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Research performed in the accuracy assessment of remotely sensed data is updated and reviewed. The use of discrete multivariate analysis techniques for the assessment of error matrices, the use of computer simulation for assessing various sampling strategies, and an investigation of spatial autocorrelation techniques are examined.
The planetary atmosphere of Mars was studied during the opposition of May, 1984, by means of a 10-micron heterodyne receiver mounted at the Cassegrain focus of a 3-m telescope. On the basis of a model of the Martian atmosphere, the isotopic ratios derived from the fully resolved absorption spectra obtained were compared with the results of Viking probe in situ measurements and terrestrial values; agreement is obtained within statistical errors. It is shown that highly resolving spectroscopy allows for the determination of isotopic ratios in remote sensing with a precision that is comparable to that of in situ mass spectroscopy.
Techniques being applied to test the sensitivity of the physical characteristics of clouds, as determined by remote sensing, to the spatial resolution of the scans are described. The sensitivity is being evaluated with an error assessment of data from the AVHRR instrument on Nimbus-7. A spatial coherence analysis is being applied to AVHRR data for a 250 sq km region in the Pacific off the Mexican coast. Errors in the derived cloud cover and radiances from which cloud-free regions and cloud-covered regions are being estimated on the basis of radiance values in pixel-sized areas.
An improved method is developed for eigenvalues and eigenvectors placement of a closed-loop control system using either state or output feedback. The method basically consists of three steps. First, the singular value of QR decomposition is used to generate an orthonormal basis that spans admissible eigenvector space corresponding to each assigned eigenvalue. Secondly, given a unitary matrix, the eigenvector set which best approximates the given matrix in the least-square sense and still satisfy eigenvalue cosntraints is determined. Thirdly, a unitary matrix is sought to minimize the error between the unitary matrix and the assignable eigenvector matrix. For use as the desired eigenvector set, two matrices, namely, the open-loop eigenvector matrix and its closest unitary matrix are proposed. The latter matrix generally encourages both minimum conditioning and control gains. In addition, the algorithm is formulated in real arithmetic for efficient implementation. To illustrate the basic concepts, numerical examples are included.
The fundamental principles of human-factors (HF) analysis for aviation applications are examined in a collection of reviews by leading experts, with an emphasis on recent developments. The aim is to provide information and guidance to the aviation community outside the HF field itself. Topics addressed include the systems approach to HF, system safety considerations, the human senses in flight, information processing, aviation workloads, group interaction and crew performance, flight training and simulation, human error in aviation operations, and aircrew fatigue and circadian rhythms. Also discussed are pilot control; aviation displays; cockpit automation; HF aspects of software interfaces; the design and integration of cockpit-crew systems; and HF issues for airline pilots, general aviation, helicopters, and ATC.
One of the most remarkable perceptual properties of common experience is that the perceived shapes of known objects are constant despite movements about them which transform their projections on the retina. This perceptual ability is one aspect of shape constancy (Thouless, 1931; Metzger, 1953; Borresen and Lichte, 1962). It requires that the viewer be able to sense and discount his or her relative position and orientation with respect to a viewed object. This discounting of relative position may be derived directly from the ranging information provided from stereopsis, from motion parallax, from vestibularly sensed rotation and translation, or from corollary information associated with voluntary movement. It is argued that: (1) errors in exocentric judgements of the azimuth of a target generated on an electronic perspective display are not viewpoint-independent, but are influenced by the specific geometry of their perspective projection; (2) elimination of binocular conflict by replacing electronic displays with actual scenes eliminates a previously reported equidistance tendency in azimuth error, but the viewpoint dependence remains; (3) the pattern of exocentrically judged azimuth error in real scenes viewed with a viewing direction depressed 22 deg and rotated + or - 22 deg with respect to a reference direction could not be explained by overestimation of the depression angle, i.e., a slant overestimation.
A control system architecture for an actively controlled segmented reflector is described along with a design realization for achieving precision alignment of reflector panels. Performance requirements are derived in part from the Large Deployable Reflector, which is a representative mission, and error allocations are made which consider mirror panel surface errors, position measurement and figure estimation, and position control of both quasi-static and dynamic disturbances. The design uses multiple wavelength interferometric edge sensors and voice coil actuators in conjunction with a hybrid control strategy to correct panel position errors. A unit cell shown to be central to the concept is analyzed. The cell integrates the sensing, actuation, and mechanical functions of a control module together with a reflector panel to form a unitized assembly.
The Voyager Planetary Radio Astronomy (PRA) antenna and receiver system provides an indication of the sense of elliptical or circular polarization of radiation that is not correct for all directions of incidence. The true sense could be determined for all directions if accurate calibration data were available. It was not feasible to make the calibration before the Voyagers were launched. Lecacheux & Ortega-Molina (1987), however, were able to derive such calibration data from planetary radio observations made in flight. They expressed their results in terms of the tilt of a plane (the E-plane) that divides the incident ray directions for which the indicated polarization sense is correct from those directions for which the indicated sense is reversed. We demonstrate that there are certain directions for which this calibration is itself in error, and that the surface dividing the two sets of incident rays is more complex than a tilted plane. We are able to make a crude approximation to the true surface from the limited data available.
This viewgraph presentation reviews the Adaptive Cross-Correlation (ACC) Algorithm for extended scene-Shack Hartmann wavefront (WF) sensing. A Shack-Hartmann sensor places a lenslet array at a plane conjugate to the WF error source. Each sub-aperture lenslet samples the WF in the corresponding patch of the WF. A description of the ACC algorithm is included. The ACC has several benefits; amongst them are: ACC requires only about 4 image-shifting iterations to achieve 0.01 pixel accuracy and ACC is insensitive to both background light and noise much more robust than centroiding,
The James Webb Space Telescope (JWST) requires testing of the full optical system in a cryogenic vacuum environment before launch. Challenges with the telescope architecture and the test environment lead to placing removable optical test sources at the Cassegrain intermediate focus of the Telescope. The Science Instrument suite will be used to align the telescope and to verify the wavefront error. The Science Instruments capture test images that are analyzed using focus diverse phase retrieval. The wavefront sensing algorithms have the large dynamic range required to measure the relatively small wavefronts of interest in the presence of the large aberrations resulting from the off-axis source locations at the intermediate focus. These inherent aberrations of the off-axis design are removed analytically from the measured data. The test design and in-situ wavefront sensing process enables a number of tests to verify the alignment and optical quality of the system.
The Advanced Technology Large Aperture Space Telescope (ATLAST) team has identified five key technologies to enable candidate architectures for the future large-aperture ultraviolet/optical/infrared (LUVOIR) space observatory envisioned by the NASA Astrophysics 30-year roadmap, Enduring Quests, Daring Visions. The science goals of ATLAST address a broad range of astrophysical questions from early galaxy and star formation to the processes that contributed to the formation of life on Earth, combining general astrophysics with direct-imaging and spectroscopy of habitable exoplanets. The key technologies are: internal coronagraphs, starshades (or external occulters), ultra-stable large-aperture telescopes, detectors, and mirror coatings. Selected technology performance goals include: 1x1010 raw contrast at an inner working angle of 35 milli-arcseconds, wavefront error stability on the order of 10 pm RMS per wavefront control step, autonomous on-board sensing & control, and zero-read-noise single-photon detectors spanning the exoplanet science bandpass between 400 nm and 1.8 μm. Development of these technologies will provide significant advances over current and planned observatories in terms of sensitivity, angular resolution, stability, and high-contrast imaging. The science goals of ATLAST are presented and flowed down to top-level telescope and instrument performance requirements in the context of a reference architecture: a 10-meter-class, segmented aperture telescope operating at room temperature (~290 K) at the sun-Earth Lagrange-2 point. For each technology area, we define best estimates of required capabilities, current state-of-the-art performance, and current Technology Readiness Level (TRL) - thus identifying the current technology gap. We report on current, planned, or recommended efforts to develop each technology to TRL 5.
In passive microwave remote sensing of soil moisture, the tau-omega (τ-ω) model has often been used to provide soil moisture estimates at a spatial scale representative of the satellite footprint dimensions. For modeling simplicity, model parameters such as the single scattering albedo (ω) and vegetation opacity (τ) that go into the geophysical inversion process are often assumed to be independent of polarizations. Although this absence of polarization dependence can often be justified in special cases as in low-frequency remote sensing or under dense vegetation conditions, it is not a robust assumption in general. Additional model parameterization errors arising from this assumption are possible, leading to degradation in soil moisture estimation accuracy. In this paper, we propose a time series approach to try to resolve the polarization dependence of several τ-ω model parameters as well as the temperature bias arising from the ancillary temperature data. The Version 4 of the Soil Moisture Active Passive (SMAP) Level 1B brightness temperature time series observations were used to illustrate the mechanics of this approach, with an emphasis on a comparison between resulting satellite soil moisture retrievals and in situ data collected at several core validation sites. It was found that this time series approach resulted in significant reduction of the dry bias exhibited in the current SMAP passive soil moisture data products, while retaining the same performance in other metrics of the current baseline passive soil moisture retrieval algorithm.
Calibration and validation determine the quality and integrity of the data provided by sensors and have enormous downstream impacts on the accuracy and reliabilityof the products generated by these sensors. With the imminent launch of the next generation of space borne imaging spectroscopy sensors, the IEEE Geoscience and Remote Sensing Society's (GRSS's) Geoscience Spaceborne Imaging Spectroscopy Technical Committee (GSIS TC) initiated a calibration and validation initiative.This article reports on a recent reflectance-based imaging spectrometer error budget field practicum focused on radiometric calibration of spaceborne imaging spectroscopy sensors. The field exercise, conducted at Railroad Valley in Nevada, provided valuable training for personnel in a variety of Earth observation (EO) areas, from engineers developing future sensors to calibration scientists actively working in the field. Future work in this area will focus on analyzing the data acquired as part of the training to answer numerous scientific questions, e.g., understanding the spatial and spectral homogeneity of the site being measured, identifying the optimal sampling to characterize the site, and optimizating the sampling techniques, including looking into the automation of some measurement protocol aspects. The training exercise was recorded to ensure that the knowledge can be disseminated across the GRSS and wider imaging spectroscopy community.
P1640 high contrast imaging system on the Palomar 200 inch Telescope consists of an apodized-pupil Lyot coronagraph, the PALM-3000 adaptive optics (P3K-AO), and P1640 Calibrator (CAL). Science images are recorded by an integral field spectrograph covering J-H bands for detecting and characterizing stellar companions. With aberrations from atmosphere corrected by the P3K-AO, instrument performance is limited mainly by the quasi-static speckles due to noncommon path wavefront aberrations for the light to propagate to the P3K-AO wavefront sensor and to the coronagraph mask. The non-common path wavefront aberrations are sensed by CAL, which measures the post-coronagraph E-field using interferometry, and can be effectively corrected by offsetting the P3K-AO deformable mirror target position accordingly. Previously, we have demonstrated using CAL measurements to correct high order wavefront aberrations, which is directly connected to the static speckles in the image plane. Low order wavefront, on the other hand, usually of larger amplitudes, causes light to leak through the coronagraph making the whole image plane brighter. Knowledge error in low order wavefront aberrations can also affect the estimation of the high order wavefront. Even though, CAL is designed to sense efficiently high order wavefront aberrations, the low order wavefront front can be inferred with less sensitivity. Here, we describe our method for estimating both low and high order wavefront aberrations using CAL measurements by propagating the post-coronagraph E-field to a pupil before the coronagraph. We present the results from applying this method to both simulated and experiment data.
Long-term measurements from satellites and surface stations have demonstrated a decreasing trend of tropospheric carbon monoxide (CO) in the Northern Hemisphere over the past decade. Likely explanations for this decrease include changes in anthropogenic, fires, and/or biogenic emissions or changes in the primary chemical sink hydroxyl radical (OH). Using remotely sensed CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument, in situ methyl chloroform (MCF) measurements from the World Data Centre for Greenhouse Gases (WDCGG) and the adjoint of the GEOS-Chem model, we estimate the change in global CO emissions from 2001 to 2015. We show that the loss rate of MCF varied by 0.2 % in the past 15 years, indicating that changes in global OH distributions do not explain the recent decrease in CO. Our two-step inversion approach for estimating CO emissions is intended to mitigate the effect of bias errors in the MOPITT data as well as model errors in transport and chemistry, which are the primary factors contributing to the uncertainties when quantifying CO emissions using these remotely sensed data. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, and unchanged anthropogenic CO emissions from Europe since 2008. We find decreasing trends of biomass burning CO emissions from boreal North America, boreal Asia and South America, but little change over Africa. In contrast to prior results, we find that a positive trend in CO emissions is likely for India and southeast Asia.
The equations for large-eddy simulation (LES) are derived formally by applying a spatial filter to the Navier-Stokes equations. The filter width as well as the details of the filter shape are free parameters in LES, and these can be used both to control the effective resolution of the simulation and to establish the relative importance of different portions of the resolved spectrum. An analogous, but less well justified, approach to filtering is more or less universally used in conjunction with LES using finite-difference methods. In this approach, the finite support provided by the computational mesh as well as the wavenumber-dependent truncation errors associated with the finite-difference operators are assumed to define the filter operation. This approach has the advantage that it is also 'automatic' in the sense that no explicit filtering: operations need to be performed. While it is certainly convenient to avoid the explicit filtering operation, there are some practical considerations associated with finite-difference methods that favor the use of an explicit filter. Foremost among these considerations is the issue of truncation error. All finite-difference approximations have an associated truncation error that increases with increasing wavenumber. These errors can be quite severe for the smallest resolved scales, and these errors will interfere with the dynamics of the small eddies if no corrective action is taken. Years of experience at CTR with a second-order finite-difference scheme for high Reynolds number LES has repeatedly indicated that truncation errors must be minimized in order to obtain acceptable simulation results. While the potential advantages of explicit filtering are rather clear, there is a significant cost associated with its implementation. In particular, explicit filtering reduces the effective resolution of the simulation compared with that afforded by the mesh. The resolution requirements for LES are usually set by the need to capture most of the energy-containing eddies, and if explicit filtering is used, the mesh must be enlarged so that these motions are passed by the filter. Given the high cost of explicit filtering, the following interesting question arises. Since the mesh must be expanded in order to perform the explicit filter, might it be better to take advantage of the increased resolution and simply perform an unfiltered simulation on the larger mesh? The cost of the two approaches is roughly the same, but the philosophy is rather different. In the filtered simulation, resolution is sacrificed in order to minimize the various forms of numerical error. In the unfiltered simulation, the errors are left intact, but they are concentrated at very small scales that could be dynamically unimportant from a LES perspective. Very little is known about this tradeoff and the objective of this work is to study this relationship in high Reynolds number channel flow simulations using a second-order finite-difference method.
An analysis of phenomena causing nonlinearities in the transformation from Landsat multispectral scanner coordinates to ground coordinates is presented. Experimental results comparing rms errors at ground control points indicated a slight improvement when a nonlinear (8-parameter) transformation was used instead of an affine (6-parameter) transformation. Using a preliminary ground truth map of a test site in Alabama covering the Mobile Bay area and six Landsat images of the same scene, several classification methods were assessed. A methodology was developed for automatic change detection using classification/cluster maps. A coding scheme was employed for generation of change depiction maps indicating specific types of changes. Inter- and intraseasonal data of the Mobile Bay test area were compared to illustrate the method. A beginning was made in the study of data compression by applying a Karhunen-Loeve transform technique to a small section of the test data set. The second part of the report provides a formal documentation of the several programs developed for the analysis and assessments presented.
The basic geometric features of a developed sea surface affecting the accuracy of wind speed measurements by satellite instruments are reviewed. Error trends in the satellite winds are shown to be correlated with various measures of wave development. For a developed sea, the influence of the equilibrium range parameters characterizing the spectrum of wind-generated waves are derived and compared with field observations. Fluctuations in the actual number of steep wavelet events which occur within a finite surface area are shown to be an important factor of the radar backscatter if the surface area, i.e., the resolution cell, is much smaller than 1 sq km. The inner scale of the equilibrium range caused by energy dissipation by breaking waves is considered to be a major factor in determining the surface's statistical geometry and, hence, its microwave returns for all satellite sensors.