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NASA NTRS2001

Estimation of comprehensive forest variable sets from multiparameter SAR data over a large area with diverse species

Polarimetric and multifrequency data from the NASA/JPL airborne synthetic aperture radar (AIRSAR) have been used in a multi-tier estimation algorithm to calculate a comprehensive set of forest canopy properties including branch layer moisture and thickness, trunk density, trunk water content and diameter, trunk height, and subcanapy soil moisture. The estimation algorithm takes advantage of species-specific allometric relations, and is applied to a 100Km x 100Km area in the Canadian boreal region containing many different vegetation species types. The results show very good agreement with ground measurements taken at several focused and auxiliary study sites. This paper expands on the results reported in [1] and applies the algorithm on the regional scale.

variable estimation forestry multiparameter SAR↗

NASA NTRS2007

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Interpolating scattered data points is a problem of wide ranging interest. A number of approaches for interpolation have been proposed both from theoretical domains such as computational geometry and in applications' fields such as geostatistics. Our motivation arises from geological and mining applications. In many instances data can be costly to compute and are available only at nonuniformly scattered positions. Because of the high cost of collecting measurements, high accuracy is required in the interpolants. One of the most popular interpolation methods in this field is called ordinary kriging. It is popular because it is a best linear unbiased estimator. The price for its statistical optimality is that the estimator is computationally very expensive. This is because the value of each interpolant is given by the solution of a large dense linear system. In practice, kriging problems have been solved approximately by restricting the domain to a small local neighborhood of points that lie near the query point. Determining the proper size for this neighborhood is a solved by ad hoc methods, and it has been shown that this approach leads to undesirable discontinuities in the interpolant. Recently a more principled approach to approximating kriging has been proposed based on a technique called covariance tapering. This process achieves its efficiency by replacing the large dense kriging system with a much sparser linear system. This technique has been applied to a restriction of our problem, called simple kriging, which is not unbiased for general data sets. In this paper we generalize these results by showing how to apply covariance tapering to the more general problem of ordinary kriging. Through experimentation we demonstrate the space and time efficiency and accuracy of approximating ordinary kriging through the use of covariance tapering combined with iterative methods for solving large sparse systems. We demonstrate our approach on large data sizes arising both from synthetic sources and from real applications.

Memarsadeghi, Nargess↗

NASA NTRS2011

Prediction of Hydrological Drought: What Can We Learn From Continental-Scale Offline Simulations?

Land surface model experiments are used to quantify, across the coterminous United States, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Forecasted streamflows are compared to naturalized streamflow observations where available and to synthetic (model-generated) streamflow data elsewhere. We find that snow initialization has a major impact on skill in the mountainous western U.S. and in a portion of the northern Great Plains; a mid-winter (January 1) initialization of snow in these areas leads to significant skill in the spring melting season. Soil moisture initialization also contributes to skill, and although the maximum contributions are not as large as those seen for snow initialization, the soil moisture contributions extend across a much broader geographical area. Soil moisture initialization can contribute to skill at long leads (up to 5 or 6 months), particularly for forecasts issued during winter.

Koster, Randal↗

NASA NTRS2011

Multi-Modal Image Registration and Matching for Localization of a Balloon on Titan

A solution was developed that matches visible/IR imagery aboard a balloon in Saturn's moon Titan's atmosphere to SAR (synthetic aperture radar) and visible/IR data acquired from orbit. A balloon in Titan's atmosphere must be able to localize itself autonomously both globally and with respect to local terrain. The orbital data is used to provide the balloon imagery with global context. The work is novel in applying mutual information (MI) to orbital vs. aerial data. There are unique challenges in this setting. Image offsets are much higher than in medical imaging, there is local distortion due to 3D terrain relief, and the fields of regard from orbit and from the air are quite different.

Ansar, Adnan I.↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Harrivel, Angela↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Harrivel, Angela↗

NASA NTRS2014

Assessing the Origins of Aliphatic Amines in the Murchison Meteorite from their Compound-Specific Carbon Isotopic Ratios and Enantiomeric Composition

The study of meteoritic organic compounds provides a unique window into the chemical inventory of the early Solar System and prebiotic chemistry that may have been important for the origin of life on Earth. Multiple families of organic compounds have been extracted from the Murchison meteorite, which is one of the most thoroughly studied carbonaceous chondrites. The amino acids extracted from Murchison have been extensively analyzed, including measurements of non-terrestrial stable isotopic ratios and discoveries of L-enantiomeric excesses for alpha-dialkyl amino acids, notably isovaline. However, although the isotopic signatures of bulk amine-containing fractions have been measured, the isotopic ratios and enantiomeric composition of individual aliphatic amines, compounds that are chemically related to amino acids, remain unknown. Here, we report a novel method for the extraction, separation, identification and quantitation of aliphatic monoamines extracted from the Murchison meteorite. Our results show a complete suite of structural isomers, with a larger concentration of methylamine and ethylamine and decreasing amine concentrations with increasing carbon number. The carbon isotopic compositions of fourteen meteoritic aliphatic monoamines were measured, with delta C-13 values ranging from +21% to +129%, showing a decrease in C-13 with increasing carbon number, a relationship that may be consistent with the chain elongation mechanism under kinetic control previously proposed for meteoritic amino acids. We also found the enantiomeric composition of sec-butylamine, a structural analog to isovaline, was racemic within error, while the isovaline extracted from the same Murchison piece showed an L-enantiomeric excess of 9.7; this result suggested that processes leading to enantiomeric excess in the amino acid did not affect the amine. We used these collective data to assess the primordial synthetic origins of these meteoritic aliphatic amines and their potential linkage to meteoritic amino acids.

prebiotic chemistry↗

NASA NTRS2016

Aliphatic Amines in Antarctic CR2, CM2, and CM1/2 Carbonaceous Chondrites

Meteoritic water-soluble organic compounds provide a unique record of the processes that occurred during the formation of the solar system and the chemistry preceding the origins of life on Earth. We have investigated the molecular distribution, compound-specific delta13C isotopic ratios and enantiomeric compositions of aliphatic monoamines present in the hot acid-water extracts of the carbonaceous chondrites LAP 02342 (CR2), GRA 95229 (CR2), LON 94101 (CM2), LEW 90500 (CM2), and ALH 83100 (CM1/2). Analyses of the concentration of monoamines in these meteorites revealed: (a) the CR2 chondrites studied here contain higher concentrations of monoamines relative to the analyzed CM2 chondrites; (b) the concentration of monoamines decreases with increasing carbon number; and (c) isopropylamine is the most abundant monoamine in these CR2 chondrites, while methylamine is the most abundant amine species in these CM2 and CM1/2 chondrites. The delta13C values of monoamines in CR2 chondrite do not correlate with the number of carbon atoms; however, in CM2 and CM1/2 chondrites, the 13C enrichment decreases with increasing monoamine carbon number. The delta13C values of methylamine in CR2 chondrites ranged from −1 to +10per mille, while in CM2 and CM1/2 chondrites the delta13C values of methylamine ranged from +41 to +59per mille. We also observed racemic compositions of sec-butylamine, 3-methyl-2-butylamine, and sec-pentylamine in the studied carbonaceous chondrites. Additionally, we compared the abundance and delta13C isotopic composition of monoamines to those of their structurally related amino acids. We found that monoamines are less abundant than amino acids in CR2 chondrites, with the opposite being true in CM2 and CM1/2 chondrites. We used these collective data to evaluate different primordial synthetic pathways for monoamines in carbonaceous chondrites and to understand the potential common origins these molecules may share with meteoritic amino acids.

Meteoritic water-soluble organic compounds↗

NASA NTRS2020

Terrain Relative Navigation for Guided Descent on Titan

Titan’s dense atmosphere, low gravity, and high winds at high altitudes create descent times of >90 minutes with standard entry/descent/landing (EDL) architectures and result in large unguided landing ellipses, with 99% values of 110x110 km and 149x72 km in recent Titan lander proposals. Enabling precision landing on Titan could increase science return for the types of missions proposed to date and make additional types of landing sites accessible, opening up new possibilities for science investigations. Precision landing on Titan has unique challenges, because the hazy atmosphere makes it difficult to see the surface and because it requires guided descent with divert ranges that are one to two orders of magnitude larger than needed for other target bodies, i.e. up to on the order of 100 km. It is conceivable that such a divert capability could be provided economically by a parafoil or other steerable aerodynamic decelerator deployed several 10s of km above the surface. The long descent times lead to large inertial navigation errors, hence a need for terrain relative navigation (TRN). This would require a TRN capability that can operate at such altitudes, despite challenges of seeing the surface sufficiently clearly and of depending on map products that are two orders of magnitude lower in spatial resolution than those for Mars and airless bodies. We then develop algorithms for map matching and feature tracking with descent images and test these with synthetic images created from Cassini/Huygens data sets and our radiative transfer model. We also introduce new possibilities for TRN based on the potential to discriminate some specific types of terrain onboard in descent imagery, such as lake vs adjacent ground and dune vs interdune. We use sensor measurement noise models in simulations of state estimation with an extended Kalman filter that includes coordinates of a set of tracked features in the state vector. Case studies were done for two notional landing sites, one in a site with only dry ground and one in a Titan lake district. In both cases, the filter error model shows 3 position error at touchdown on the order of 2 km. More work is needed to validate these results with higher fidelity camera models and larger data sets, but this is very promising.

Matthies, Larry↗

NASA NTRS2022

Lower Illinois River Valley Ecological Forecasting: Inundation Mapping of the Lower Illinois River Valley Using Synthetic Aperture Radar and Optical Satellite Imagery for Wetland Conservation and Restoration Prioritization Efforts

The Lower Illinois River Valley (LIRV) is home to some of the richest agricultural lands in the United States and its wetlands provide key ecosystem services like clean water and flood reduction. It has also experienced extensive degradation due to development and urban pollution. The Great Rivers Land Trust (GRLT), the National Great Rivers Research & Education Center, Principia College, and the American Geophysical Union’s (AGU) Thriving Earth Exchange sought to incorporate inundation and surface water extent layers into their geodatabases to more accurately identify priority areas for wetland restoration. This project aimed to determine the feasibility of detecting inundation extent and duration along the valley using remotely sensed data. We used Sentinel-1 C-band Synthetic Aperture Radar (SAR) data to classify open water and inundated vegetation within the study site. The open water classification was compared to Dynamic Surface Water Extent(DSWE) derived from Landsat 8 Operational Land Imager. We successfully created layers of inundation minimum and maximum extent, as well as inundation duration across the study area for 2019 and 2020. The open water classification resulted in an overall accuracy of 86% when validated against DSWE classifications. These analyses will help end users to identify high priority areas along the LIRV best suited for land conversion projects in the future.

Vanessa Machuca↗

NASA NTRS2006

Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity

Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10,19, and 37 GHz. This depolarization .would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity.

Maslanik, J. A.↗

NASA NTRS2020

Colorado & New Mexico Water Resources: Mapping Wetland and Riparian Areas to Support Rio Grande Cutthroat Trout Habitat Restoration

Over the last century, the Rio Grande cutthroat trout (Oncorhynchus clarki virginalis; RGCT) population has declined significantly due to habitat loss, competition, and hybridization with non-native trout species; the species currently occupies roughly 11% of its historic habitat. Conservation efforts led by governmental and private actors have succeeded in increasing RGCT populations since the early 2000s. Vermejo Park Ranch, a privately owned 560,000-acre property, partnered with US Fish and Wildlife Service and Colorado Parks and Wildlife (CPW) to begin the largest native trout restoration initiative in North America. Since 2002, these efforts have included wetland and riparian area restoration and RGCT reintroduction. Current restoration efforts focus on restoring the Costilla Creek Watershed to provide cool water temperatures, improve water quality, and create the necessary habitat requirements for the trout species. To guide these restoration efforts, the Colorado – Fort Collins NASA DEVELOP team produced maps to locate and characterize wetland and riparian areas in the Costilla Creek watershed. The team utilized NASA data from Landsat 8 Operational Land Imager (OLI), as well as Sentinel-2 MultiSpectral Instrument (MSI), Sentinel-1 Synthetic Aperture Radar (SAR), and additional ancillary data for May 2016 to October 2019. In order to produce probability maps of wetland presence, the team used the Software for Assisted Habitat Modeling (SAHM) incorporating predictor variables generated from topographic indices, spectral indices, and radar. The resulting maps allowed Vermejo Ranch and CPW to determine the extent of possible RGCT habitat and identify where habitat restoration efforts may be needed.

Water Resources↗

NASA NTRS1990

Synthetic Aperture Radar Imagery of Airports and Surrounding Areas: Denver Stapleton International Airport

This is the third in a series of three reports which address the statistical description of ground clutter at an airport and in the surrounding area. These data are being utilized in a program to detect microbursts. Synthetic aperture radar (SAR) data were collected at the Denver Stapleton Airport using a set of parameters which closely match those which are anticipated to be utilized by an aircraft on approach to an airport. These data and the results of the clutter study are described. Scenes of 13 x 10 km were imaged at 9.38 GHz and HH-, VV-, and HV-polarizations, and contain airport grounds and facilities (up to 14 percent), cultural areas (more than 50 percent), and rural areas (up to 6 percent). Incidence angles range from 40 to 84 deg. At the largest depression angles the distributed targets, such as forest, fields, water, and residential, rarely had mean scattering coefficients greater than -10 dB. From 30 to 80 percent of an image had scattering coefficients less than -20 dB. About 1 to 10 percent of the scattering coefficients exceeded 0 dB, and from 0 to 1 percent above 10 dB. In examining the average backscatter coefficients at large angles, the clutter types cluster according to the following groups: (1) terminals (-3 dB), (2) city and industrial (-7 dB), (3) warehouse (-10 dB), (4) urban and residential (-14 dB), and (5) grass (-24 dB).

Onstott, Robert G.↗

NASA NTRS1988

Color graphics workstations used for simultaneous display of satellite and model data sets

Model-measurement display methods for studying actual or synthetic satellite measurements of cloudiness are developed. Visualization and animation techniques are employed to analyze the data. Two types of animation sequences, one based on Insat IR geosynchronous satellite imagery combined with upper level velocity potentials calculations and isoline depictions of the high amplitude centers of low frequency cloudiness activity, and the other combines a mesoscale cloud model simulation of a severe hail storm and synthetic microwave radiation signatures, are described.

Cooper, Harry J.↗

NASA NTRS1989

Segmentation of multifrequency polarimetric radar images to facilitate the inference of geophysical parameters

An unsupervised clustering algorithm is used to segment multifrequency polarimetric radar data from the NASA/JPL airborne SAR (synthetic aperture radar). Twenty-two parameters are evaluated for their discriminatory capability for each pixel of an image. A clustering analysis is then performed using different subsets of these parameters. This analysis relies on data taken as part of an intensive field experiment during the summer of 1988 in the vicinity of the Pisgah lava flow in the Mojave Desert in southern California. As part of the experiment, extensive ground truth was acquired, including dielectric constant and topography measurements. Segmentation results show good agreement with these measurements.

Burnette, C F.↗

NASA NTRS1992

Processing of polarimetric SAR data for soil moisture estimation over Mahantango watershed area

Microwave remote sensing technique has a high potential for measuring soil moisture due to the large contrast in dielectric constant of dry and wet soils. Recent work by Pults et al. demonstrated the use of X/C-band data for quantitative surface soil moisture extraction from Airborne Synthetic Aperture Radar (SAR) system. Similar technique was adopted using polarimetric SAR data acquired with the JPL-AIRSAR system over the Mahantango watershed area in central Pennsylvania during July 1990. The data sets reported include C-, L-, and P-bands of 10, 13, 15, and 17 July 1990.

Rao, K. S.↗

NASA NTRS1996

Geostatistical approaches to interpolation and classification of remote-sensing data from ice surfaces

Geostatistical methods for interpolation and extrapolation techniques are used in glaciological data analysis. The results of a program involving the mapping of the Antarctica from satellite radar altimeter data are discussed. A combination of high and low resolution techniques was applied in the analysis of the Bering Glacier (Alaska). The global positioning system (GPS) located video data collected from small aircraft and the ERS-1 synthetic aperture radar (SAR) images were used. From the perspective of SAR data analysis, the Bering Glacier surge was the opportunity to characterize the surface of fast flowing ice and the rapid changes in the surface roughness.

Herzfeld, Ute Christina↗

NASA NTRS2010

Measurement and Mitigation of the Ionosphere in L-Band Interferometric SAR Data

Satellite-based repeat-pass Interferometric Synthetic Aperture Radar (InSAR) provides a synoptic high spatial resolution perspective of Earth's changing surface, permitting one to view large areas quickly and efficiently. By measuring relative phase change from one observation to the next on a pixel-by-pixel basis, maps of deformation and change can be derived. Variability of the atmosphere and the ionosphere leads to phase/time delays that are present in the data that can mask many of the subtle deformation signatures of interest, so methods for mitigation of these effects are important. Many of these effects have been observed in existing ALOS PALSAR data, and studies are underway to characterize and mitigate the ionosphere using these data. Since the ionosphere is a dispersive medium, it is possible in principle distinguish the ionospheric signatures from the non-dispersive effects of deformation and the atmosphere. In this paper, we describe a method for mapping the ionosphere in InSAR data based on a multi-frequency split-spectrum processing technique.

Rosen, Paul A.↗