exchange study, the First ISLSCP Field Experiment (FIFE) are summarized. Findings result from nearly 80 days of field measurements over a 15 kilometer square area involving 30 science teams, seven remote sensing aircraft, and 5 satellites which acquired over 1200 low resolution and 35 high spatial resolution satellite images, maps of remotely sensed temperature, vegetation index and soil moisture, surface flux measurements from more than 20 ground stations and airborne sensors, and transects of vegetation, soil moisture and soil chemistry. Relationships between in situ, airborne, and spaceborne remote measurements and the problem of scaling will be discussed. Energy balance comparisons among sites were made. Diurnal measurements of latent heat fluxes indicated a strong correlation between the evaporative fraction at midday and the daytime average value.

Murphy, R. E.↗