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NASA NTRSDate not supplied

OCI Geolocation Evaluation and Refinement Using Landsat Control Points

The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission is NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer, Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. The geolocation processing is performed for OCI using spacecraft navigation data and an instrument geometry model. To evaluate the geolocation accuracy for OCI and develop refinements to the processing methods, control point matching using Landsat data has been implemented as a step in the operational processing of OCI data at the Science Data Segment. This processing provides between 200 and 300 high-quality matchups per day with good global and geometric distribution, allowing rapid evaluation of the OCI geolocation accuracy. The results provided an early indication of the overall quality of the geolocation processing and of specific aspects needing improvement. A standard set of granules was identified to support rapid implementation and testing of geolocation refinements, and this approach has been highly successful in improving the geolocation processing accuracy to meet the science requirements. The evaluation will continue throughout the mission to ensure the ongoing accuracy of geolocation. This paper describes the control point matching methodology, the approach to development of the geolocation processing refinements, and the recent results.

PACE↗

NASA NTRSDate not supplied

OCI Geolocation Evaluation and Refinement Using Landsat Control Points

PACE↗

NASA NTRS2002

Low Altitude AVIRIS Data for Mapping Landform Types on West Ship Island, Mississippi

A chain of barrier islands provides protection against hurricanes and severe storms along the south and southeastern shores of the United States. Barrier island landform types can be spectrally similar and as small as a few meters across, making highly detailed maps difficult to produce. To determine whether high-resolution airborne hyperspectral imagery could provide detailed maps of barrier island landform types, we used low-altitude hyperspectral and multispectral imagery to map surface environments of West Ship Island, Mississippi. We employed 3.4-meter AVIRIS hyperspectral imagery acquired in July 1999 and 0.5-meter ADAR multispectral data acquired in November 1997. The data were co-registered to digital ortho aerial imagery, and the AVIRIS data was scaled to ground reflectance using ATREM software. Unsupervised classification of AVIRIS and ADAR data proceeded using ISODATA clustering techniques. The resulting landform maps were field-checked and compared to aerial photography and digital elevation maps. Preliminary analyses indicated that the AVIRIS classification mapped more landform types, while the ADAR-based map enabled smaller patches to be identified. Used together, these maps provided a means to assess landform distributions of West Ship Island before and after Hurricane Gorges. Classification accuracy is being addressed through photo-interpretation and field surveys of sample areas selected with stratified random sampling.

Spruce, Joseph↗

NASA NTRS2003

Low Altitude AVIRIS Data for Mapping Landform Types on West Ship Island, Mississippi

A chain of barrier islands provides protection against hurricanes and severe storms along the southern and southeastern shores of the Unites States. Barrier island landform types can be spectrally similar and as small as a few meters across, making highly detailed maps difficult to produce. To determine whether high-resolution airborne hyperspectral imagery could provide detailed maps of barrier island landform types, we used low-altitude hyperspectral and multispectral imagery to map surface environments of West Ship Island, Mississippi. We employed 3.4 meter AVIRIS hyperspectral imagery acquired in July 1999 and 0.5 meter ADAR multispectral data acquired in November 1997. The data were co-registered to digital ortho aerial imagery, and the AVIRIS data was scaled to ground reflectance using ATREM software. Unsupervised classification of AVIRIS and ADAR data proceeded using ISODATA clustering techniques. The resulting landform maps were field-checked and compared to aerial photography and digital elevation maps. Preliminary analyses indicated that the AVIRIS classification mapped more landform types, while the ADAR-based map enabled smaller patches to be identified. Used together, these maps provided a means to assess landform distributions of West Ship Island before and after Hurricane Georges. Classification accuracy is being assessed through photo-interpretation and field surveys of sample areas selected with stratified random sampling.

Spruce, Joseph↗

DOE OSTI2021

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Desert Peak Geothermal Field.

15 GEOTHERMAL ENERGY↗

NASA NTRS2010

Exploiting the Free Landsat Archive for Operational Monitoring of Ecosystem Condition and Change Across the Chesapeake Bay Watershed

For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover, impervious cover, winter cover) are being produced using well-established decision tree and regression tree algorithms. The goal of this session is to present the data products that we have been developing to the Bay science community and to discuss potential avenues for improvements and usage of the products for decision support.

BrowndeColstoun, Eric↗

NASA NTRSDate not supplied

The Impact of All-Sky Hyperspectral Infrared Radiance Assimilation on the Simulation and Forecast of Hurricane Sally in GEOS

Hyperspectral infrared (IR) radiance observations have been one of the major data sources assimilated in the data assimilation system over the last 20 years. However, observations peaking in the lower and mid-troposphere are underutilized in clear-sky radiance data assimilation as the quality control procedure removes a significant portion of cloud-affected observations from the assimilation. To include these cloud-affected observations, one approach is to assimilate them directly under all-sky conditions. The framework for all-sky assimilation of hyperspectral IR radiance observations has been developed in GEOS. The preliminary evaluation of simulated cloud-affected IR observations has been conducted, along with the corresponding sensitivities with respect to all hydrometeors. The symmetric cloud effect has been used as a cloud proxy in the observation error modeling, providing a balanced representation that mitigates the discrepancies between observations and model simulations for IR all-sky assimilation. The observation errors vary for different cloud conditions and have been modeled as cloud amount dependent and inter-channel correlated. Preliminary evaluation of model simulations for IR all-sky assimilation indicates that the simulated brightness temperature tends to have broader structures and lacks small-scale details. Excessive clouds generated by the model are also observed. To address this issue, Hurricane Sally (2020), which formed near the Bahamas, is used as a case study. Several cloud overlap schemes and cloud lookup tables (LUTs), along with other important aspects of all-sky IR radiance assimilation, will be evaluated and tested, aiming to improve the impact on Hurricane Sally's simulation and forecast.

Wei Gu↗

NASA NTRS1999

The Thermal Emission Imaging System (THEMIS) Instrument for the Mars 2001 Orbiter

The primary objective of the Thermal Emission Imaging System (THEMIS) on the Mars Surveyor '01 Orbiter is to study the composition of the Martian surface at high spatial resolution. THEMIS will map the surface mineralogy using multi-spectral thermal infrared images in 8 spectral bands from 6.5 to 14.5 microns. In addition, a band centered at 15 microns will be used to map atmospheric temperatures and provide an important aid in separating the surface and atmospheric components. The entire planet will be mapped at 100 m resolution within the available data volume using a multi-spectral, rather than hyperspectral, imaging approach. THEMIS will also acquire 20 m resolution visible images in up to 5 spectral bands using a replica of the Mars 98 Orbiter (MARCI) and Lander (MARDI) cameras. Over 15,000 panchromatic (3,000 5-color), 20 x 20 km images will be acquired for morphology studies and landing site selection. The thermal-infrared spectral region contains the fundamental vibrational absorption bands of most minerals which provide diagnostic information on mineral composition. All geologic materials, including carbonates, hydrothermal silica, sulfates, phosphates, hydroxides, silicates, and oxides have strong absorptions in the 6.5-14.5 micron region. Silica and carbonates, which are key diagnostic minerals in thermal spring deposits, are readily identified using thermal-IR spectra. In addition, the ability to identify all minerals allows the presence of aqueous minerals to be interpreted in the proper geologic context. An extensive suite of studies over the past 35 years has demonstrated the utility of vibrational spectroscopy for the quantitative determination of mineralogy and petrology. The fundamental vibrations within different anion groups, such as C03, S04, P04, and SiO4, produce unique, well separated spectral bands that allow carbonates, sulfates, phosphates, silicates, oxides, and hydroxides to be readily identified. Additional stretching and bending modes involving major cations, such as Mg, Fe, Ca, and Na, allow Further mineral identification, such as the excellent discriminability of minerals within the silicate and carbonate groups.

Christensen, P. R.↗

NASA NTRS2016

Scientific and Technical Assistance for the Deployment of a Flexible Airborne Spectrometer System During C-MAPExp and COMEX: COMEX Version - 1.9T

The COMEX (CO2 and MEthane eXperiment) campaign supports the mission definition of CarbonSat and HyspIRI (Hyperspectral Infrared Imager) by providing representative airborne remote sensing data ‐ MAMAP (Methane Airborne MAPper) for CarbonSat; the Airborne Visual InfraRed Imaging Spectrometer (Classic & Next Generation) AVIRIS‐C/AVIRIS‐NG for HyspIRI ‐ as well as ground-based and airborne in‐situ data. The objectives of the COMEX campaign activities are (see Campaign Implementation Plan (RD‐4)): 1. Investigate spatial/spectral resolution trade‐offs for CH4 anomaly detection and flux inversion by comparison of MAMAP‐derived emission estimates with AVIRIS/AVIRIS‐NG derived data. 2. Evaluate sun‐glint observation geometry on CH4 retrievals for marine sources. 3. Characterize the effect of Surface Spectral Reflectance (SSR) heterogeneity on trace gas retrievals of CO2 and CH4 for medium and low‐resolution spectrometry. 4. Identify benefits from joint SWIR/TIR (ShortWave InfraRed/Thermal InfraRed ) data for trace gas detection and retrieval by comparison of MAMAP and AVIRIS/AVIRIS‐NG NIR/SWIR data with MAKO (Aerospace Corp.)TIR data. The ability to derive emission source strength for a range of strong emitting targets by remote sensing will be evaluated from combined AVIRIS‐NG and MAMAP data, adding significant value to the HyspIRI campaign AVIRIS‐NG dataset. The data will be used to quantify anomalies in atmospheric CO2 and CH4 from strong local greenhouse gas sources e.g. localized industrial complexes, landfills, etc. and to derive CO2 and CH4 emissions estimates from atmospheric gradient measurements. The original campaign concept was developed by University of Bremen and BRI. The COMEX campaign is funded bilaterally by NASA and ESA (European Space Agency). Whereas NASA funds the US part of the project via a contract with Dr. Ira Leifer, BRI (Bubbleology Research International), the contribution of MAMAP to the COMEX campaign is funded by ESA within the COMEX‐E project and NASA with respect to a 50 percent contribution to the flight-related costs of flying MAMAP on a US aircraft. The Data Acquisition Report (RD‐9) describes the instrumentation used, the measurements made by the team during the COMEX campaign in May/June 2014 and August/September 2014 in California, and an initial assessment of the data quality.

Point Sources↗

NASA NTRSDate not supplied

PRIMA: The PRobe Far-Infrared Mission for Astrophysics

PRIMA is a far-infrared observatory concept being developed to address timely and fundamental questions about the growths of galaxies and solar systems and their constituents. It will observe the build-up of heavy elements, dust, stars, and black holes in galaxies and their interrelationships, and trace the masses and water contents of protoplanetary disks to probe the growths of solar systems. The majority of observing time will be devoted to Guest Observer programs to enable the astrophysics community to identify and plan the most critical observations, with focused PI programs to address key science with rapid releases of data to inform community planning. PRIMA will have spectral, hyperspectral imaging, and polarimetric capabilities, enabled now for the first time by extraordinary progress in kinetic inductance detector (KID) array technology over the last two decades. The 2.0-meter telescope will be cooled to < 5 K to take maximum advantage of the KID sensitivities. For observations of atomic fine-structure lines, molecular lines, and solid-state emission and absorption bands, R = 200 spectral coverage will range from approximately 25 µm to 200 µm, with a high-resolution mode across the entire band that will have a spectral resolving power of a few thousand at 100 µm. R ~ 10 moderate-resolution (hyperspectral) imaging will range from 25 to 80 µm for rest-frame, mid- and far-infrared spectral energy distribution measurements to probe dust grain composition and disambiguate star formation and active galactic nuclei in galaxies. Polarimetric observations of large areas of Galactic molecular clouds and the Magellanic Clouds from 80 to ~200 µm will bridge between the large-scale polarimetry of the interstellar medium from cosmic microwave background observatories and protostellar disk-scale interferometric observations to probe magnetic fields at the critical scales at which clouds collapse to form stars. An overview of PRIMA’s basic design and capabilities will be presented. Other posters in this session describe PRIMA science, technology, and instrumentation in greater depth.

Jason Glenn↗

DOE OSTI2023

Hyperspectral Infrared Observations of Arctic Snow, Sea Ice, and Non-Frozen Ocean from the RV Polarstern during the MOSAiC Expedition October 2019 to September 2020

This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A Neural Differential Equation Formulation for Modeling Atmospheric Effects in Hyperspectral Images

Atmospheric correction is the process for removing atmospheric effects from spectral data; a necessary step for recovering salient spectral properties. The complex interactions between the atmosphere and light are dominated by absorbance and scattering physics. Existing methods for modeling atmospheric interactions typically rely on deep knowledge of relevant environmental conditions and high-fidelity numerical simulations of the governing physics in order to obtain accurate estimates of these effects. Additionally, existing approaches often require a subject matter expert for pre/post-processing of the data. Model-based approaches for removing atmospheric effects struggle in situations where such domain expertise is not available, and require significant human effort and computational power even when that expertise is available. In contrast, we propose a data-driven approach the uses Neural Differential Equations (NDEs) to accurately learn the interactions between electromagnetic radiation and the atmospheric without access to location specific environmental information. Once trained, the NDE can be applied bi-directionally; to apply or remove atmospheric effects. We demonstrate the effectiveness and utility of these techniques on an example multi-spectral scene.

Koch, James V.↗

NASA NTRS2003

Derivative Analysis of AVIRIS Data for Crop Stress Detection

Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery of a cornfield in Nebraska was used to determine whether derivative analysis methods provided enhanced plant stress detection compared with narrow-band ratios. The field was divided into 20 plots representing 4 replicates each of 5 nitrogen (N) fertilization treatments that ranged from 0 to 200 kg N/ha in 50 kg/ha increments. The imagery yielded a 3 m ground pixel size for 224 spectral bands. Derivative analysis provided no advantage in stress detection compared with the performance of narrow-band indices derived from the literature. This result was attributed to a high leaf area index at the time of overflight (LAI approx. equal to 5 to 6t) and the high signal-to-noise character of the narrow AVIRIS bands.

Estep, Lee↗

NASA NTRS2011

High Speed, Multi-Channel, Thermal Instrument Development in Support of HyspIRI-TIR

The Jet Propulsion Laboratory is currently developing an end-to-end instrument which will provide a proof of concept prototype vehicle for a high data rate, multi-channel, thermal instrument in support of the Hyperspectral Infrared Imager (HyspIRI)-Thermal Infrared (TIR) space mission. HyspIRI mission was recommended by the National Research Council Decadal Survey (DS). The HyspIRI mission includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. The prototype testbed instrument addressed in this effort will only support the TIR. Data from the HyspIRI mission will be used to address key science questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission Directorate. Current designs for the HyspIRI-TIR space borne imager utilize eight spectral bands delineated with filters. The system will have 60m ground resolution, 200mK NEDT, 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. The prototype instrument will use mercury cadmium telluride (MCT) technology at the focal plane array in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence high data rates needed for the 5 day repeat. The current HyspIRI requirements dictate a ground knowledge measurement of 30m, so the prototype instrument will tackle this problem with a newly developed interferometeric metrology system. This will provide an absolute measurement of the scanning mirror to an order of magnitude better than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing postprocessing (e.g. geo-rectification computations).

Multi-spectral↗

NASA NTRS2012

Hyperspectral Image Turbulence Measurements of the Atmosphere

A Forward Looking Interferometer (FLI) sensor has the potential to be used as a means of detecting aviation hazards in flight. One of these hazards is mountain wave turbulence. The results from a data acquisition activity at the University of Colorado s Mountain Research Station will be presented here. Hyperspectral datacubes from a Telops Hyper-Cam are being studied to determine if evidence of a turbulent event can be identified in the data. These data are then being compared with D&P TurboFT data, which are collected at a much higher time resolution and broader spectrum.

Lane, Sarah E.↗

NASA NTRS1998

Neural Network for Analysis of Hyperspectral Imagery

Each material has unique spectral distribution that can be viewed as its fingerprint. Advanced hyper and ultra spectral sensors will produce large amount of data. Therefore, advanced capabilities are required that can effectively deal with large data cubes, possibly in real time.

hyperspectral imagery neural network↗

NASA NTRS2005

Evaluation of Vertically Resolved Water Winds from AIRS using Hurricane Katrina

The knowledge of wind velocity as a function of altitude is key to weather forecast improvements. The ability of hyperspectral sounders in principle to measure vertically resolved water winds, which has long been recognized, has been tested with Atmospheric Infrared Sounder (AIRS) data. AIRS retrievals of total column water above 300 mb have been correlated with the radiosonde upper-tropospheric wind velocity and moisture data. The excellent correlation is illustrated with results obtained from hurricane Katrina and from the western United States. AIRS is a hyperspectral infrared sounder in low Earth orbit. It was launched in May 2002. We illustrate the use of AIRS data for the measurement of upper tropospheric water by using the 2387/cm CO2 R-branch channel and the 1551/cm water vapor channel. The 2387/cm channel measures the temperature at 300 mb totally independent of water vapor. The weighting function of the 1551/cm channel peaks at 300 mb only under moist conditions; the peak shifts downward (higher temperature) for less water and upward (lower temperature) for more water. The difference between the brightness temperatures bt2387 and bt1551 cancels the local several degree weather related variability of the temperature and measures the component due to the water vapor at 300 mb.

Atmospheric Infrared Sounder (AIRS)↗

NASA NTRS2006

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Ross, Kenton W.↗