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Results for “multispectral imaging”

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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Performance evaluation of the two-inch return-beam vidicon three-camera subsystem.

A very-high resolution multispectral television camera system is being developed for NASA for use on the Earth Resources Technology Satellite (ERTS) program. There are three cameras in the system, each viewing the same area but operating in the blue-green, red and near-infrared spectral bands. In the laboratory the cameras' limiting resolution is 4500 TV lines over the 25 x 25-mm image format of the Return Beam Vidicon (RBV). Analysis of typical ERTS scenes shows that actual contrast ratios will be much lower than those of laboratory test targets. A model was developed to predict the resolving power performance of the RBV camera under realistic conditions. The methods used are applicable to all types of imaging systems. To verify the model, tests were conducted using the RBV camera, a laser-beam image reproducer and a series of AF tribar test patterns of known values of contrast. As a more graphic demonstration, simulated multispectral images were generated using color-IR photographs from Apollo 9.

Miller, B. P.↗
NASA NTRS1973

High resolution multispectral camera system for ERTS A & B

A very high resolution multispectral television camera system has been developed for NASA for use on the Earth Resources Technology Satellite (ERTS) program. There are three cameras in the system, each viewing the same area but operating in the blue-green, red, and near-infrared spectral bands. In the laboratory the cameras' limiting resolution is 4500 TV lines over the 25 x 25-mm image format of the Return Beam Vidicon (RBV). Analysis of typical ERTS scenes shows that actual contrast ratios will be much lower than those of laboratory test targets. A model was developed to predict the resolving power performance of the RBV camera under realistic conditions. To verify the model, tests were conducted using the RBV camera, a laser-beam image reproducer and a series of AF tribar test patterns of known values of contrast. As a more graphic demonstration, simulated multispectral images were generated using color-IR photographs from Apollo 9. The measured signal-to-noise, resolution, and spectral characteristics of the ERTS Flight A and Flight B three-camera systems are presented in conclusion.

Miller, B. P.↗
NASA NTRS1981

Utilization of LANDSAT images in cartography

The use of multispectral imagery obtained from LANDSAT for mapping purposes is discussed with emphasis on geometric rectification, image resolution, and systematic topographic mapping. A method is given for constructing 1:250,000 scale maps. The limitations for satellite cartography are examined.

Dejesusparada, N.↗
NASA NTRS2012

Obtaining Accurate Change Detection Results from High-Resolution Satellite Sensors

Multi-date acquisitions of high-resolution imaging satellites (e.g. GeoEye and WorldView), can display local changes of current economic interest. However, their large data volume precludes effective manual analysis, requiring image co-registration followed by image-to-image change detection, preferably with minimal analyst attention. We have recently developed an automatic change detection procedure that minimizes false-positives. The processing steps include: (a) Conversion of both the pre- and post- images to reflectance values (this step is of critical importance when different sensors are involved); reflectance values can be either top-of-atmosphere units or have full aerosol optical depth calibration applied using bi-directional reflectance knowledge. (b) Panchromatic band image-to-image co-registration, using an orthorectified base reference image (e.g. Digital Orthophoto Quadrangle) and a digital elevation model; this step can be improved if a stereo-pair of images have been acquired on one of the image dates. (c) Pan-sharpening of the multispectral data to assure recognition of change objects at the highest resolution. (d) Characterization of multispectral data in the post-image ( i.e. the background) using unsupervised cluster analysis. (e) Band ratio selection in the post-image to separate surface materials of interest from the background. (f) Preparing a pre-to-post change image. (g) Identifying locations where change has occurred involving materials of interest.

multispectral↗
DOE OSTI2026

Comparison of CNN-Based Image Classification Approaches for Implementation of Low-Cost Multispectral Arcing Detection

Camera-based sensing has benefited in recent years from developments in machine learning data processing methods, as well as improved data collection options such as Unmanned Aerial Vehicles (UAV) mounted sensors. However, cost considerations, both for the initial purchase of sensors as well as updates, maintenance, or potential replacement if damaged, can limit adoption of more expensive sensing options for some applications. To evaluate more affordable options with less expensive, more available, and more easily replaceable hardware, we examine the use of machine learning-based image classification with custom datasets, utilizing deep learning based-image classification and the use of ensemble models for sensor fusion. Utilizing the same models for each camera to reduce technical overhead, we showed that for a very representative training dataset, camera-based detection can be successful for detection of electrical arcing. We also use multiple validation datasets, based on conditions expected to be of varying difficulty, to evaluate custom data. These results show that ensemble models of different data sources can mitigate risks from gaps in training data, though the system will be less redundant for those cases unless other precautions are taken. We found that with good quality custom datasets, data fusion models can be utilized without specialization in design to the specific cameras utilized, allowing for less specialized, more accessible equipment to be utilized as multispectral camera components. This approach can provide an alternative to expensive sensing equipment for applications in which lower-cost or more easily replaceable sensing equipment is desirable.

convolutional neural networks↗
NASA NTRS1983

Shuttle Imaging Radar-A (SIR-A) data as a complement to Landsat Multispectral Scanner (MSS) data

Principal components analysis and supervised classifications were performed on two dates of Landsat multispectral scanner (MSS) data registered to one date of Shuttle Imaging Radar-A (SIR-A) data in a wheat-growing area of New South Wales, Australia. The purpose was to evaluate SIR-A data as a complement to Landsat MSS data in an agricultural environment. The SIR-A data was filtered using a 7 x 7 pixel moving window median filter. Principal components analysis indicated the SIR-A data were discriminating between trees and agricultural fields. Supervised classifications using wheat, pasture, trees, and idle classes resulted in increased accuracies for wheat and pasture and slightly decreased accuracies for trees and idle for the Landsat MSS/SIR-A registered data sets over the Landsat MSS alone. Overall classification accuracies were unchanged for one date and substantially increased for the other when the SIR-A data were added to the Landsat MSS data.

Henninger, D. L.↗
NASA NTRS1983

Analysis of the quality of image data acquired by the LANDSAT-4 thematic mapper and multispectral scanners

The three types of LANDSAT 4 film products generally accessible to the user community were analyzed and attempts were made to acquire a data set consisting of a variety of TM and MSS image products for the Sacramento and San Francisco Bay Area test sites. On request, the EDC developed an interim TM analytical film by using a leaser beam recorder to produce black and white masters from which natural and false color composites were created.

Colwell, R. N.↗
NASA NTRS1972

A study of temporal estaurine flow dynamics

Multispectral photography,infrared imagery, image enhancement, and oceanographic, radiometric, and meteorological data were used in the study of temporal estuarine flow dynamics, nearshore circulation, and the resulting dispersal of suspended and dissolved substances introduced from the continent. Repetitive multispectral photography, IR imagery, total radiance and irradiance, water surface temperatures, salinity, total suspended solids, visibility, current velocity, winds, dye implants, and high contrast image enhancement were used to observe and describe water mass boundaries in the nearshore zone and to attempt to establish on what repetitive scale these coastal features should be observed to better understand their behavior. Water mass variability patterns, seen naturally and with the use of dyes, along the North Carolina coast and in the Chesapeake Bay are being studied as synoptic data on the basic dynamics of circulation, flushing, and mixing in coastal waters.

Mairs, R. L.↗
NASA NTRS1974

Image data processing of earth resources management

The Earth Resources Technology Satellite (ERTS-1) was launched on July 23, 1972. Since that date, the vehicle has been acquiring and transmitting to earth a vast amount of information relating to the earth's resources. Scientific investigators throughout the world have been analyzing photographic products produced from this data with significant results. Recently, there has been a major shift of emphasis from the visual analysis of photo products to the use of sophisticated digital information extraction techniques. Specialized equipment, such as the GE IMAGE 100 System, has been developed that operates directly from Computer Compatible Tapes, (CCT’s), which contain preprocessed digital data acquired from the ERTS spacecraft. Analysis of CCT data avoids the losses in image resolution and quality which are inherent to all photo processing techniques, thereby greatly increasing the utility of ERTS data. Future ground processing systems will turn out fully corrected (radiometric and geometric) digital tapes which will further increase the utility of ERTS data. This paper is presented in two parts: the first part deals with the subject of present and future generations of image processing and information extraction systems under development at the General Electric Company; the second part describes in more detail the design and operation of GE1s interactive multispectral information extraction systems, IMAGE 100, and discusses results of analyses of ERTS data over a number of U.S. sites.

A W DeSio↗
NASA NTRS1995

CNR LARA project, Italy: Airborne laboratory for environmental research

The increasing interest for the environmental problems and the study of the impact on the environment due to antropic activity produced an enhancement of remote sensing applications. The Italian National Research Council (CNR) established a new laboratory for airborne hyperspectral imaging, the LARA Project (Laboratorio Aero per Ricerche Ambientali - Airborne Laboratory for Environmental Research), equipping its airborne laboratory, a CASA-212, mainly with the Daedalus AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) instrument. MIVIS's channels, spectral bandwidths, and locations are chosen to meet the needs of scientific research for advanced applications of remote sensing data. MIVIS can make significant contributions to solving problems in many diverse areas such as geologic exploration, land use studies, mineralogy, agricultural crop studies, energy loss analysis, pollution assessment, volcanology, forest fire management and others. The broad spectral range and the many discrete narrow channels of MIVIS provide a fine quantization of spectral information that permits accurate definition of absorption features from a variety of materials, allowing the extraction of chemical and physical information of our environment. The availability of such a hyperspectral imager, that will operate mainly in the Mediterranean area, at the present represents a unique opportunity for those who are involved in environmental studies and land-management to collect systematically large-scale and high spectral-spatial resolution data of this part of the world. Nevertheless, MIVIS deployments will touch other parts of the world, where a major interest from the international scientific community is present.

Bianchi, R.↗
NASA NTRS1981

Dynamic study of the upper Sao Francisco River and the Tres Marias reservoir using MSS/LANDSAT images

The use of LANDSAT multispectral ban scanner imagery to verify the relationship between the behavior of the Tres Marias reservoir and the dynamics of the Sao Francisco River supply basin is described. The dispersion of suspended sediments and their concentration in the surface layers of the water are considered. A five year survey of the region during both dry and rainy seasons was performed. The drainage network was analyzed based on the patterns of dessication, water rises and soil use in the supply basin. Surface layers of the reservoir were tabulated as a function of the levels of gray in the imagery. In situ observations of water depth and reflectance were performed. Ground truth and LANDSAT data were correlated to determine the factors affecting the dynamics of the supply basin.

Dejesusparada, N.↗
NASA NTRS1988

Spectral feature design in high dimensional multispectral data

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Chen, Chih-Chien Thomas↗
NASA NTRS1984

NASA's activities in remote sensing

NASA spaceborne terrestrial remote-sensing projects of the 1960-1983 period are briefly surveyed, and future plans are outlined. The increased coverage of spectral bands and improving resolution provided by such satellites as Tiros, Seasat, and the ERTS/Landsat series are indicated; the Shuttle imaging radar, SAR, and multispectral IR radiometer are characterized; and the planned Upper-Atmospheric Research Satellite and ocean-topography experiment (Topex) are considered. Drawings and photographs of the spacecraft and sample images are included.

Edelson, B. I.↗
NASA NTRS2003

NASA IKONOS Multispectral Radiometric Calibration and 3-Year Temporal Stability Assessment

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can place confidence in the imagery they use and can fully understand its properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other system. In addition, the user community has little or no insight into the design and operation of commercial sensors or into the methods involved in generating commercial products. To address this calibration need, the NASA Stennis Space Center (SSC) Earth Science Applications (ESA) Directorate established a commercial satellite imaging radiometric calibration team consisting of three independent groups: NASA, SSC,ESA, the University of Arizona Remote Sensing Group, and South Dacota State University. Each group determined the absolute radiometric calibration coefficients of the Space Imaging IKONOS 4-band, 4 m multispectral product covering the visible through near-infrared spectral region. For a three year period beginning in 2000, each team employed some variant of a reflectance-based vicarious calibration approach, requiring ground-based measurements coincident with IKONOS image acquisitions and radiative transfer calculations. Several study sites throughout the United States were employed that covered nearly the entire dynamic range of the IKONOS sensor. IKONOS at-sensor radiance values were compared to those estimated by each independent group to determine the IKONOS sensor's radiometric accuracy and stability. Over 10 individual vicariously determined at-sensor radiance estimates were used each year. When combined, these estimates provided a high-precision radiometric gain calibration coefficient. No significant calibration offset was observed. The results of this evaluation provide the scientific community with an independent assessment of the IKONOS sensor's absolute calibration and temporal stability over the 3-year period. While the techniques and method described in this paper reflect those developed at the NASA SSC, the results of the entire team are included.

Pagnutti, Mary↗
NASA NTRSDate not supplied

Impact of Anthropogenic Activity, Climate Change, and Urbanization on Wetland Habitat in the Platte River Basin​

The Platte River Basin (PRB) is a dynamic ecosystem where wetlands play a pivotal role as essential habitats for various flora and fauna, including local and migratory birds. It provides many crucial ecosystem services that benefit humans directly and indirectly. However, anthropogenic activity, climate change, and urbanization have resulted in decline in wildlife habitat, elevated flood risk, and wetland loss. To address this issue, NASA DEVELOP partnered with Audubon Great Plains (AGP) to address the vital habitats within urban areas to protect bird species, reduce flood hazards, and analyze the potential impact of future development on wetlands. We utilized remotely sensed data from Landsat 8 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR) to assess land use and land cover (LULC) change. Nighttime lights data from Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) as well as NASA Socioeconomic Data and Applications Center (SEDAC) population data were also used as inputs to simulate urban growth potential up to 2050 using the open-source FUTure Urban-Regional Environment Simulation (FUTURES) model. A broad scale analysis across 13 focal cities showed varied changes in land use patterns across the PRB, with the most notable being a decrease in agricultural land coverage and an increase in vegetation and grassland coverage. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under AGP’s Urban Woods and Prairies Initiative. The results for two proposed scenarios showed that at least 51 counties out of 81 in the PRB would experience growth by year 2050. The first scenario (all wetlands are protected) showed that there will be no loss of wetlands by 2050. However, the second scenario (no wetlands are protected) showed a decrease in wetland area and loss of habitat for bird conservation. The results will help AGP to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies in the future.​

Nancee Uniyal↗
NASA NTRS1984

Experiences with digital processing of images at INPE

Four different research experiments with digital image processing at INPE will be described: (1) edge detection by hypothesis testing; (2) image interpolation by finite impulse response filters; (3) spatial feature extraction methods in multispectral classification; and (4) translational image registration by sequential tests of hypotheses.

Mascarenhas, N. D. A.↗