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At least 487 records · Page 27

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NASA NTRS1983

Experimental philosophy leading to a small scale digital data base of the conterminous United States for designing experiments with remotely sensed data

Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.

Labovitz, M. L.↗

DOE OSTI2021

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Evaluation of partial volume correction and analysis of longitudinal [ 18 F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models

Purpose: We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [ 18 F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM). Methods: We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden–level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates. Results: The VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability. Conclusion: The results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [ 18 F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test–retest variability. Clinical trial registration: NCT02640092 and NCT03289143.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1984

Performance evaluation and geologic utility of LANDSAT-4 TM and MSS data

Radiometric calibration accuracy of TM data, radiometric comparison of A-, B-, and P-format data, and geometric registration accuracy of the TM data at enlarged scales were analyzed. Radiometric analysis of the Wind River Basin, Wyoming scene demonstrates that the TM system can be used to extract image reflectance spectra from ground targets following calibration of the system. It was also demonstrated that: (1) image DN (radiance values) vs. ground reflectance calibration scatterplots yield parameters which can be used to constrain atmospheric models and can determine TM radiometric sensitivity; (2) no significant degradation occurs as a result of radiometric and geometric correction by SCROUNGE processing; and (3) TM data can be enlarged to 1:24000 with no major geometric distortions or misregistration problems to USGS topographic maps.

Paylor, E. D.↗

NASA NTRS1990

Ultrasonic and radiographic evaluation of advanced aerospace materials: Ceramic composites

Two conventional nondestructive evaluation techniques were used to evaluate advanced ceramic composite materials. It was shown that neither ultrasonic C-scan nor radiographic imaging can individually provide sufficient data for an accurate nondestructive evaluation. Both ultrasonic C-scan and conventional radiographic imaging are required for preliminary evaluation of these complex systems. The material variations that were identified by these two techniques are porosity, delaminations, bond quality between laminae, fiber alignment, fiber registration, fiber parallelism, and processing density flaws. The degree of bonding between fiber and matrix cannot be determined by either of these methods. An alternative ultrasonic technique, angular power spectrum scanning (APSS) is recommended for quantification of this interfacial bond.

Generazio, Edward R.↗

NASA NTRS1992

The impact of misregistration on change detection

The impact of images misregistration on the detection of changes in land cover was studied using spatially degraded Landsat MSS images. Emphasis is placed on simulated images of the Normalized Difference Vegetation Index (NDVI) at spatial resolutions of 250 and 500 m. It is pointed out that there is the need to achieve high values of registration accuracy. The evidence from simulations suggests that misregistrations can have a marked effect on the ability of remotely sensed data to detect changes in land cover. Even subpixel misregistrations can have a major impact, and the most marked proportional changes will tend to occur at the finest misregistrations.

Townshend, John R. G.↗

NASA NTRS1982

Geometric registration and rectification of spaceborne SAR imagery

This paper describes the development of automated location and geometric rectification techniques for digitally processed synthetic aperture radar (SAR) imagery. A software package has been developed that is capable of determining the absolute location of an image pixel to within 60 m using only the spacecraft ephemeris data and the characteristics of the SAR data collection and processing system. Based on this location capability algorithms have been developed that geometrically rectify the imagery, register it to a common coordinate system and mosaic multiple frames to form extended digital SAR maps. These algorithms have been optimized using parallel processing techniques to minimize the operating time. Test results are given using Seasat SAR data.

Curlander, J. C.↗

NASA NTRS1983

LANDSAT-4 image data quality analysis

Analysis during the quarter was carried out on geometric, radiometric, and information content aspects of both MSS and thematic mapper (TM) data. Test sites in Webster County, Iowa and Chicago, IL., and near Joliet, IL were studied. Band to band registration was evaluated and TM Bands 5 and 7 were found to be approximately 0.5 pixel out of registration with 1,2,3,4, and the thermal was found to be misregistered by 4 30 m pixels to the east and 1 pixel south. Certain MSS bands indicated nominally .25 pixel misregistration. Radiometrically, some striping was observed in TM bands and significant oscillatory noise patterns exist in MSS data which is possibly due to jitter. Information content was compared before and after cubic convolution resampling and no differences were observed in statistics or separability of basic scene classes.

Anuta, P. E.↗

NASA NTRS1983

Performance appraisal of VAS radiometry for GOES-4, -5 and -6

The first three VISSR Atmospheric Sounders (VAS) were launched on GOES-4, -5, and -6 in 1980, 1981 and 1983. Postlaunch radiometric performance is assessed for noise, biases, registration and reliability, with special attention to calibration and problems in the data processing chain. The postlaunch performance of the VAS radiometer meets its prelaunch design specifications, particularly those related to image formation and noise reduction. The best instrument is carried on GOES-5, currently operational as GOES-EAST. Single sample noise is lower than expected, especially for the small longwave and large shortwave detectors. Detector to detector offsets are correctable to within the resolution limits of the instrument. Truncation, zero point and droop errors are insignificant. Absolute calibration errors, estimated from HIRS and from radiation transfer calculations, indicate moderate, but stable biases. Relative calibration errors from scanline to scanline are noticeable, but meet sounding requirements for temporarily and spatially averaged sounding fields of view. The VAS instrument is a potentially useful radiometer for mesoscale sounding operations. Image quality is very good. Soundings derived from quality controlled data meet prelaunch requirements when calculated with noise and bias resistant algorithms.

Chesters, D.↗

NASA NTRS1984

CCRS proposal for evaluating LANDSAT-4 MSS and TM data

The measurement of registration errors in LANDSAT MSS data is discussed as well as the development of a revised algorithm for the radiometric calibration of TM data and the production of a geocoded TM image.

Strome, W. M.↗

NASA NTRS1985

Preliminary Evaluation of Thematic Mapper Image Data Quality

Improvements in the ability to monitor renewable resources/vegegation due to improvements in the spatial, spectral and radiometric resolution of TM data were evaluated. Results presented from the first 4 months of analysis presented include: (1) geometric performance; (2) band-to-band registration; (3) modulation transfer function; and (4) crop separabililty performance. Crop separability in Webster County, Iowa and in Mississippi County, Arkansas as determined by cluster and principal components analyses is assessed.

Macdonald, R. B.↗

NASA NTRS1985

The geometric properties of Landsat-5 Thematic Mapper data and their conformity to Landsat-4 data and to earth's surface geometry

The geometry of two TIPS processed Landsat-5 Thematic Mapper scenes was analyzed and compared with that of SCROUNGE processed Landsat-4 data. Swath-to-swath and band-to-band registration of Washington, DC, and northeastern Iowa scenes was found to be similar to or better than that of Landsat-4 data. Results indicate a high degree of geometric conformity between the images produced by the different systems. The geometric conformity of the TIPS processed images to the Space Oblique Mercator projection, however, proved to be less accurate than the targeted processing error of 15 meters.

Walker, R. E.↗

NASA NTRS1987

Rectification of terrain induced distortions in radar imagery

This paper describes a technique to generate geocoded synthetic aperture radar (SAR) imagery corrected for terrain induced geometric distortions. This algorithm transforms the raw slant range image, generated by the signal processor, into a map registered product, resampled to either Universal Transverse Mercator (UTM) or Polar Stereographic projections, and corrected for foreshortening. The technique utilizes the space platform trajectory information in conjunction with a digital elevation map (DEM) of the target area to generate an ortho-radar map with near-autonomous operation. The current procedure requires only two to three tie-points to compensate for the platform position uncertainty that results in translational error between the image and the DEM. This approach is unique in that it does not require generation of a simulated radar image from the DEM or a grid of tie-points to characterize the image-to-map distortions. Rather, it models the inherent distortions based on knowledge of the radar data collection characteristics, the signal Doppler parameters, and the local terrain height to automatically predict the registration transformation. This algorithm has been implemented on a minicomputer system equipped with an array processor and a large random-access memory to optimize the throughput.

Kwok, Ronald↗

NASA NTRS1991

Automated multisensor registration - Requirements and techniques

The synergistic utilization of data from a suite of remote sensors requires multi-dimensional analysis of the data. Prior to this analysis, processing is required to correct for the systematic geometric distortions characteristic of each sensor, followed by a registration operation to remove any residual offsets. Furthermore, to handle a large volume of data and high data rates, the registration process must be fully automated. A conceptual approach is presented that integrates a variety of registration techniques and selects the candidate algorithm based on certain performance criteria. The performance requirements for an operational algorithm are formulated given the spatially, temporally, and spectrally varying factors that influence the image characteristics and the science requirements of various applications. Several computational techniques are tested and their performance evaluated using a multisensor test data set assembled from the Landsat TM, Seasat, SIR-B, TIMS, and SPOT sensors. The results are discussed and recommendations for future studies are given.

Rignot, Eric J. M.↗

NASA NTRS2017

Characterizing the GOES-R (GOES-16) Geostationary Lightning Mapper (GLM) On-Orbit Performance

Two overlapping efforts help to characterize the GLM performance, the Post Launch Test (PLT) phase to validate the predicted pre-launch instrument performance and the Post Launch Product Test (PLPT) phase to validate the lightning detection product used in forecast and warning decision-making. This paper documents the calibration and validation plans and activities for the first 6 months of GLM on-orbit testing and validation commencing with first light on 4 January 2017. The PLT phase addresses image quality, on-orbit calibration, RTEP threshold tuning, image navigation, noise filtering, and solar intrusion assessment, resulting in a GLM calibration parameter file. The PLPT includes four main activities, the Reference Data Comparisons (RDC), Algorithm Testing (AT), Instrument Navigation and Registration Testing (INRT), and Long Term Baseline Testing (LTBT). Field campaigns are also designed to contribute valuable insights into the GLM performance capabilities. The PLPT tests each contribute to the beta, provisional, and fully validated GLM data.

validation↗

NASA NTRS2016

Motion Estimation System Utilizing Point Cloud Registration

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

Chen, Qi↗

NASA NTRS1984

Use of satellite data in agricultural surveys

The state-of-the-art of crop surveying by satellite is reviewed with an emphasis on the signature extension problem. Registration and preprocessing procedures are discussed with refereence to: normalization of the radiometric values of each scene for scene-to-scene differences; registration techniques, implemented at the NASA Johnson Space Center, capable of 0.5 pixel root-mean-square error; and current research in this direction. Data transformation and modeling techniques applied to the Landsat MSS images and a solution for the field-to-field variations of the greenness and brightness temporal trajectories are included. Finally, a review of the mixture decomposition method of labeling and estimating the areal proportions is given.

Hall, F. G.↗

NASA NTRSDate not supplied

Ground control points refresh for MODIS and VIIRS geolocation monitoring

The Control Point Matching (CPM) program and a set of over 1200 globally distributed ground control points (GCPs ) have been successfully used to develop more than 20 years of MODIS geolocation products. In this research, we refresh current GCP library with more than 2500 new GCPs using the latest Landsat 8 Collection 2 images. The refreshed GCPs are distributed from 56 S to 80 N latitude, with more than 2000 shoreline and 500 inland GCP chips. The size of these GCPs are extended from800*800 to 1400*1400 Landsat pixels and the CPM program correspondingly increase s t h e searching distance from 0.8 pixels to 2.5 pixels, which also extends the geolocation error measurement from +/-45 to the edge of scan at +/-55 degree in scan angle. This will allow the algorithm to catch geolocation errors that are larger than one MODIS pixel. The geolocation errors measured with the refreshed GCP library are comparable to the previous results, yet with 2-3more times of matched GCPs. The daytime Aqua ascending orbits and Terra descending orbits enable us to identify a few GCP outliers which might be due to the quality of the original Landsat images. Most importantly, the refreshed GCP library will include images from both Landsat band 4 to match with VIIRS I1, and Landsat band 6 to match with VIIRS I3. This will allow us to measure and correct on orbit band-to-band registration at both track and scan directions, which will help understanding and improving future JPSS mission’s prelaunch geometric performance.

VIIRS↗