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NASA NTRSDate not supplied

Assessment of Sensor Footprint Size and Comparison of Commercial Smallsat Images

Science users of commercial satellite data build their studies on the properties of the satellite data they work with, pixel size being one of the determining factors. However, pixel size and nominal image footprint size can be different, impacting the scale of features discernable in the satellite images. Here, we assess geometric properties such as nominal image footprint size for Planet Labs' SuperDove series, MAXAR's WorldView series, and potentially BlackSky. Additionally, we assess temporal change in nominal footprint size for the SuperDove series. Nominal Image footprint size is assessed over the CalVal sites in Baotou, China; Shadnagar, India; and Big Spring, TX. Edge spread functions are constructed along the black/white transitions, from which the line spread functions are constructed and modulation transfer functions of the scene are estimated. Scene full width half maximum (FWHM), which represents sensor footprint size, is estimated from the line spread function. The average nominal footprint size is 3.3 pixels for SuperDove series, 1.5 pixels for WorldView-2, and 1.3 pixels for WorldView-3. The SuperDove series nominal footprint size improves with time in orbit, from an average of 3.4 pixels soon after launch to an average of 3.2 pixels one or more years after launch.

PlanetScope↗
NASA NTRS1974

Correlation and registration of ERTS multispectral imagery

Examples of automatic digital processing demonstrate the feasibility of registering one ERTS multispectral scanner (MSS) image with another obtained on a subsequent orbit, and automatic matching, correlation, and registration of MSS imagery with aerial photography (multisensor correlation) is demonstrated. Excellent correlation was obtained with patch sizes exceeding 16 pixels square. Qualities which lead to effective control point selection are distinctive features, good contrast, and constant feature characteristics. Results of the study indicate that more than 300 degrees of freedom are required to register two standard ERTS-1 MSS frames covering 100 by 100 nautical miles to an accuracy of 0.6 pixel mean radial displacement error. An automatic strip processing technique demonstrates 600 to 1200 degrees of freedom over a quater frame of ERTS imagery. Registration accuracies in the range of 0.3 pixel to 0.5 pixel mean radial error were confirmed by independent error analysis. Accuracies in the range of 0.5 pixel to 1.4 pixel mean radial error were demonstrated by semi-automatic registration over small geographic areas.

Bonrud, L. O.↗
NASA NTRS1981

Toward multidisciplinary use of LANDSAT: Interfacing computerized LANDSAT analysis systems with geographic information systems

The LANDSAT-geographic information system (GIS) interface must summarize the results of the LANDSAT classification over the same cells that serve as geographic referencing units for the GIS, and output these summaries on a cell-by-cell basis in a form that is readable by the input routines of the GIS. The ZONAL interface for cell-oriented systems consists of two primary programs. The PIXCEL program scans the grid of cells and outputs a channel of pixels. Each pixel contains not the reflectance values but the identifier of the cell in which the center of the pixel is located. This file of pixelized cells along with the results of a pixel-by-pixel classification of the scene produced by the LANDSAT analysis system are input to the CELSUM program which then outputs a cell-by-cell summary formatted according to the requirements of the host GIS. Cross-correlation of the LANDSAT layer with the other layers in the data base is accomplished with the analysis and display facilities of the GIS.

Myers, W. L.↗
NASA NTRS1983

Effects of autocorrelation upon LANDSAT classification accuracy

Richmond, Virginia and Denver, Colorado were study sites in an effort to determine the effect of autocorrelation on the accuracy of a parallelopiped classifier of LANDSAT digital data. The autocorrelation was assumed to decay to insignificant levels when sampled at distances of at least ten pixels. Spectral themes developed using blocks of adjacent pixels, and using groups of pixels spaced at least 10 pixels apart were used. Effects of geometric distortions were minimized by using only pixels from the interiors of land cover sections. Accuracy was evaluated for three classes; agriculture, residential and "all other"; both type 1 and type 2 errors were evaluated by means of overall classification accuracy. All classes give comparable results. Accuracy is approximately the same in both techniques; however, the variance in accuracy is significantly higher using the themes developed from autocorrelated data. The vectors of mean spectral response were nearly identical regardless of sampling method used. The estimated variances were much larger when using autocorrelated pixels.

Craig, R. G.↗
NASA NTRS1991

Performance characteristics of the imaging MAMA detector systems for SOHO, STIS, and FUSE/Lyman

Imaging Extreme Ultraviolet (EUV) Multi-Anode Microchannel Array (MAMA) detector systems with formats of 360 x 1024 pixels and pixel dimensions of 25 x 25 sq microns are being fabricated and tested for flight in two instruments on the ESA/NASA Solar and Heliospheric Observatory (SOHO). In addition, very-large-format (1024 x 1024)- and (2048 x 2048)-pixel Far Ultraviolet (FUV) and EUV MAMA detectors with pixel dimensions of 25 x 25 sq microns are being fabricated and tested for use in the NASA Goddard Space Flight Center's Hubble Space Telescope Imaging Spectrograph (STIS), a second-generation instrument scheduled for in-orbit installation in 1997. Finally, FUV MAMA detectors with formats of 224 x 960 pixels and pixel dimensions of 14 x 14 sq microns are being evaluated as prototypes of the detector for the prime FUV spectrograph of the Far Ultraviolet Spectroscopic Explorer (FUSE/Lyman) mission. The configurations and performance characteristics of the different detector systems are described, and the plans for further development of the Advanced Technology MAMA detector system discussed.

Timothy, J. G.↗
NASA NTRS1991

Full complex spatial filtering with a phase mostly DMD

A new technique for implementing fully complex spatial filters with a phase mostly deformable mirror device (DMD) light modulator is described. The technique combines two or more phase-modulating flexure-beam mirror elements into a single macro-pixel. By manipulating the relative phases of the individual sub-pixels within the macro-pixel, the amplitude and the phase can be independently set for this filtering element. The combination of DMD sub-pixels into a macro-pixel is accomplished by adjusting the optical system resolution, thereby trading off system space bandwidth product for increased filtering flexibility. Volume in the larger dimensioned space, space bandwidth-complex axes count, is conserved. Experimental results are presented mapping out the coupled amplitude and phase characteristics of the individual flexure-beam DMD elements and demonstrating the independent control of amplitude and phase in a combined macro-pixel. This technique is generally applicable for implementation with any type of phase modulating light modulator.

Florence, James M.↗
NASA NTRS1995

SeaWiFS technical report series. Volume 31: Stray light in the SeaWiFS radiometer

Some of the measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will not be useful as ocean measurements. For the ocean data set, there are procedures in place to mask the SeaWiFS measurements of clouds and ice. Land measurements will also be masked using a geographic technique based on each measurment's latitude and longitude. Each of these masks involves a source of light much brighter than the ocean. Because of stray light in the SeaWiFS radiometer, light from these bright sources can contaminate ocean measurements located a variable number of pixels away from a bright source. In this document, the sources of stray light in the sensor are examined, and a method is developed for masking measurements near bright targets for stray light effects. In addition, a procedure is proposed for reducing the effects of stray light in the flight data from SeaWiFS. This correction can also reduce the number of pixels masked for stray light. Without these corrections, local area scenes must be masked 10 pixels before and after bright targets in the along-scan direction. The addition of these corrections reduces the along-scan masks to four pixels before and after bright sources. In the along-track direction, the flight data are not corrected, and are masked two pixels before and after. Laboratory measurements have shown that stray light within the instrument changes in a direct ratio to the intensity of the bright source. The measurements have also shown that none of the bands show peculiarities in their stray light response. In other words, the instrument's response is uniform from band to band. The along-scan correction is based on each band's response to a 1 pixel wide bright sources. Since these results are based solely on preflight laboratory measurements, their successful implementation requires compliance with two additional criteria. First, since SeaWiFS has a large data volume, the correction and masking procedures must be such that they can be converted into computationally fast algorithms. Second, they must be shown to operate properly on flight data. The laboratory results, and the corrections and masking procedures that derive from them, should be considered as zeroeth order estimates of the effects that will be found on orbit.

Hooker, Stanford B.↗
NASA NTRS1999

Preliminary Performance of CdZnTe Imaging Detector Prototypes

The promise of good energy and spatial resolution coupled with high efficiency and near-room-temperature operation has fuelled a large International effort to develop Cadmium-Zinc-Telluride (CdZnTe) for the hard-x-ray region. We present here preliminary results from our development of small-pixel imaging arrays fabricated on 5x5x1-mm and 5x5x2-mm spectroscopy and discriminator-grade material. Each array has 16 (4x4) 0.65-mm gold readout pads on a 0.75-mm pitch, with each pad connected to a discrete preamplifier via a pulse-welded gold wire. Each array is mounted on a 3-stage Peltier cooler and housed in an ion-pump-evacuated housing which also contains a hybrid micro-assembly for the 16 channels of electronics. We have investigated the energy resolution and approximate photopeak efficiency for each pixel at several energies and have used an ultra-fine beam x-ray generator to probe the performance at the pixel boundaries. Both arrays gave similar results, and at an optimum temperature of -20 C we achieved between 2 and 3% FWHM energy resolution at 60 keV and around 15% at 5.9 keV. We found that all the charge was contained within 1 pixel until very close to the pixels edge, where it would start to be shared with its neighbor. Even between pixels, all the charge would be appropriately shared with no apparently loss of efficiency or resolution. Full details of these measurements will be presented, together with their implications for future imaging-spectroscopy applications.

Ramsey, B.↗
NASA NTRS1997

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Quattrochi, Dale A.↗
NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗
NASA NTRS2001

Sensing, Spectra and Scaling: What's in Store for Land Observations

Bill Pecora's 1960's vision of the future, using spacecraft-based sensors for mapping the environment and exploring for resources, is being implemented today. New technology has produced better sensors in space such as the Landsat Thematic Mapper (TM) and SPOT, and creative researchers are continuing to find new applications. However, with existing sensors, and those intended for launch in this century, the potential for extracting information from the land surface is far from being exploited. The most recent technology development is imaging spectrometry, the acquisition of images in hundreds of contiguous spectral bands, such that for any pixel a complete reflectance spectrum can be acquired. Experience with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has shown that, with proper attention paid to absolute calibration, it is possible to acquire apparent surface reflectance to 5% accuracy without any ground-based measurement. The data reduction incorporates in educated guess of the aerosol scattering, development of a precipitable water vapor map from the data and mapping of cirrus clouds in the 1.38 micrometer band. This is not possible with TM. The pixel size in images of the earth plays and important role in the type and quality of information that can be derived. Less understood is the coupling between spatial and spectral resolution in a sensor. Recent work has shown that in processing the data to derive the relative abundance of materials in a pixel, also known is unmixing, the pixel size is an important parameter. A variance in the relative abundance of materials among the pixels is necessary to be able to derive the endmembers or pure material constituent spectra. In most cases, the 1 km pixel size for the Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is too large to meet the variance criterion. A pointable high spatial and spectral resolution imaging spectrometer in orbit will be necessary to make the major next step in our understanding of the solid earth surface and its changing face.

Goetz, Alexander F. H.↗
NASA NTRS2004

Retinal Light Processing Using Carbon Nanotubes

Method and system for processing light signals received by the eye of a human or other animal, where the eye may be compromised or non-functioning. Incident light is received at first and second pixels in a photodetector array and provides a pixel electrical signal representing the received light. Each of an array of carbon nanotube (CNT) towers is connected to a pixel, has a first tower end penetrating a retinal active layer of the animal and has a second tower end positioned to receive to receive and transport the pixel electrical signal to the retinal active layer. The CNT tower may be coated with a biologically active substance or chemically modified to promote neurite connections with the tower. The photoreceptor array can be provide with a signal altering mechanism that alters at least one of light intensity and wavelength intensity sensed by a first pixel relative to a second pixel, to correct for one or more selected eye problems.

David J Loftus↗
NASA NTRS2004

Background Count Rates and the Anti-Coincidence Detector on the Instrument on Astro-E2

Minimum ionizing particles incident on the XRS microcalorimeter array will deposit energy in the pixels on the same scale as an x-ray photon and would be confused with x-rays without an anti-coincidence detector. The XRS anti-coincidence detector is a silicon ionization detector placed directly behind the calorimeter array. Given an isotropic particle flux, 98% of those particles that pass through a calorimeter pixel will also deposit energy in the anti-coincidence detector. Particle events that are not rejected by coincidence are those that pass through at small angles relative to the plane of the array, and thus deposit more energy. Modeling with GEANT4 showed that only 0.1% of all protons incident on the array miss the anti-coincidence detector yet deposit less than 10 keV in a pixel. The unrejected background will thus be dominated by secondary events; we will provide an estimate of this rate. Protons incident on the thick silicon frame around the active area of the array deposit enough energy t o heat the whole chip slightly. This results in small simultaneous pulses on multiple pixels. These can be easily rejected by pixel-to-pixel coincidence. We will discuss the impact of these events on the instrument dead time and will present the expected rate. We will present laboratory background data demonstrating the performance of the anti-coincidence detector and the effectiveness of coincidence analysis in the laboratory environment.

Kilbourne, C. A.↗
NASA NTRS2005

Dynamically re-configurable CMOS imagers for an active vision system

A vision system is disclosed. The system includes a pixel array, at least one multi-resolution window operation circuit, and a pixel averaging circuit. The pixel array has an array of pixels configured to receive light signals from an image having at least one tracking target. The multi-resolution window operation circuits are configured to process the image. Each of the multi-resolution window operation circuits processes each tracking target within a particular multi-resolution window. The pixel averaging circuit is configured to sample and average pixels within the particular multi-resolution window.

Yang, Guang↗
NASA NTRS2010

Image Segmentation Analysis for NASA Earth Science Applications

NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

Tilton, James C.↗
NASA NTRS2009

The OMPS Limb Profiler Instrument: An Alternative Data Analysis and Retrieval Algorithm

The upcoming Ozone Mapper and Profiler Suite (OMPS), which will be launched on the NPOESS Preparatory Project (NPP) platform in early 2011, will continue monitoring the global distribution of the Earth's middle atmosphere ozone and aerosol. OMPS is composed of three instruments, namely the Total Column Mapper (heritage: TOMS, OMI), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE, OSIRIS, SCIAMACHY, SAGE III). The ultimate goal of the mission is to better understand and quantify the rate of stratospheric ozone recovery. The focus of the paper will be on the Limb Profiler (LP) instrument. The LP instrument will measure the Earth fs limb radiance (which is due to the scattering of solar photons by air molecules, aerosol and Earth surface) in the ultra-violet (UV), visible and near infrared, from 285 to 1000 nm. The LP simultaneously images the whole vertical extent of the Earth's limb through three vertical slits, each covering a vertical tangent height range of 100 km and each horizontally spaced by 250 km in the cross-track direction. The focal plane of the LP spectrometer is a two ]dimensional CCD array comprised of 340 x 740 pixels. Several data analysis tools are presently being constructed and tested to retrieve ozone and aerosol vertical distribution from limb radiance measurements. The primary NASA algorithm is based on earlier algorithms developed for the SOLSE/LORE and SAGE III limb scatter missions. The paper will describe an alternative algorithm which will retrieve ozone density and aerosol extinction directly from radiance data collected on individual CCD pixels. This alternative method uses an optimal estimation approach to retrieve ozone and aerosol in the 10-60 km range from the information contained within an ensemble of about 50000 down-linked pixels. Tangent height registration is performed using the Rayleigh Scattering Attitude Sensor (RSAS) technique applied to columns of pixels in the 340-360 nm range. Cloud height is determined by analyzing the radiance first derivative along pixel columns at longer wavelengths. Wavelength registration is performed using rows of pixels and identifying Fraunhofer solar lines within the measured spectra. Special attention is given to stray-light decontamination and modeling of the measured finite spectral/spatial line shape functions.

Rault, Didier F.↗
NASA NTRS2011

Kilopixel X-Ray Microcalorimeter Arrays for Astrophysics: Device Performance and Uniformity

We are developing kilo-pixel arrays of TES microcalorimeters to enable high-resolution X-ray imaging spectrometers for future X-ray observatories and laboratory astrophysics experiments. Our current array design was targeted as a prototype for the X-ray Microcalorimeter Spectrometer proposed for the International X-ray Observatory, which calls for a 40x40-pixel core array of 300 micron devices with 2.5 e V energy resolution (at 6 keV). Here we present device characterization of our 32x32 arrays, including X-ray spectral performance of individual pixels within the array. We present our results in light of the understanding that our Mo/Au TESs act as weak superconducting links, causing the TES critical current (Ic) and transition shape to oscillate with applied magnetic field (B). We show Ic(B) measurements and discuss the uniformity of these measurements across the array, as well as implications regarding the uniformity of device noise and response. In addition, we are working to reduce pixel-to-pixel electrical and thermal crosstalk; we present recent test results from an array that has microstrip wiring and an angle-evaporated Cu backside heatsinking layer, which provides Cu coverage on the four sidewalls of the silicon wells beneath each pixel.

Eckart, M. E.↗
NASA NTRS2010

Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET

We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

Mishchenko, Michael I.↗