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At least 109 records · Page 6

A Large Aperture Fabry-Perot Tunable Filter Based On Micro Opto Electromechanical Systems Technology

A research and development effort sponsored by the NASA Goddard Spaceflight Center (GSFC) is focused on applying Micro Opto Electromechanical Systems (MOEMS) technology to create a miniature Fabry-Perot tunable etalon for space and ground-based near infrared imaging spectrometer applications. Unlike previous devices developed for small-aperture telecommunications systems, the GSFC research is directed toward a novel 12 - 40 mm aperture for astrophysical studies, including emission line imaging of galaxies and nebulae, and multi-spectral redshift surveys in the 1.1 - 2.3 micron wavelength region. The MOEMS design features integrated electrostatic scanning of the 11-micron optical gap, and capacitance micrometry for closed loop control of parallelism within a 10-nm tolerance. The low thermal mass and inertia inherent in MOEMS devices allows for rapid cooling to the proposed 30 K operating temperature, and high frequency response. Achieving the proposed 6-nm aperture flatness (with an effective finesse of 50) represents the primary technical challenge in the current 12-mm prototype.

Greenhouse, Matt↗

Applying Tafkaa For Atmospheric Correction of Aviris Over Coral Ecosystems In The Hawaiian Islands

Growing concern over the health of coastal ecosystems, particularly coral reefs, has produced increased interest in remote sensing as a tool for the management and monitoring of these valuable natural resources. Hyperspectral capabilities show promising results in this regard, but as yet remain somewhat hindered by the technical and physical issues concerning the intervening water layer. One such issue is the ability to atmospherically correct images over shallow aquatic areas, where complications arise due to varying effects from specular reflection, wind blown surface waves, and reflectance from the benthic substrate. Tafkaa, an atmospheric correction algorithm under development at the U.S. Naval Research Laboratory, addresses these variables and provides a viable approach to the atmospheric correction issue. Using imagery from the Advanced Visible InfraRed Imaging Spectrometer (AVIRIS) over two shallow coral ecosystems in the Hawai ian Islands, French Frigate Shoals and Kane ohe Bay, we first demonstrate how land-based atmospheric corrections can be limited in such an environment. We then discuss the input requirements and underlying algorithm concepts of Tafkaa and conclude with examples illustrating the improved performance of Tafkaa using the same AVIRIS images.

Goodman, James A.↗

Ecosystem Impacts of Woody Encroachment In Texas: A Spatial Analysis Using AVIRIS

Woody encroachment, the increase of woody plant density relative to herbaceous vegetation, has been documented in drylands of Texas as well as worldwide (Archer 1994, Harrington and Harman 1995, Moleele et al. 2002). Over-grazing, fire suppression and climate change are implicated in the shift from open grasslands to ecosystems now populated by trees and shrubs (Scholes and Archer 1997, Archer et al. 2001), such as Prosopis glandulosa var. glandulosa (honey mesquite) in north Texas (Teague et al. 1997, Ansley et al. 2001, Asner et al. 2003a). Several studies have examined changes in ecosystem properties accompanying woody vegetation encroachment in the Southwest U.S., with research focused on increases in plant and soil carbon (C) and nitrogen (N) stores (Hoffman and Jackson 2000, Asner et al. 2003a), isotopic shifts in these pools (Boutton 1999, Archer et al. 2001), and increases in N cycling rates (Rundel et al. 1982, Hibbard et al. 2001). However, little is known regarding the impact of woody encroachment on N trace gas emissions from dryland regions such as Texas. NOx is produced in the soil during the processes of nitrification and denitrification (Firestone and Davidson 1989). The total N efflux from soils is most directly influenced by the internal cycling of N, which at a regionalscale, is controlled by the inputs and availability of N from vegetation via litterfall and subsequent decomposition (Robertson et al. 1989). Although plot-scale studies are critical to understanding controls over N oxide emissions, regionalization of the measurements is impeded by spatial variation in the factors contributing most to N cycling processes: soil properties (affecting soil moisture regimes and N stocks) and vegetation cover (affecting litter inputs and N uptake). While broad patterns in ecosystem structure and vegetation composition co-vary with general patterns of trace gas emissions (Matson 1997), there is no easily measured index of N availability that can be applied for regional-scale studies of N oxide fluxes. Remote sensing is arguably the only approach available to develop a spatially-explicit understanding of ecosystem processes. More specifically, remotely detectable spatial patterns in the distal controls over soil N properties, such as vegetation cover, land use and soil type (Robertson et al. 1989), should be exploited for regional studies of N oxide emissions. The woody encroachment phenomenon provides an opportunity to test the strength of the relationship between N oxide emissions and those factors controlling the fluxes that can be remotely measured. If such linkages can be firmly established, and if the spatial pattern of distal controls is relevant, then the combination of field measurements and remote sensing offers to improve regional-scale N oxide estimates. The paper presents the utility of linking field based sampling of soil NOx emissions with very high resolution remote sensing estimates of woody vegetation cover from the NASA AVIRIS, Airborne Visible-Infrared Imaging Spectrometer (Green et al. 1998, Asner and Green 2001) and automated spectral mixture analysis (Asner and Lobell 2000, Asner and Heidebrecht 2002) that provide a means to spatially extrapolate soil NOx emissions to the regional scale.

Martin, Roberta E.↗

AAT Observations of Shoemaker Levy-9 Collisions with Jupiter

We will use the Infrared Imaging Spectrometer (IRIS) on the 3.9m Anglo-Australian Telescope (AAT)to observe the collisions of the fragmented comet Shoemaker Levy-9 (SL9) with Jupiter on July 16-22.

IRIS K-band image fragments Jovian magnetosphere K↗

High Altitude Hyperspectral Remote Sensing with AVIRIS

None given. From Intro: This paper describes AVIRIS (the Airborne Visible and InfraRed Imaging Spectrometer) as a remote sensing instrument that is supported, calibrated, and maintained by JPL.

AVIRIS detector fiberoptics remote sensing spectro↗

Overview of AVIRIS Acquisitions in Argentina as Part of the NM EO-1 Campaign in 2001

This document presents an overview of Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) acquisitions in Argentina. The document initially discusses imaging spectroscopy, spectrum measurement, the AVIRIS instrument and AVIRIS performance. Additionally, AVIRIS imaging collection activities since its deployment to Argentina in January of 2001 are briefly cited.

Airborne Visible/Infrared Imaging Spectrometer (AV↗

Design and Manufacture of a Highly Reliable, Miniaturized and Low Mass Shutter Mechanism

This paper describes the development, manufacturing and testing of a lightweight shutter mechanism made of titanium for the MERTIS Instrument. MERTIS is a thermal infrared imaging spectrometer onboard ESA's future BepiColombo mission to Mercury. The mechanism is built as a parallelogram arrangement of flexible hinges, actuated by a voice coil. In a first test run, it was shown that the selected EDM processing led to the generation of titanium oxides and an oxygen-enriched surface layer on the substrate (so called alpha-case layer). In the revised version of the shutter, it was possible to manufacture the complex geometry by micro-milling and an adjacent pickling procedure. The adequacy of this approach was verified by lifetime and vibration testing.

Manhart, M.↗

Benefits of Sharing Information from Commercial Airborne Forward-Looking Sensors in the Next Generation Air Transportation System

The air transportation system of the future will need to support much greater traffic densities than are currently possible, while preserving or improving upon current levels of safety. Concepts are under development to support a Next Generation Air Transportation System (NextGen) that by some estimates will need to support up to three times current capacity by the year 2025. Weather and other atmospheric phenomena, such as wake vortices and volcanic ash, constitute major constraints on airspace system capacity and can present hazards to aircraft if encountered. To support safe operations in the NextGen environment advanced systems for collection and dissemination of aviation weather and environmental information will be required. The envisioned NextGen Network Enabled Weather (NNEW) infrastructure will be a critical component of the aviation weather support services, providing access to a common weather picture for all system users. By taking advantage of Network Enabled Operations (NEO) capabilities, a virtual 4-D Weather Data Cube with aviation weather information from many sources will be developed. One new source of weather observations may be airborne forward-looking sensors, such as the X-band weather radar. Future sensor systems that are the subject of current research include advanced multi-frequency and polarimetric radar, a variety of Lidar technologies, and infrared imaging spectrometers.

Schaffner, Philip R.↗

Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

small satellite↗

Towards a Generic and Adaptive System-On-Chip Controller for Space Exploration Instrumentation

This paper introduces one of the first efforts conducted at NASA’s Jet Propulsion Laboratory (JPL) to develop a generic System-on-Chip (SoC) platform to control science instruments that are proposed for future NASA missions. The SoC platform is named APEX-SoC, where APEX stands for Advanced Processor for space Exploration, and is based on a hybrid Xilinx Zynq that combines an FPGA and an ARM Cortex-A9 dual-core processor on a single chip. The Zynq implements a generic and customizable on-chip infrastructure that can be reused with a variety of instruments, and it has been coupled with a set of off-chip components that are necessary to deal with the different instruments. We have taken JPL’s Compositional InfraRed Imaging Spectrometer (CIRIS), which is proposed for NASA icy moons missions, as a use-case scenario to demonstrate that the entire data processing, control and interface of an instrument can be implemented on a single device using the on-chip infrastructure described in this paper. We show that the performance results achieved in this preliminary version of the instrumentation controller are sufficient to fulfill the science requirements demanded to the CIRIS instrument in future NASA missions, such as Europa.

embedded system↗

The Future of Oaks in the Santa Monica Mountains: A Case Study in Using Remote Sensing Data for Species Distributions Models

The Woolsey Fire began on November 8, 2018, and lasted for almost two weeks, during which it burned almost 100,000 acres of valuable landscape and habitat, including a vast area of woodland. The persistence of key woodland species provides aesthetic, monetary, and ecological value to the landscape through carbon sequestration, air temperature moderation, and erosion mitigation, among other ecosystem services. This study investigated the impact of the Woolsey Fire on native woodland species distributions and identified areas suitable for restoration within the Santa Monica Mountains National Recreation Area. The team partnered with the Resource Conservation District of the Santa Monica Mountains; National Park Service, Santa Monica Mountains National Recreation Area; California Department of Parks and Recreation, Los Angeles County Division; County of Los Angeles Fire Department, Prevention Services Bureau, Forestry Division; County of Los Angeles Department of Regional Planning; and the University of Montana. The Earth observations used include data from Landsat 8 Operational Land Imager, NASA ER-2 Jet Airborne Visible InfraRed Imaging Spectrometer, Shuttle Radar Topography Mission, and RapidEye. The team produced maps of burn severity from the Woolsey Fire, its impact on plant species distributions, and habitat suitability projections for 2050 and 2099 to assist partners in prioritizing areas for restoration. A plant community classification was successfully created using Multiple Endmember Spectral Mixture Analysis (MESMA). Overall accuracy was assessed at 90.54% by comparing the classification to validation pixels derived from ground truth information provided by our partners.

Roger Ly↗

Mapping Environmental Contaminants at Ray Mine, AZ

Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Projection Agency (EPA) through the Advanced Measurement Initiative (AMI).

AVIRIS↗

LiveCheckHSI: a Hardware/Software Co-verification Tool for Hyperspectral Imaging Systems with Embedded System-on-Chip Instrument Avionics

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This paper describes hardware/software co-verification tools for the Xilinx Zynq-based control and data handling system that have been developed at the Jet Propulsion Laboratory (JPL) for visible-infrared imaging spectrometers. The system acquires and compresses images in real-time, in addition to programming the spectrometer (frame rate, exposure time), focus step motor, and heaters and reporting telemetry.

Dolman, David↗

High Spectral Resolution Datasets of in Situ Aquatic Inherent and Apparent Optical Properties

Light emerging from natural water bodies and measured by remote sensing radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities to characterize aquatic ecosystems. Such upcoming missions include NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem PACE Mission; the NASA Surface Biology and Geology observable mission; and NASA Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) - Next Generation airborne missions. In anticipation of these missions, we present a dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP/AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland water, estuaries and oceans. Specific in situ measurements include particulate absorption, particulate attenuation, non-algal particulate or detritus absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, total backscatter, remote sensing reflectance, and irradiance reflectance. The dataset can be downloaded from PANGAEA: (https://www.pangaea.de/TBD ).

K A Casey↗

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗

Accelerating TEMPO Air Quality Science Through STAQS

Soon after the launch of Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission, NASA is supporting the Synergistic TEMPO Air Quality Science field study (STAQS) in summer 2023. This study’s main objective is to accelerate science with geostationary air quality observations from TEMPO to better understand its use in air pollution research and applications. Science objectives include, but are not limited to, TEMPO L2 product evaluation, the interpretation of the spatiotemporal evolution of TEMPO data during air quality events, assessment of anthropogenic emissions, contributions to chemical transport modeling, and environmental justice applications. These objectives can be accomplished through the integration of satellite data with systematically repeated high-resolution aircraft- and ground-based measurements in multiple urban environments. The primary urban cities considered include Los Angeles, New York City, and Chicago in June-August 2023. Measurements consist of airborne remote sensing observations of air quality constituents of nitrogen dioxide (NO2), formaldehyde (HCHO), ozone, and aerosols using the GeoCape Airborne Simulator and High-Spectral Resolution Lidar 2/Differential Absorption Lidar (HSRL2/DIAL) on the NASA JSC G-V aircraft, greenhouse gas observations from Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) and High Altitude Lidar Observatory (HALO) on the NASA LaRC G-III aircraft, and ground-based remote sensing and in situ observations of ozone, NO2, and HCHO from the Tropospheric Ozone Lidar Network (TOLNet), Pandora spectrometers, and ground-based monitoring networks. Key partnership studies providing in situ airborne observations include the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) field study on the NASA DC-8 in the same primary target areas as STAQS and Greater New York Oxidant, Tropospheric Halogens, and Aerosol Measurements and Modeling (GOTHAMM) field study on the NSF C-130 near New York City. This presentation will include a current status update of the STAQS mission and an overview of its measurement strategies and science objectives with the goal of promoting continued discussions for building and strengthening collaborations prior to the mission.

Laura Judd↗

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↗

Deciphering the Spectra of Flowers to Map Landscape-scale Blooming Dynamics

Like leaves, floral coloration is driven by inherent optical properties, which are determined by pigments, scattering structure, and thickness. However, establishing the relative contribution of these factors to canopy spectral signals is usually limited to in-situ observations. Modeling flowering dynamics (e.g., blooming duration, spatial distribution) at the landscape scale may reveal insights into ecological processes and phenological adaptations to environmental changes. Multitemporal visible to shortwave infrared (VSWIR) imaging spectroscopy observations are especially suited for such efforts. Reflectance in this spectral range is sensitive to major flower pigments, flowering phenology traces, and biophysical differences between flowers and other plant parts. We explored how flowers contribute to spectral signals using a time series of imagery from the Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) collected as part of the SBG High-Frequency Time Series (SHIFT) campaign as a case study. Airborne data were collected weekly during the spring of 2022 across two natural reserves in California. Field spectra were gathered from blooming plots at leaf, flower, and canopy levels at two time points during the campaign. The processed data was used to investigate flowering species' spectro-temporal variation and spatial distribution using Spectral Mixture Residual, Gaussian clustering techniques, and a proposed narrow-band flowering index. Linear spectral unmixing allowed the computation of the weighted contribution of four major high-variance endmembers (leaves, flowers, soil, dark) and low-variance residual signal that comprises subtle spectral features used to track biophysical processes. The reflectance residual was projected on a low principal component basis to characterize flowering clusters' variation and spatial distribution based on the Gaussian mixture model, providing an uncertainty metric to assess the results. Mapping flowering events from modeling spectro-temporal dynamics throughout the season, from pre-blooming to post-flowering stages, allowed us to identify gradient variations in spectral features within the VSWIR spectral range linked to flowering pigments. Time series of the Mixture Residual Blooming Index and the Red-Edge Normalized Difference Vegetation Index revealed specific flowering and greenness phenophases across the two main species (Coreopsis gigantea, Artemisia californica) in the flowering areas. Overall, our approach opens opportunities for future satellite monitoring of floral cycles at broader scales.

Yoseline Angel↗