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The following techniques are considered for classifying low resolution satellite imagery: (1) Gradient operations; (2) histogram methods; (3) gray level detection; (4) frequency domain operations; (5) Hadamard transform in digital image matching; and (6) edge and line detection schemes.
Various image processing techniques developed for enhancement and extraction of linear features, of interest to the structural geologist, from digital remote sensing, geologic, and gravity data, are presented. These techniques include: (1) automatic detection of linear features and construction of rose diagrams from Landsat MSS data; (2) enhancement of principal structural directions using selective filters on Landsat MSS, Spacelab panchromatic, and HCMM NIR data; (3) directional filtering of Spacelab panchromatic data using Fast Fourier Transform; (4) detection of linear/elongated zones of high thermal gradient from thermal infrared data; and (5) extraction of strong gravimetric gradients from digitized Bouguer anomaly maps. Processing results can be compared to each other through the use of a geocoded database to evaluate the structural importance of each lineament according to its depth: superficial structures in the sedimentary cover, or deeper ones affecting the basement. These image processing techniques were successfully applied to achieve a better understanding of the transition between Provence and the Pyrenees structural blocks, in southeastern France, for an improved structural interpretation of the Mediterranean region.
A high temperature pressure transducer and sensing apparatus to determine the deflection of the transducer diaphragm is disclosed. The pressure transducer utilizes a fused silica diaphragm (12) which is illuminated at selected locations by a coherent laser source (52) via optical fibers (38, 46). The light reflected by the diaphragm (12) forms interference fringe patterns which are focused by gradient index rod lenses (36) on the ends of optical fibers (40, 48) for transmission to a fringe counting circuit (54). By digital techniques, the fringe count is converted into a determination of diaphragm deflection.
Within randomly sampled squares of a 1 km x 1 km grid, rill/gullies frequency, land cover/land use type and shape of the slopes were extracted from aerial photographs of the Ribeirao Anhumas drainage basin. Mean slope gradient, stream frequency and slope length were calculated on topographic maps. Ground truth data on fine sand/coarse sand ratio and vegetation cover densities were obtained. The MSS-LANDSAT-2 data (CCTs) were analyzed using single-cell, cluster synthesis and slicer algorithms. Graphical and statistical analyses of the data indicate that different slope gradients and land cover/land use types are the most significant factors related to the soil erosion process. The digital analysis of MSS data allowed the association among gray level classes and vegetation cover classes, which defined seven classes. These gray level classes and slope gradient classes were used to rank erosion risk.
The planetary boundary layer (PBL) is the lowest layer of the atmosphere in contact with the Earth's surface. It plays an important role in atmospheric circulation and dynamics by influencing surface fluxes of moisture, heat, and momentum. The PBL is characterized by its turbulence structure. Organized convection within the PBL may generate gravity waves within the free troposphere. These waves can propagate vertically, modifying global circulation. Remote sensing of the PBL using a downward-looking lidar is providing new insight into dynamic processes of this important layer and its connection with wave generation. An airborne lidar is an ideal tool to study the PBL. The lidar is installed on the NASA Electra aircraft. It consists of a frequency doubled Nd:YAG laser aligned with a 40 cm diameter telescope. As the laser beam propagates downward from the aircraft toward the surface, it is scattered by the aerosols and molecules in the atmosphere. Generally, there is a sharp gradient of aerosol scattering associated with the PBL top, with high aerosol scattering from within the PBL, and generally very low scattering from the free atmosphere above. It is this gradient in aerosol scattering that is used to visualize the structure of the PBL. A small portion of the scattered radiation is collected by the telescope, filtered, detected by a photomultiplier, and digitized at 100 nsec rate. The horizontal resolution is typically around 13 m, using a 10 Hz laser and a nominal aircraft moves, the resolution of features in the atmosphere below the aircraft is about 15 x 13 m. Results from several studies are presented and discussed.
The problem of image registration, or alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times, and that would provide sub-pixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the band-pass wavelets obtained from the Steerable Pyramid due to Simoncelli perform better than two types of low-pass pyramids when the images being registered have relatively small amount of nonlinear radiometric variations between them. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.
The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.
Our project focused on the investigation of the post-eruption hazards at Mt. Pinatubo (Philippines) using remote sensing data, and field observations of the 1991 eruption deposits. Through the use of multiple satellite images, field work, and the 1996/2000 PacRim data sets, we conducted studies of the co- and post-eruption hazards of the volcano due to erosion and re-deposition of the extensive pyroclastic flow deposits. A major part of this project was the assembly and analysis of a database of over 50 high resolution (1 - 50 m/pixel) images that will facilitate this study. We collected Ikonos, SPOT, SIR-C/X-SAR, Landsat, ERS, RADARSAT, and ASTER images of the area around Mt. Pinatubo. An example of the changes that could be seen in these data is shown. Our investigation focused on a retrospective analysis of the erosion, redeposition, and re-vegetation of the 1991 pyroclastic flow deposits of Mt. Pinatubo. The primary geologic goal of our work was the analysis of the spatial distribution and volume change of the sources and sinks of materials associated with mudflow ('lahar') events. This included the measurement of river valley gradients and cross-sections using TOPSAR digital elevation data, as we are participating in the PacRim 2000 deployment to the Philippines specifically so that we can collect a second set of TOPSAR data that can then be used to create a topographic difference image of the volcano. The main results from this multi-sensor study have been published as Torres et al.. A discussion of the methodology that we used to assemble an appropriate database was included in Mouginis-Mark and Domergue-Schmidt. As part of an educational outreach effort, we also helped the Philippine Institute of Volcanology and Seismology (PHIVOLCS) in the Philippines to use NASA data to study Mt. Pinatubo and other Filipino volcanoes.
We tested the hypothesis that the relative water content (RWC) of the sunlit leaves in a plant canopy may be estimated from polarized canopy imagery. Recently (IGARSS, July 27-31, 2015, Milan, Italy), we reported the results of laboratory polarization measurements of single detached leaves during dry down. We found that RWC was linearly related to the ratio of the reflectance of the interior of the leaf and the leaf transmittance. Here we report application of the laboratory results to estimate RWC for sunlit leaves in a plant canopy. Using a commercial-off-the-shelf (COTS) Nikon 810 camera with Nikkor 300 mm lens and Polaroid type HN-22 linear polarizer, we photographed in the principle plane a plant canopy displaying a gradient of water stress and collected, at each of multiple points along the gradient, two images, one with the polarization filter oriented for maximum scene response and a second with the filter oriented for minimum scene response. We converted the digital values in the two images to reflectance factor with reference to images of a white, flat, horizontal Spectralon surface. We classified the polarization imagery, identifying reflecting leaves, transmitting leaves, other sunlit vegetation and shadows. For each image pair we normalized the leaf internal reflectance by dividing by the cosine of the angle of incidence of the sunlight on the leaf, selected the leaf maximum transmittance in the scene and divided to obtain the ratio reflectance/transmittance, which we compared with leaf RWC. We determined the leaf relative water content by harvesting a section of leaf and immediately placing it in a sealed container in an ice chest. Later in the laboratory the leaf sample was weighed, rehydrated, weighed, dried and again weighed. RWC was determined using the standard formula. Our experimental results support our hypothesis, suggesting that the RWC of sunlit leaves in a plant canopy may be estimated from analysis of polarization imagery collected by a COTS camera system. Unlike remotely sensed estimates of canopy equivalent water thickness, our estimates of the RWC of sunlit canopy leaves provide leaf physiological information. We propose RWC estimates based upon sunlit leaves are more relevant to assessing the water status of a plant canopy than would be RWC estimates based upon large FOV canopy measurements.
Snow depth was one of the core ground measurements required to validate remotely-sensed data collected during SnowEx Year 1, which occurred in Colorado. The use of a single, common protocol was fundamental to produce a community reference dataset of high quality. Most of the nearly 100 Grand Mesa and Senator Beck Basin SnowEx ground crew participants contributed to this crucial dataset during 6-25 February 2017. Snow depths were measured along ~300 m transects, whose locations were determined according to a random-stratified approach using snowfall and tree-density gradients. Two-person teams used snowmobiles, skis, or snowshoes to travel to staked transect locations and to conduct measurements. Depths were measured with a 1-cm incremented probe every 3 meters along transects. In shallow areas of Grand Mesa, depth measurements were also collected with GPS snow-depth probes (a.k.a. MagnaProbes) at ~1-m intervals. During summer 2017, all reference stake positions were surveyed with <10 cm accuracy to improve overall snow depth location accuracy. During the campaign, 193 transects were measured over three weeks at Grand Mesa and 40 were collected over two weeks in Senator Beck Basin, representing more than 27,000 depth values. Each day of the campaign depth measurements were written in waterproof field books and photographed by National Snow and Ice Data Center (NSIDC) participants. The data were later transcribed and prepared for extensive quality assessment and control. Common issues such as protocol errors (e.g., survey in reverse direction), notebook image issues (e.g., halo in the center of digitized picture), and data-entry errors (sloppy writing and transcription errors) were identified and fixed on a point-by-point basis. In addition, we strove to produce a georeferenced product of fine quality, so we calculated and interpolated coordinates for every depth measurement based on surveyed stakes and the number of measurements made per transect. The product has been submitted to NSIDC in csv format. To educate data users, we present the study design and processing steps that have improved the quality and usability of this product. Also, we will address measurement and design uncertainties, which are different in open vs. forest areas.
Flight testing of the performance seeking control (PSC) excitation mode was successfully completed at NASA Dryden on the F-15 highly integrated digital electronic control (HIDEC) aircraft. Although the excitation mode was not one of the original objectives of the PSC program, it was rapidly prototyped and implemented into the architecture of the PSC algorithm, allowing valuable and timely research data to be gathered. The primary flight test objective was to investigate the feasibility of a future measurement-based performance optimization algorithm. This future algorithm, called AdAPT, which stands for adaptive aircraft performance technology, generates and applies excitation inputs to selected control effectors. Fourier transformations are used to convert measured response and control effector data into frequency domain models which are mapped into state space models using multiterm frequency matching. Formal optimization principles are applied to produce an integrated, performance optimal effector suite. The key technical challenge of the measurement-based approach is the identification of the gradient of the performance index to the selected control effector. This concern was addressed by the excitation mode flight test. The AdAPT feasibility study utilized the PSC excitation mode to apply separate sinusoidal excitation trims to the controls - one aircraft, inlet first ramp (cowl), and one engine, throat area. Aircraft control and response data were recorded using on-board instrumentation and analyzed post-flight. Sensor noise characteristics, axial acceleration performance gradients, and repeatability were determined. Results were compared to pilot comments to assess the ride quality. Flight test results indicate that performance gradients were identified at all flight conditions, sensor noise levels were acceptable at the frequencies of interest, and excitations were generally not sensed by the pilot.