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NASA NTRS1972

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. For the exploitation of the ERTS-1 images, both multispectral and spatial pattern recognition techniques are important. A multispectral recognition software program was successfully tested. A technique for the generation of resource boundaries has been successfully combined with terrain recognition software resulting in a regionalized terrain classification system. Digital registration of multispectral images has been achieved. Also, photointerpretation results from one test site are reported and the development of spatial terrain signatures from optical diffraction patterns is described.

Gramenopoulos, N.↗

NASA NTRS1982

Study of atmospheric diffusion using LANDSAT

The parameters of diffusion patterns of atmospheric pollutants under different conditions were investigated for use in the Gaussian model for calculation of pollution concentration. Value for the divergence pattern of concentration distribution along the Y axis were determined using LANDSAT images. Multispectral scanner images of a point source plume having known characteristics, wind and temperature data, and cloud cover and solar elevation data provided by LANDSAT, were analyzed using the 1-100 system for image analysis. These measured values are compared with pollution transport as predicted by the Pasquill-Gifford, Juelich, and Hoegstroem atmospheric models.

Torsani, J. A.↗

NASA NTRS1991

Integration of optical and microwave images for geologic mapping and resource explorations

Multispectral images in the visible, near-IR, short-wave IR, thermal IR, and microwave regions, obtained during the Geologic Remote Sensing Field Experiment were combined with data from Landsat TM, laboratory, and field spectral measurements, as well as traditional geologic mapping and were used to produce thematic image maps showing details of the surface geology for an area at the north end of Death Valley (California/Nevada). The integrated multispectral images provide new geologic information which can be used in mineral deposit models to provide exploration targets. The data demonstrated the relationship between the surface composition of materials and remote sensing in the visible and infrared.

Kruse, Fred A.↗

NASA NTRS1991

Integration of diverse remote sensing data sets for geologic mapping and resource exploration

The use of high-quality multispectral images in the visible, near-infrared, shortwave infrared, thermal infrared, and microwave regions of the spectrum for producing thematic maps showing details of the surface geology is reported. The airborne data sets used in the study include the Airborne Visible/Infrared Imaging Spectrometer, the Thermal Infrared Multispectral Scanner, and the airborne SAR. Ancillary data include a digital elevation model, National High Altitude Photography, Landsat Multispectral Scanner data, Landsat Thematic Mapper data, laboratory and field spectral measurements, and traditional geologic mapping. The integrated, multispectral images are shown to provide new geologic information that can be used in mineral deposit models to provide exploration targets.

Kruse, Fred A.↗

NASA NTRS1983

An exploitation of coregistered SIR-A, Seasat and Landsat images

Multispectral registration and classification of SIR-A, Seasat SAR, and Landsat MSS data is presented over two playas located in the northeastern Algerian Sahara. A supervised classification was made over six classes: salt, palm trees, dunes, limestones, gypsum and sand. The best classification is obtained by using all of the data. The images using radar only misclassify trees and salt, limestone and dunes, gypsum and dunes. Landsat only gives a good map but lacks the roughness information contained in the radar data. The Landsat/SIR-A combination gives a better classification than the Landsat/Seasat combination. Density number histograms computed within several classes on the Seasat and SIR-A data show the misclassification is mainly due to the Seasat data.

Rebillard, P.↗

NASA NTRS2009

Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

McCorkel, Joel↗

NASA NTRS1996

Field Geology/Processes

The field geology/process group examined the basic operations of a terrestrial field geologist and the manner in which these operations could be transferred to a planetary lander. Four basic requirements for robotic field geology were determined: geologic content; surface vision; mobility; and manipulation. Geologic content requires a combination of orbital and descent imaging. Surface vision requirements include range, resolution, stereo, and multispectral imaging. The minimum mobility for useful field geology depends on the scale of orbital imagery. Manipulation requirements include exposing unweathered surfaces, screening samples, and bringing samples in contact with analytical instruments. To support these requirements, several advanced capabilities for future development are recommended. Capabilities include near-infrared reflectance spectroscopy, hyper-spectral imaging, multispectral microscopy, artificial intelligence in support of imaging, x ray diffraction, x ray fluorescence, and rock chipping.

Allen, Carlton↗

NASA NTRS1985

Retrieval of cloud cover parameters from multispectral satellite images

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Arking, A.↗

NASA NTRS1977

Multispectral-scanner image processing

QUIKLOOK program performs approximate geometric and radiometric corrections of Landsat multispectral-scanner digital data and calculates Earth rotation (skew) correction from format center latitude as given by annotation record of Landsat bulk computer-compatible tapes.

Stein, M. I.↗

NASA NTRS1983

Interpretation of aircraft multispectral scanner images for mapping of alteration with uranium mineralization, Copper Mountain, Wyoming

NS-001 multispectral scanner data (0.45-2.35 micron) combined as principal components were utilized to map distributions of surface oxidation/weathering in Precambrian granitic rocks at Copper Mountain, Wyoming. Intense oxidation is found over granitic outcrops in partly exhumed pediments along the southern margin of the Owl Creek uplift, and along paleodrainages higher in the range. Supergene(?) uranium mineralization in the granites is localized beneath remnant Tertiary sediments covering portions of the pediments. The patterns of mineralization and oxidation are in agreement, but the genetic connections between the two remain in doubt.

Conel, J. E.↗

NASA NTRS1993

Software For Computing Image Ratios

RATIO_TOOL is interactive computer program for viewing and analyzing large sets of multispectral image data created by imaging spectrometer. Uses ratios between intensities in different spectral bands in order to spot significant areas of interest within multispectral image. Each image band viewed iteratively, or selected image band of set of data requested and displayed. When image ratios computed, result displayed as grayscale image. Written in C Language.

Yates, Gigi L.↗

NASA NTRS2003

Software for Simulating Remote Sensing Systems

The Application Research Toolbox (ART) is a collection of computer programs that implement algorithms and mathematical models for simulating remote sensing systems. The ART is intended to be especially useful for performing design-tradeoff studies and statistical analyses to support the rational development of design requirements for multispectral imaging systems. Among other things, the ART affords a capability to synthesize coarser-spatial-resolution image-data sets from finer-spatial-resolution data sets and multispectral-image-data products from hyperspectral-image-data products. The ART also provides for synthesis of image-degradation effects, including point-spread functions, misregistration of spectral images, and noise. The ART can utilize real or synthetic data sets, along with sensor specifications, to create simulated data sets. In one example of a typical application, simulated data pertaining to an existing multispectral sensor system are used to verify the data collected by the system in operation. In the case of a proposed sensor system, the simulated data can be used to conduct trade studies and statistical analyses to ensure that the sensor system will satisfy the requirements of potential scientific, academic, and commercial user communities.

Zanoni, Vicki↗

NASA NTRS2003

Software for Simulating Remote Sensing Systems

Vicki Zanoni↗

NASA NTRS1995

Remotely sensed image compression based on wavelet transform

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. the transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.

Kim, Seong W.↗

NASA NTRSDate not supplied

Development of Multi-Edge Slant Target for Unlocalized MTF Measurement of Airborne Imaging System Payloads

Calibration of imaging instruments is a critical step in effectively characterizing imaging data. A comprehensive characterization of an imaging system provides valuable insight into the overall uncertainties in the results derived from the raw data collected. The Scientifically Calibrated In-Flight Imagery (SCIFLI) team (based at NASA Langley Research Center) has designed, built, tested, and successfully flown the optical payload known as the SCIFLI Airborne Multispectral Imager (SAMI). SAMI is a multispectral imaging payload, complete with sensor configurations for the Ultraviolet-Visible spectrum as well as Near- Infrared, Shortwave Infrared, and Midwave Infrared bands and is fitted with various optical hardware designed to turn, split, and focus light beams to the respective in-band sensors. Radiometric calibrations are performed for SAMI such that the accuracy and uncertainty of thermal and spectral measurements are effectively characterized. However, SAMI does not regularly undergo spatial characterizations to evaluate the performance of the imager at high spatial frequencies. This is essential, as understanding the spatial sensor response of discrete sensors is just as important as the spectral sensor response. The payload currently utilizes a calibration cart for lab testing. Equipped with a modular setup and several radiation sources, it is perfect for performing high-quality radiometric calibrations. This work focuses on using the calibration cart to perform spatial calibrations. A custom designed calibration target is being used to evaluate the optical performance of SAMI. Specifically, the target is designed to measure the Modulation Transfer Function (MTF) of the imager in discrete locations around the focal plane. The results of this characterization will provide insight into the spatial resolution capabilities of the SAMI payload in practice. Future work includes using the results of the study to correct optical imperfections in imagery taken with SAMI.

SAMI↗

NASA NTRS1972

Image correlation and sampling study

The development of analytical approaches for solving image correlation and image sampling of multispectral data is discussed. Relevant multispectral image statistics which are applicable to image correlation and sampling are identified. The general image statistics include intensity mean, variance, amplitude histogram, power spectral density function, and autocorrelation function. The translation problem associated with digital image registration and the analytical means for comparing commonly used correlation techniques are considered. General expressions for determining the reconstruction error for specific image sampling strategies are developed.

Popp, D. J.↗

NASA NTRS1992

Lunar Resources Using Moderate Spectral Resolution Visible and Near-infrared Spectroscopy: Al/si and Soil Maturity

Modern visible and near-infrared detectors are critically important for the accurate identification and relative abundance measurement of lunar minerals; however, even a very small number of well-placed visible and near-infrared bandpass channels provide a significant amount of general information about crucial lunar resources. The Galileo Solid State Imaging system (SSI) multispectral data are an important example of this. Al/Si and soil maturity will be discussed as examples of significant general lunar resource information that can be gleaned from moderate spectral resolution visible and near-infrared data with relative ease. Because quantitative-albedo data are necessary for these kinds of analyses, data such as those obtained by Galileo SSI are critical. SSI obtained synoptic digital multispectral image data for both the nearside and farside of the Moon during the first Galileo Earth-Moon encounter in December 1990. The data consist of images through seven filters with bandpasses ranging from 0.40 microns in the ultraviolet to 0.99 microns in the near-infrared. Although these data are of moderate spectral resolution, they still provide information for the following lunar resources: (1) titanium content of mature mare soils based upon the 0.40/0.56-micron (UV/VIS) ratio; (2) mafic mineral abundance based upon the 0.76/0.99-micron ratio; and (3) the maturity or exposure age of the soils based upon the 0.56-0.76-micron continuum and the 0.76/0.99-micron ratio. Within constraints, these moderate spectral resolution visible and near-infrared reflectance data can also provide elemental information such as Al/Si for mature highland soils.

Fischer, Erich M.↗

NASA NTRS1976

Digital preprocessing and classification of multispectral earth observation data

The development of airborne and satellite multispectral image scanning sensors has generated wide-spread interest in application of these sensors to earth resource mapping. These point scanning sensors permit scenes to be imaged in a large number of electromagnetic energy bands between .3 and 15 micrometers. The energy sensed in each band can be used as a feature in a computer based multi-dimensional pattern recognition process to aid in interpreting the nature of elements in the scene. Images from each band can also be interpreted visually. Visual interpretation of five or ten multispectral images simultaneously becomes impractical especially as area studied increases; hence, great emphasis has been placed on machine (computer) techniques for aiding in the interpretation process. This paper describes a computer software system concept called LARSYS for analysis of multivariate image data and presents some examples of its application.

Anuta, P. E.↗