Fundamental remote sensing science research program. Part 1: Status report of the mathematical pattern recognition and image analysis project

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of the Earth from remotely sensed measurement of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inference about the Earth

Accurate Feature Extraction and Control Point Correction for Camera Calibration with a Mono-Plane Target

The paper addresses two problems related to 3D camera calibration using a single mono-plane calibration target with circular control marks. The first problem is how to compute accurately the locations of the features (ellipses) in images of the target. Since the structure of the control marks is known beforehand, we propose to use a shape-specific searching technique to find the optimal locations of the features. Our experiments have shown this technique generates more accurate feature locations than the state-of-the-art ellipse extraction methods. The second problem is how to refine the control mark locations with unknown manufacturing errors. We demonstrate in a case study, where the control marks are laser printed on a A4 paper, that the manufacturing errors of the control marks can be compensated to a good extent so that the remaining calibration errors are reduced significantly. 1

Observations of Detailed Structure in the Solar Wind at 1 AU with STEREO/HI-2

Heliospheric imagers offer the promise of remote sensing of large-scale structures present in the solar wind. The STEREO/HI-2 imagers, in particular, offer high resolution, very low noise observations of the inner heliosphere but have not yet been exploited to their full potential. This is in part because the signal of interest, Thomson scattered sunlight from free electrons, is ~1000 times fainter than the background visual field in the images, making background subtraction challenging. We have developed a procedure for separating the Thomson-scattered signal from the other background/foreground sources in the HI-2 data. Using only the Level 1 data from STEREO/HI-2, we are able to generate calibrated imaging data of the solar wind with sensitivity of a few times 1e-17 Bsun, compared to the background signal of a few times 1e-13 Bsun. These images reveal detailed spatial structure in CMEs and the solar wind at projected solar distances in excess of 1 AU, at the instrumental motion-blur resolution limit of 1-3 degree. CME features visible in the newly reprocessed data from December 2008 include leading-edge pileup, interior voids, filamentary structure, and rear cusps. "Quiet" solar wind features include V shaped structure centered on the heliospheric current sheet, plasmoids, and "puffs" that correspond to the density fluctuations observed in-situ. We compare many of these structures with in-situ features detected near 1 AU. The reprocessed data demonstrate that it is possible to perform detailed structural analyses of heliospheric features with visible light imagery, at distances from the Sun of at least 1 AU.Comment: Accepted by Astrophysical Journa

Coseismic surface deformation from air photos: The Kickapoo step over in the 1992 Landers rupture

Coseismic deformation of the ground can be measured from aerial views taken before and after an earthquake. We chose the area of the Kickapoo-Landers step over along the 1992 Landers earthquake zone, using air photos (scale 1:40,000) scanned at 0.4 m resolution. Two photos acquired after the earthquake are used to assess the accuracy and to evaluate various sources of noise. Optical distortions, film deformation, scanning errors, or errors in viewing parameters can yield metric bias at wavelength larger than 1 km. Offset field at shorter wavelength is more reliable and mainly affected by temporal decorrelation of the images induced by changes in radiometry with time. Temporal decorrelation and resulting uncertainty on offsets are estimated locally from the correlation degree between the images. Relative surface displacements are measured independently every about 15 m and with uncertainty typically below 10 cm (RMS). The offset field reveals most of the surface ruptures mapped in the field. The fault slip is accurate to about 7 cm (RMS) and measured independently every 200 m from stacked profiles. Slip distribution compares well with field measurements at the kilometric scale but reveals local discrepancies suggesting that deformation is generally, although not systematically, localized on the major fault zone located in the field. This type of data can provide useful insight into the fault zone's mechanical properties. Our measurements indicate that elastic coseismic strain near the fault zone can be as large as 0.5 × 10^(−3), while anelastic yielding was attained for strain in excess of about 1–2 × 10^(−3)

LANDSAT-4/5 image data quality analysis

A LANDSAT Thematic Mapper (TM) quality evaluation study was conducted to identify geometric and radiometric sensor errors in the post-launch environment. The study began with the launch of LANDSAT-4. Several error conditions were found, including band-to-band misregistration and detector-to detector radiometric calibration errors. Similar analysis was made for the LANDSAT-5 Thematic Mapper and compared with results for LANDSAT-4. Remaining band-to-band misregistration was found to be within tolerances and detector-to-detector calibration errors were not severe. More coherent noise signals were observed in TM-5 than in TM-4, although the amplitude was generally less. The scan direction differences observed in TM-4 were still evident in TM-5. The largest effect was in Band 4 where nearly a one digital count difference was observed. Resolution estimation was carried out using roads in TM-5 for the primary focal plane bands rather than field edges as in TM-4. Estimates using roads gave better resolution. Thermal IR band calibration studies were conducted and new nonlinear calibration procedures were defined for TM-5. The overall conclusion is that there are no first order errors in TM-5 and any remaining problems are second or third order

Determining remote sensing spatial resolution requirements for the monitoring of harmful algal blooms in the Great Lakes

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms\u27 spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 and HSI-3. Hyperspectral imagery is necessary in order to conduct experiments on differentiation of algal bloom types based on their spectral reflectance. In this analysis, imagery from September 19, 2016 was utilized to study the subpixel variability within the footprint of arbitrary sized pixels using several analysis techniques. This particular data set is utilized because it represents a worst case scenario where there is significant potential for public health concern due to high concentrations of microcystin toxin found in the water on this day and the concurrent observational challenges to accurately measure the algal bloom concentration variability with a remote sensing system due to the blooms high spatial variability. It has been determined that the optimal spatial resolution to monitor algal blooms in the Great Lakes is at most 50 m, and for much lower error 25 m, thus allowing for greater ease in identifying high concentration blooms near the surface. This resolution provides the best sensitivity to high concentration areas that are of significant importance in regard to human health and ecological damage

Semi-automated geomorphological mapping applied to landslide hazard analysis

Computer-assisted three-dimensional (3D) mapping using stereo and multi-image (“softcopy”) photogrammetry is shown to enhance the visual interpretation of geomorphology in steep terrain with the direct benefit of greater locational accuracy than traditional manual mapping. This would benefit multi-parameter correlations between terrain attributes and landslide distribution in both direct and indirect forms of landslide hazard assessment. Case studies involve synthetic models of a landslide, and field studies of a rock slope and steep undeveloped hillsides with both recently formed and partly degraded, old landslide scars. Diagnostic 3D morphology was generated semi-automatically both using a terrain-following cursor under stereo-viewing and from high resolution digital elevation models created using area-based image correlation, further processed with curvature algorithms. Laboratory-based studies quantify limitations of area-based image correlation for measurement of 3D points on planar surfaces with varying camera orientations. The accuracy of point measurement is shown to be non-linear with limiting conditions created by both narrow and wide camera angles and moderate obliquity of the target plane. Analysis of the results with the planar surface highlighted problems with the controlling parameters of the area-based image correlation process when used for generating DEMs from images obtained with a low-cost digital camera. Although the specific cause of the phase-wrapped image artefacts identified was not found, the procedure would form a suitable method for testing image correlation software, as these artefacts may not be obvious in DEMs of non-planar surfaces.Modelling of synthetic landslides shows that Fast Fourier Transforms are an efficient method for removing noise, as produced by errors in measurement of individual DEM points, enabling diagnostic morphological terrain elements to be extracted. Component landforms within landslides are complex entities and conversion of the automatically-defined morphology into geomorphology was only achieved with manual interpretation; however, this interpretation was facilitated by softcopy-driven stereo viewing of the morphological entities across the hillsides.In the final case study of a large landslide within a man-made slope, landslide displacements were measured using a photogrammetric model consisting of 79 images captured with a helicopter-borne, hand-held, small format digital camera. Displacement vectors and a thematic geomorphological map were superimposed over an animated, 3D photo-textured model to aid non-stereo visualisation and communication of results

Edge Detection with Sub-pixel Accuracy Based on Approximation of Edge with Erf Function

Edge detection is an often used procedure in digital image processing. For some practical applications is desirable to detect edges with sub-pixel accuracy. In this paper we present edge detection method for 1-D images based on approximation of real image function with Erf function. This method is verified by simulations and experiments for various numbers of samples of simulated and real images. Results of simulations and experiments are also used to compare proposed edge detection scheme with two often used moment-based edge detectors with sub-pixel precision

A Characterization Of Low Cost Simulator Image Generation Systems

Report identifies and briefly discusses the characteristics that should be considered in the evaluation, comparison, and selection of low cost computer image generation systems to be used for simulator applications