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Results for “spectral band selection”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Spectral band selection for classification of soil organic matter content

This paper describes the spectral-band-selection (SBS) algorithm of Chen and Landgrebe (1987, 1988, and 1989) and uses the algorithm to classify the organic matter content in the earth's surface soil. The effectiveness of the algorithm was evaluated comparing the results of classification of the soil organic matter using SBS bands with those obtained using Landsat MSS bands and TM bands, showing that the algorithm was successful in finding important spectral bands for classification of organic matter content. Using the calculated bands, the probabilities of correct classification for climate-stratified data were found to range from 0.910 to 0.980.

Henderson, Tracey L.↗
NASA NTRS1982

Imaging spectrometer technologies for advanced Earth remote sensing

A major requirement of multispectral imaging systems for advanced Earth remote sensing is the provision for greater spectral resolution and more versatile spectral band selection. The imaging spectrometer instrument concept provides this versatility by the combination of pushbroom imaging and spectrally dispersing optics using area array detectors in the focal plane. The shuttle imaging spectrometer concept achieves 10- and 20-meter ground instantaneous fields of view with 20-nanometer spectral resolution from Earth Orbit. Onboard processing allows the selection of spectral bands during flight; this, in turn, permits the sensor parameters to be tailored to the experiment objectives. Advances in optical design, infrared detector arrays, and focal plane cooling indicate the feasibility of the instrument concept and support the practicability of a validation flight experiment for the shuttle in the late 1980s.

Wellman, J. B.↗
NASA NTRS1982

Imaging spectrometer technologies for advanced earth remote sensing

A major requirement of multispectral imaging systems for advanced earth remote sensing is the provision for greater spectral resolution and more versatile spectral band selection. The imaging spectrometer instrument concept provides this versatility by the combination of pushbroom imaging and spectrally dispersing optics using area array detectors in the focal plane. The shuttle imaging spectrometer concept achieves 10- and 20-meter ground instantaneous fields of view with 20-nanometer spectral resolution from earth orbit. Onboard processing allows the selection of spectral bands during flight; this, in turn, permits the sensor parameters to be tailored to the experiment objectives. Advances in optical design, infrared detector arrays, and focal plane cooling indicate the feasibility of the instrument concept and support the practicability of a validation flight experiment for the shuttle in the late 1980s. Previously announced in STAR as N83-28542

Wellman, J. B.↗
NASA NTRS1980

Snow mapping from space platforms

The paper considers problems of optimum resolution, periodicity, and wavelength bands used for snow mapping. Analog and digital methods were used for application of satellite data; techniques were developed for producing steamflow forecasts, hydroelectric power generation regulation data, irrigation potentials, and information on the availability of drinking water supplies. Future systems will utilize improved spectral band selection, new spectral regions, higher repetition rates, and more rapid access to satellite data.

Itten, K. I.↗
NASA NTRS2006

Multiple Waveband Temperature Sensor (MWTS)

This slide presentation reviews the development of Multiple Waveband Temperature Sensor (MWTS). The MWTS project will result in a highly stable, monolithically integrated, high resolution infrared detector array sensor that records registered thermal imagery in four infrared wavebands to infer dynamic temperature profiles on a laser-irradiated ground target. An accurate surface temperature measurement of a target in extreme environments in a non-intrusive manner is required. The development challenge is to: determine optimum wavebands (suitable for target temperatures, nature of the targets and environments) to measure accurate target surface temperature independent of the emissivity, integrate simultaneously readable multiband Quantum Well Infrared Photodetectors (QWIPs) in a single monolithic focal plane array (FPA) sensor and to integrate the hardware/software and system calibration for remote temperature measurements. The charge was therefore to develop and demonstrate a multiband infrared imaging camera with the detectors simultaneously sensitive to multiple distinct color bands for front surface temperature measurements Wavelength ( m) measurements. Amongst the requirements are: that the measurement system will not affect target dynamics or response to the laser irradiation and that the simplest criterion for spectral band selection is to choose those practically feasible spectral bands that create the most contrast between the objects or scenes of interest in the expected environmental conditions. There is in the presentation a review of the modeling and simulation of multi-wave infrared temperature measurement and also a review of the detector development and QWIP capacities.

infrared photodector↗
NASA NTRS1985

Multiband Selector for Linear Photodetector Array

Line image observed simultaneously in two or more spectral bands. Incoming light focused through beam splitter onto two linear arrays of photodetectors to form line images. Array of band-pass filters above each detector array positioned to select spectral band of line image. These capabilities are valuable in such multispectral-imaging applications as spaceborne and airborne visible and infrared observation of Earth for geology, oil and mineral exploration, biomass distribution, forestry, agriculture, and urban and rural development.

Richard, H. L.↗
NASA NTRSDate not supplied

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↗
NASA NTRS1980

Experiments in infrared multispectral mapping of earth resources

Two evolutionary infrared remote sensing experiments provide the basis for the development of an operational mapping capability for geology exploration. A 10-band radiometer scheduled for an early Shuttle flight has completed an aircraft flight program which demonstrated the utility of a number of narrow spectral channels. A multispectral mapper utilizing an infrared area array detector to acquire simultaneous images in multiple wavelengths is being assembled. A design concept for an operational sensor which employs area arrays for registered multispectral image data acquisition is under study. The sensor would utilize onboard spectral band selection, radiometric correction, and data compression to satisfy the demanding requirements of the user community.

Wellman, J. B.↗
NASA NTRS1980

LANDSAT imagery of the Venetian Lagoon: A multitemporal analysis

The use of LANDSAT multispectral scanner images from 1975 to 1979 to determine pollution dispersion in the central basin of the lagoon under varying tidal conditions is described. Images taken during the late spring and representing both short and long range tidal dynamics were processed for partial haze removal and removal of residual striping. Selected spectral bands were correlated to different types of turbid water. The multitemporal data was calibrated, classified considering sea truth data, and evaluated. The classification differentiated tide diffusion, algae belts, and industrial, agricultural, and urban turbidity distributions. Pollution concentration is derived during the short time interval between inflow and outflow and from the distance between the two lagoon inlets and the industrial zones. Increasing pollution of the lagoon is indicated.

Alberotanza, L.↗
NASA NTRS1984

A Concept for the Processing and Display of Thematic Mapper Data

Multispectral information can best be accessed and evaluated through digital interactive image processing techniques. The potential user community, however, has not reached the level where image processing is being used routinely as a standard tool. Therefore, for the time being, special effort must be put into development of strategies that will guarantee optimal utilization of the spectral information contained in remote sensing data acquired under the varying conditions affecting each scene. The Thematic Mapper system provides spectral information in seven carefully selected spectral bands, covering the visible, near IR, short-wave IR and thermal IR region of the electromagntic spectrum. The challenge is to devise the best approach for presenting this complex spectral information in a pictorial format which can be understood and accepted as a standard by the growing user community.

Haydn, R.↗
NASA NTRS1985

A Concept for the Processing and Display of Thematic Mapper Data

The thematic mapper system provides spectral information in seven carefully selected spectral bands. The challenge is to devise the best approach for presenting this complex spectral information in a pictorial format which can be understood and accepted as a standard by the growing user community. For photointerpretation purposes, the overall approach in the processing of multispectral, and especially of Thematic Mapper data is based on the Independent definition and optimization of individual panchromatic and spectral (interpretive) components and the combined display of these individual interpretive components in a perceivable manner. Processing of the Thematic Mapper data within the framework of interpretive components requires the application of special intensity, hue, saturation (IHS) and synthetic stereo (SST) display techniques. The results to date using these techniques demonstrate improved visual separability of spectral surface categories relative to standard multispectral color composites as well as a greater potential for conducting meaningful spectral-diagnostic analysis.

Haydn, R.↗
NASA NTRS2003

Validation of On-board Cloud Cover Assessment Using EO-1

The purpose of this NASA Earth Science Technology Office funded effort was to flight validate an on-board cloud detection algorithm and to determine the performance that can be achieved with a Mongoose V flight computer. This validation was performed on the EO-1 satellite, which is operational, by uploading new flight code to perform the cloud detection. The algorithm was developed by MIT/Lincoln Lab and is based on the use of the Hyperion hyperspectral instrument using selected spectral bands from 0.4 to 2.5 microns. The Technology Readiness Level (TRL) of this technology at the beginning of the task was level 5 and was TRL 6 upon completion. In the final validation, an 8 second (0.75 Gbytes) Hyperion image was processed on-board and assessed for percentage cloud cover within 30 minutes. It was expected to take many hours and perhaps a day considering that the Mongoose V is only a 6-8 MIP machine in performance. To accomplish this test, the image taken had to have level 0 and level 1 processing performed on-board before the cloud algorithm was applied. For almost all of the ground test cases and all of the flight cases, the cloud assessment was within 5% of the correct value and in most cases within 1-2%.

Mandl, Dan↗
NASA NTRS2015

Measured Polarized Spectral Responsivity of JPSS J1 VIIRS Using the NIST T-SIRCUS

Recent pre-launch measurements performed on the Joint Polar Satellite System (JPSS) J1 Visible Infrared Imaging Radiometer Suite (VIIRS) using the National Institute of Standards and Technology (NIST) Traveling Spectral Irradiance and Radiance Responsivity Calibrations Using Uniform Sources (T-SIRCUS) monochromatic source have provided wavelength dependent polarization sensitivity for select spectral bands and viewing conditions. Measurements were made at a number of input linear polarization states (twelve in total) and initially at thirteen wavelengths across the bandpass (later expanded to seventeen for some cases). Using the source radiance information collected by an external monitor, a spectral responsivity function was constructed for each input linear polarization state. Additionally, an unpolarized spectral responsivity function was derived from these polarized measurements. An investigation of how the centroid, bandwidth, and detector responsivity vary with polarization state was weighted by two model input spectra to simulate both ground measurements as well as expected on-orbit conditions. These measurements will enhance our understanding of VIIRS polarization sensitivity, improve the design for future flight models, and provide valuable data to enhance product quality in the post-launch phase.

JPSS↗
NASA NTRS2022

Using Machine Learning for Timely Estimates of Ocean Color Information From Hyperspectral Satellite Measurements in the Presence of Clouds, Aerosols, and Sunglint

Retrievals of ocean color from space are important for better understanding of the ocean ecosystem but can be limited under conditions such as clouds, aerosols, and sunglint. Many ocean color algorithms use a few selected spectral bands to perform an atmospheric correction and then derive the upwelling radiance from the ocean. The limitations in the atmospheric correction under certain conditions lead to many gaps in daily spatial coverage of ocean color retrievals. To address these limitations, we introduce a new approach that uses machine learning to estimate ocean color from top of atmosphere radiances or reflectance measurements. In this approach, a principal component analysis is used to decompose the hyperspectral measurements into spectral features that describe the scattering and absorption of the atmosphere and the underlying surface. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from the MODIS atmospheric correction algorithm. This machine learning approach is independent of a priori information and does not rely on any radiative transfer modeling. We apply the approach to two hyperspectral UV/VIS instruments, the ozone monitoring instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI), using measurements from 320–500 nm to show that it can be used to reproduce ocean color properties in less-than-ideal conditions. This machine learning approach complements the current atmospheric correction ocean color retrievals by filling in the gaps resulting from cloud, aerosol, and sunglint contamination. This method can be applied to the future hyperspectral Ocean Color Instrument (OCI), which will be onboard NASA’s Plankton, Aerosol Cloud, ocean Ecosystem (PACE) ocean color satellite set to launch in 2024.

Ocean color↗
NASA NTRS1981

Multispectral mapper - Imaging spectroscopy as applied to the mapping of earth resources

An instrument concept that uses solid-state array imaging has been developed for a future land observing system. The design concept is responsive to a variety of use needs and provides improved capabilities over the planned Landsat Thematic Mapper. A comparison of the differing approaches to the instrument design was made, resulting in the selection of a concept which uses a spectrograph coupled to a line-array imager to provide simultaneous spatial and spectral resolution. The design provides an inherent solution to the problem of achieving precise registration among the spectral bands. Data processing on the focal plane is used to select the spectral bands and their band widths. Onboard capabilities include radiometric correction, selection of instantaneous field-of-view and swath width, and data compression.

Wellman, J. B.↗
NASA NTRS1995

Programmable hyperspectral image mapper with on-array processing

A hyperspectral imager includes a focal plane having an array of spaced image recording pixels receiving light from a scene moving relative to the focal plane in a longitudinal direction, the recording pixels being transportable at a controllable rate in the focal plane in the longitudinal direction, an electronic shutter for adjusting an exposure time of the focal plane, whereby recording pixels in an active area of the focal plane are removed therefrom and stored upon expiration of the exposure time, an electronic spectral filter for selecting a spectral band of light received by the focal plane from the scene during each exposure time and an electronic controller connected to the focal plane, to the electronic shutter and to the electronic spectral filter for controlling (1) the controllable rate at which the recording is transported in the longitudinal direction, (2) the exposure time, and (3) the spectral band so as to record a selected portion of the scene through M spectral bands with a respective exposure time t(sub q) for each respective spectral band q.

Cutts, James A.↗
DOE OSTI2022

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗
NASA NTRS1978

Selection of a seventh spectral band for the LANDSAT-D thematic mapper

The author has identified the following significant results. Each of the candidate bands were examined in terms of the feasibility of gathering high quality imagery from space while taking into account solar illumination, atmospheric attenuation, and the signal/noise ratio achievable within the TM sensor constraints. For the 2.2 micron region and the thermal IR region, inband signal values were calculated from representative spectral reflectance/emittance curves and a linear discriminant analysis was employed to predict classification accuracies. Based upon the substantial improvement (from 78 t0 92%) in discriminating zones of hydrothermally altered rocks from unaltered zones, over a broad range of observation conditions, a 2.08-2.35 micron spectral band having a ground resolution of 30 meters was recommended.

Holmes, Q. A.↗