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At least 793 records · Page 44

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NASA NTRS1984

Geometric Accuracy Assessment of LANDSAT-4 Multispectral Scanner (MSS)

Standard LANDSAT-4 MSS digital image data were analyzed for geometric accuracy using two P-format (UTM projection) images of the Washington, D.C. area, scene day 109 (ID number 4010915140) and scene day 125 (ID number 4012515144). Both scenes were tested for geodetic registration accuracy (scene-to-map), temporal registration accuracy (scene-to-scene), and band-to-band registration accuracy (within a scene). The combined RMS error for geodetic registration accuracy was 0.43 pixel (25.51 meters), well within specifications. The comparison between the 2 scenes was made on a band-by-band basis. The 90 percent error figure for temporal registration was 0.68 (57x57) pixel (38.8 meters). Although this figure is larger than the specification, it can be considered excellent with respect to user application. The best case registration errors between bands 1 and 2, and 3 and 4 were 14.2m and 13.7m, respectively, both within specifications. The worst case registration error was 38.0 m between bands 2 and 3.

Imhoff, M. L.↗

NASA NTRS2000

New Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Platnick, Steven↗

NASA NTRS2003

Global Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

King, Michael D.↗

NASA NTRS2003

Global Multispectral Cloud Retrievals from MODIS

King, Michael D.↗

NASA NTRS1967

A multichannel image data handling system for agricultural remote sensing.

Multichannel image data handling and processing system using multispectral analysis for remote agricultural sensing and surveying from aerospace platforms

MULTICHANNEL RECEIVER↗

NASA NTRS1993

A tool for manual endmember selection and spectral unmixing

Sampling a continuous radiance spectrum in many narrow contiguous spectral bands results in a high covariance between the bands. Hence, the true dimensionality of imaging spectrometer data is not determined by the number of spectral bands, but by the number of spectrally unique signatures whose mixtures reproduce the spectral variance observed in an image. Methods to unmix high dimensional multispectral data use principal components analysis to reduce the dimensionality. The variance of the spectral data is modeled as a linear combination of a finite set of endmembers in the space of the eigen-vectors that account for most of the variance. The number and characteristics of these endmembers are determined not only by the number and characteristics of the spectrally unique materials on the surface but also by processes (e.g., illumination, atmospheric scattering and absorption) affecting the signal received by the sensor. Selection of endmember spectra has typically been from a library. However, since most libraries are incomplete and do not account for the processes mentioned above, we have devised a computer display that allows researchers to explore interactively the eigenvector space of a representative and mean-corrected subset of the image data in search of extreme spectra to designate as endmembers. This display, which is based on parallel coordinates, is unique in the area of multidimensional visualization in that it includes not only a passive view of higher dimensional data but also the capability to interact and move geometrical objects in higher dimensional spaces.

Bateson, C. Ann↗

NASA NTRS1974

A study program on large aperture electronic scanning phased array antennas for the shuttle imaging microwave system

Fundamental phased array theory and performance parameters are discussed in terms of their application to microwave radiometry, and four scanning phased arrays representing current examples of state-of-the-art phased array technology are evaluated for potential use as components of the multispectral antenna system for the space shuttle imaging microwave system (SIMS). A discussion of problem areas, both in performance and fabrication is included, with extrapolations of performance characteristics for phased array antennas of increased sizes up to 20 m by 20 m. The possibility of interlacing two or more phased arrays to achieve a multifrequency aperture is considered, and, finally, a specific antenna system is recommended for use with SIMS.

Source record↗

NASA NTRS1994

Wavelet compression techniques for hyperspectral data

Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet transform coder was used for the two-dimensional compression. The third case used a three dimensional extension of this same algorithm.

Evans, Bruce↗

NASA NTRS1984

Evoluation of Landsat-4 image quality for the interpretation of forest, agricultural and soil resources

Landsat-4 Multispectral Scanner (MSS) and Thematic Mapper (TM) sensor performance is being evaluated through the analysis of images generated by computer-compatible tape data and commercially available film products. Natural targets are used to evaluate spectral variability, spatial resolution, radiometric sensitivity, and geometric fidelity. Spectral characteristics are being evaluated through the interpretation of the image tone and texture variability of known features, while spatial characteristics are evaluated through lineal and areal estimates of similar features and the plotting and analysis of residual errors derived from regressions between relative image coordinates and map coordinates.

Degloria, S. D.↗

NASA NTRS1973

Task 7: Image Enhancement and Advanced Information Extraction Techniques, 1385

The author has identified the following significant results. Atmospheric effects in satellite multispectral scanner data can influence results obtained with either manual image interpretation or computer information extraction techniques. The atmosphere attenuates radiation arriving from the surface and adds an extraneous path radiance component. Initial results of an investigation of atmospheric effects in ERTS-1 data are presented. Empirical analyses of ERTS-1 MSS data and simultaneous airborne MSS underflight data for one frame, along with theoretical calculations of atmospheric effects, are discussed. The effect of limited spatial resolution on the accuracy of information extracted from ERTS-1 data also is important. Problems occur when individual resolution elements contain two or more materials. Results from an initial application of Environmental Research Institute of Michigan techniques for estimating proportions of materials within individual elements are presented and discussed. Very accurate determination of surface areas of small lakes is achieved.

Malila, W. A.↗

NASA NTRS1973

Terrain type recognition using ERTS-1 MSS images

For the automatic recognition of earth resources from ERTS-1 digital tapes, both multispectral and spatial pattern recognition techniques are important. Recognition of terrain types is based on spatial signatures that become evident by processing small portions of an image through selected algorithms. An investigation of spatial signatures that are applicable to ERTS-1 MSS images is described. Artifacts in the spatial signatures seem to be related to the multispectral scanner. A method for suppressing such artifacts is presented. Finally, results of terrain type recognition for one ERTS-1 image are presented.

Gramenopoulos, N.↗

NASA NTRS2006

Multispectral Microimager for Astrobiology

A primary goal of the astrobiology program is the search for fossil records. The astrobiology exploration strategy calls for the location and return of samples indicative of environments conducive to life, and that best capture and preserve biomarkers. Successfully returning samples from environments conducive to life requires two primary capabilities: (1) in situ mapping of the mineralogy in order to determine whether the desired minerals are present; and (2) nondestructive screening of samples for additional in-situ testing and/or selection for return to laboratories for more in-depth examination. Two of the most powerful identification techniques are micro-imaging and visible/infrared spectroscopy. The design and test results are presented from a compact rugged instrument that combines micro-imaging and spectroscopic capability to provide in-situ analysis, mapping, and sample screening capabilities. Accurate reflectance spectra should be a measure of reflectance as a function of wavelength only. Other compact multispectral microimagers use separate LEDs (light-emitting diodes) for each wavelength and therefore vary the angles of illumination when changing wavelengths. When observing a specularly-reflecting sample, this produces grossly inaccurate spectra due to the variation in the angle of illumination. An advanced design and test results are presented for a multispectral microimager which demonstrates two key advances relative to previous LED-based microimagers: (i) acquisition of actual reflectance spectra in which the flux is a function of wavelength only, rather than a function of both wavelength and illumination geometry; and (ii) increase in the number of spectral bands to eight bands covering a spectral range of 468 to 975 nm.

microimager↗

NASA NTRS1994

Quantitative estimation of granitoid composition from thermal infrared multispectral scanner (TIMS) data, Desolation Wilderness, northern Sierra Nevada, California

We have produced images that quantitatively depict modal and chemical parameters of granitoids using an image processing algorithm called MINMAP that fits Gaussian curves to normalized emittance spectra recovered from thermal infrared multispectral scanner (TIMS) radiance data. We applied the algorithm to TIMS data from the Desolation Wilderness, an extensively glaciated area near the northern end of the Sierra Nevada batholith that is underlain by Jurassic and Cretaceous plutons that range from diorite and anorthosite to leucogranite. The wavelength corresponding to the calculated emittance minimum lambda(sub min) varies linearly with quartz content, SiO2, and other modal and chemical parameters. Thematic maps of quartz and silica content derived from lambda(sub min) values distinguish bodies of diorite from surrounding granite, identify outcrops of anorthosite, and separate felsic, intermediate, and mafic rocks.

Sabine, Charles↗

NASA NTRS1980

Visual enhancement of images of natural resources: Applications in geology

The principal components technique for use in multispectral scanner LANDSAT data processing results in optimum dimensionality reduction. A powerful tool for MSS IMAGE enhancement, the method provides a maximum impression of terrain ruggedness; this fact makes the technique well suited for geological analysis.

Dejesusparada, N.↗

NASA NTRS1971

Remote sensing of changes in morphology and physiology of trees under stress

Measurements on foliage samples collected from several drought and salt treated plants revealed that leaf thickness decreased with increasing severity of the drought treatment and increased with increasing severity of treatment with NaCl, but remained essentially unaffected by treatment with CaCl2. Airborne data collected by multispectral scanner indicated that false color images provide selective enhancement of a diseased area. Comparison of simulated and actual aerial color and color IR photography revealed that the color renditions of the MSS simulations agreed closely with those of the actual photography.

Olson, C. E., Jr.↗

NASA NTRS1974

User oriented ERTS-1 images

Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.

Shlien, S.↗

NASA NTRS1975

Breadboard linear array scan imager program

The performance was evaluated of large scale integration photodiode arrays in a linear array scan imaging system breadboard for application to multispectral remote sensing of the earth's resources. Objectives, approach, implementation, and test results of the program are presented.

Source record↗

NASA NTRS1976

An eight-neighbor filter for LARSYS

An eight-neighbor filter was developed for the LARSYS program. It is used in cleaning zones and sharpening boundaries during the digitization of hand-painted zone maps, in making computer-based vegetation zones more homogeneous, and in classification of natural images, such as LANDSAT or other multispectral imagery.

Boston, S.↗