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  1. Sub-pixel resolution with the Multispectral Thermal Imager (MTI).

    The Multispectral Thermal Imager Satellite (MTI) has been used to test a sub-pixel sampling technique in an effort to obtain higher spatial frequency imagery than that of its original design. The MTI instrument is of particular interest because of its infrared detectors. In this spectral region, the detector size is traditionally the limiting factor in determining the satellite's ground sampling distance (GSD). Additionally, many over-sampling techniques require flexible command and control of the sensor and spacecraft. The MTI sensor is well suited for this task, as it is the only imaging system on the MTI satellite bus. In this super-samplingmore » technique, MTI is maneuvered such that the data are collected at sub-pixel intervals on the ground. The data are then processed using a deconvolution algorithm using in-scene measured point spread functions (PSF) to produce an image with synthetically-boosted GSD.« less
  2. Systematic evaluation of satellite remote sensing for identifying uranium mines and mills.

    In this report, we systematically evaluate the ability of current-generation, satellite-based spectroscopic sensors to distinguish uranium mines and mills from other mineral mining and milling operations. We perform this systematic evaluation by (1) outlining the remote, spectroscopic signal generation process, (2) documenting the capabilities of current commercial satellite systems, (3) systematically comparing the uranium mining and milling process to other mineral mining and milling operations, and (4) identifying the most promising observables associated with uranium mining and milling that can be identified using satellite remote sensing. The Ranger uranium mine and mill in Australia serves as a case study wheremore » we apply and test the techniques developed in this systematic analysis. Based on literature research of mineral mining and milling practices, we develop a decision tree which utilizes the information contained in one or more observables to determine whether uranium is possibly being mined and/or milled at a given site. Promising observables associated with uranium mining and milling at the Ranger site included in the decision tree are uranium ore, sulfur, the uranium pregnant leach liquor, ammonia, and uranyl compounds and sulfate ion disposed of in the tailings pond. Based on the size, concentration, and spectral characteristics of these promising observables, we then determine whether these observables can be identified using current commercial satellite systems, namely Hyperion, ASTER, and Quickbird. We conclude that the only promising observables at Ranger that can be uniquely identified using a current commercial satellite system (notably Hyperion) are magnesium chlorite in the open pit mine and the sulfur stockpile. Based on the identified magnesium chlorite and sulfur observables, the decision tree narrows the possible mineral candidates at Ranger to uranium, copper, zinc, manganese, vanadium, the rare earths, and phosphorus, all of which are milled using sulfuric acid leaching.« less
  3. Segmenting clouds from space : a hybrid multispectral classification algorithm for satellite imagery.

    This paper reports on a novel approach to atmospheric cloud segmentation from a space based multi-spectral pushbroom satellite system. The satellite collects 15 spectral bands ranging from visible, 0.45 um, to long wave infra-red (IR), 10.7um. The images are radiometrically calibrated and have ground sample distances (GSD) of 5 meters for visible to very near IR bands and a GSD of 20 meters for near IR to long wave IR. The algorithm consists of a hybrid-classification system in the sense that supervised and unsupervised networks are used in conjunction. For performance evaluation, a series of numerical comparisons to human derivedmore » cloud borders were performed. A set of 33 scenes were selected to represent various climate zones with different land cover from around the world. The algorithm consisted of the following. Band separation was performed to find the band combinations which form significant separation between cloud and background classes. The potential bands are fed into a K-Means clustering algorithm in order to identify areas in the image which have similar centroids. Each cluster is then compared to the cloud and background prototypes using the Jeffries-Matusita distance. A minimum distance is found and each unknown cluster is assigned to their appropriate prototype. A classification rate of 88% was found when using one short wave IR band and one mid-wave IR band. Past investigators have reported segmentation accuracies ranging from 67% to 80%, many of which require human intervention. A sensitivity of 75% and specificity of 90% were reported as well.« less
  4. Micropolarizing device for long wavelength infrared polarization imaging.

    The goal of this project is to fabricate a four-state pixelated subwavelength optical device that enables mid-wave infrared (MWIR) or long-wave infrared (LWIR) snapshot polarimetric imaging. The polarization information can help to classify imaged materials and identify objects of interest for numerous remote sensing and military applications. While traditional, sequential polarimetric imaging produces scenes with polarization information through a series of assembled images, snapshot polarimetric imaging collects the spatial distribution of all four Stokes parameters simultaneously. In this way any noise due to scene movement from one frame to the next is eliminated. We fabricated several arrays of subwavelength componentsmore » for MWIR polarization imaging applications. Each pixel unit of the array consists of four elements. These elements are micropolarizers with three or four different polarizing axis orientations. The fourth element sometimes has a micro birefringent waveplate on the top of one of the micropolarizers. The linear micropolarizers were fabricated by patterning nano-scale metallic grids on a transparent substrate. A large area birefringent waveplate was fabricated by deeply etching a subwavelength structure into a dielectric substrate. The principle of making linear micropolarizers for long wavelengths is based upon strong anisotropic absorption of light in the nano-metallic grid structures. The nano-metallic grid structures are patterned with different orientations; therefore, the micropolarizers have different polarization axes. The birefringent waveplate is a deeply etched dielectric one-dimensional subwavelength grating; therefore two orthogonally polarized waves have different phase delays. Finally, in this project, we investigated the near field and diffractive effects of the subwavelength element apertures upon detection. The fabricated pixelated polarizers had a measured extinction ratios larger than 100:1 for pixel sizes in the order of 15 {micro}m by 15 {micro}m that exceed by 7 times previously reported devices. The fabricated birefringent diffractive waveplates had a total variation of phase delay rms of 9.41 degrees with an average delay of 80.6 degrees across the MWIR spectral region. We found that diffraction effects change the requirement for separation between focal plane arrays (FPA) micropolarizer arrays and birefringent waveplates arrays, originally in the order of hundreds of microns (which are the typical substrate thickness) to a few microns or less. This new requirement leads us to propose new approaches to fabricate these devices.« less
  5. Sandia multispectral analyst remote sensing toolkit (SMART).

    This remote sensing science and exploitation work focused on exploitation algorithms and methods targeted at the analyst. SMART is a 'plug-in' to commercial remote sensing software that provides algorithms to enhance the utility of the Multispectral Thermal Imager (MTI) and other multispectral satellite data. This toolkit has been licensed to 22 government organizations.
  6. Evaluation of Remote Sensor Systems for Monitoring Uranium Mines.

    Abstract not provided.
  7. Geometric correction and digital elevation extraction using multiple MTI datasets.

    Digital Elevation Models (DEMs) are traditionally acquired from a stereo pair of aerial photographs sequentially captured by an airborne metric camera. Standard DEM extraction techniques can be naturally extended to satellite imagery, but the particular characteristics of satellite imaging can cause difficulties. The spacecraft ephemeris with respect to the ground site during image collects is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy, while a large angle of separation can cause an excessive number of erroneous points in themore » DEM from occlusion of ground areas. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of some sensors, such as the Multispectral Thermal Imager (MTI), allows for multiple collects of the same area from different perspectives. This functionality of MTI makes it a good candidate for the implementation of a DEM extraction algorithm using multiple images for improved accuracy. Evaluation of this capability and development of algorithms to geometrically model the MTI sensor and extract DEMs from multi-look MTI imagery are described in this paper. An RMS elevation error of 6.3-meters is achieved using 11 ground test points, while the MTI band has a 5-meter ground sample distance.« less
  8. Digital elevation extraction from multiple MTI data sets.

    The Digital Elevation Model (DEM) extraction process traditionally uses a stereo pair of aerial photographs that are sequentially captured using an airborne metric camera. Standard DEM extraction techniques have been naturally extended to utilize satellite imagery. However, the particular characteristics of satellite imaging can cause difficulties in the DEM extraction process. The ephemeris of the spacecraft during the collects, with respect to the ground test site, is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy. A large angle ofmore » separation can cause an excessive number of erroneous points in the output DEM. There is also a possibility of having occluded areas in the images when drastic topographic variation is present, making it impossible to calculate elevation in the blind spots. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of the Multispectral Thermal Imager (MTI) allows for multiple collects of the same area to be taken from different perspectives. This functionality of MTI makes it a good candidate for the implementation of DEM extraction using multiple images for improved accuracy. This paper describes a project to evaluate this capability and the algorithms used to extract DEMs from multi-look MTI imagery.« less
  9. Remote sensing data exploiration for geologic characterization of difficult targets : Laboratory Directed Research and Development project 38703 final report.

    Characterizing the geology, geotechnical aspects, and rock properties of deep underground facility sites can enhance targeting strategies for both nuclear and conventional weapons. This report describes the results of a study to investigate the utility of remote spectral sensing for augmenting the geological and geotechnical information provided by traditional methods. The project primarily considered novel exploitation methods for space-based sensors, which allow clandestine collection of data from denied sites. The investigation focused on developing and applying novel data analysis methods to estimate geologic and geotechnical characteristics in the vicinity of deep underground facilities. Two such methods, one for measuring thermalmore » rock properties and one for classifying rock types, were explored in detail. Several other data exploitation techniques, developed under other projects, were also examined for their potential utility in geologic characterization.« less

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"Smith, Jody Lynn"

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