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At least 145 records · Page 8

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗

Simulation and analysis of grating-integrated quantum dot infrared detectors for spectral response control and performance enhancement

We propose and analyze a novel detector structure for pixel-level multispectral infrared imaging. More specifically, we investigate the device performance of a grating-integrated quantum dots-in-a-well photodetector under backside illumination. Our design uses 1-dimensional grating patterns fabricated directly on a semiconductor contact layer and, thus, adds a minimal amount of additional effort to conventional detector fabrication flows. We show that we can gain wide-range control of spectral response as well as large overall detection enhancement by adjusting grating parameters. For small grating periods, the spectral responsivity gradually changes with parameters. We explain this spectral tuning using the Fabry–Perot resonance and effective medium theory. For larger grating periods, the responsivity spectra get complicated due to increased diffraction into the active region, but we find that we can obtain large enhancement of the overall detector performance. In our design, the spectral tuning range can be larger than 1 μm, and, compared to the unpatterned detector, the detection enhancement can be greater than 92% and 148% for parallel and perpendicular polarizations. Our work can pave the way for practical, easy-to-fabricate detectors, which are highly useful for many infrared imaging applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Polarization-selective optical transmission through a plasmonic metasurface

We present the design, fabrication, and experimental characterization of a nanoslit-based metasurface that offers polarization-selective optical transmission for advanced imaging applications. The metasurface consists of an array of meta-atoms, constructed with two orthogonally coupled subwavelength apertures. Highly enhanced optical transmission was achieved by selective excitation of surface plasmon waves on the metasurface. By rotating the orientation of the linearly polarized incident beam, switching of enhanced optical transmission bands through the metasurface was experimentally demonstrated. This demonstration is a significant step towards developing advanced multispectral imaging devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Validation of 2D Te and ne measurements made with Helium imaging spectroscopy in the volume of the TCV divertor

Abstract Multi-spectral imaging of helium atomic emission (HeMSI) has been used to create 2D poloidal maps of T e and n e in TCV’s divertor. To achieve these measurements, TCV’s MANTIS multispectral cameras (Perek et al 2019 Rev. Sci. Instrum. 90 123514) simultaneously imaged four He I lines (two singlet and two triplet) and a He II line (468 nm) from passively present He and He + . The images, which were absolutely calibrated and covered the whole divertor region, were inverted through the assumption of toroidal symmetry to create emissivity profiles and, consequently, line-ratio profiles. A collisional-radiative model (CRM) was applied to the line-ratio profiles to produce 2D poloidal maps of T e and n e . The collisional-radiative modeling was accomplished with the Goto helium CRM code (Zholobenko et al 2018 Nucl. Fusion 58 126006, Zholobenko et al 2018 Technical Report , Goto 2003 J. Quant. Spectrosc. Radiat. Transfer 76 331–44) which accounts for electron-impact excitation (EIE) and deexcitation, and electron–ion recombination (EIR) with He + . The HeMSI T e and n e measurements were compared with co-local Thomson scattering measurements. The two sets of measurements exhibited good agreement for ionizing plasmas: ( 5 eV ⩽ T e ⩽ 60 eV , and 2 × 10 18 m − 3 ⩽ n e ⩽ 3 × 10 19 m − 3 ) in the case of majority helium plasmas, and ( 10 eV ⩽ T e ⩽ 40 eV , 2 × 10 18 m − 3 ⩽ n e ⩽ 3 × 10 19 m − 3 ) in the case of majority deuterium plasmas. However, there were instances where HeMSI measurements diverged from Thomson scattering. When T e ⩽ 10 eV in majority deuterium plasmas, HeMSI deduced inaccurately high values of T e . This disagreement cannot be rectified within the CRM’s EIE and EIR framework. Second, on sporadic occasions within the private flux region, HeMSI produced erroneously high measurements of n e . Multi-spectral imaging of Helium emission has been demonstrated to produce accurate 2D poloidal maps of T e and n e within the divertor of a tokamak for plasma conditions relevant to contemporary divertor studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Two-color x-ray free-electron laser by photocathode laser emittance spoiler

Multispectral x-ray pump-probe experiments call for synchronized two-color free-electron lasers (FEL). This mode often implies a laborious setup or an inefficient use of the undulator. We report on a simple and noninvasive approach tested at SwissFEL for a two-color x-ray delivering almost 60% of the pulse energy compared with a single color. In this new method, a ps UV pulse is overlapped to the photocathode drive laser increasing the beam emittance, which locally inhibits the FEL process. This scheme permits high-stability in energy and spectrum and the control of the two-color duration and intensity ratio. It enables shot-to-shot switching between one and two-color FEL and, since not associate to beam losses, it is compatible with high repetition-rate and high average-power FELs.

43 PARTICLE ACCELERATORS↗

Space-Time Quantum Metasurfaces

Metasurfaces have recently entered the realm of quantum photonics, enabling manipulation of quantum light using a compact nanophotonic platform. Realizing the full potential of metasurfaces at the deepest quantum level requires the ability to tune coherent light-matter interactions continuously in space and time. Here, we introduce the concept of space-time quantum metasurfaces for arbitrary control of the spectral, spatial, and spin properties of nonclassical light using a compact photonic platform. We show that space-time quantum metasurfaces allow on-demand tailoring of entanglement among all degrees of freedom of a single photon. We also show that spatiotemporal modulation induces asymmetry at the fundamental level of quantum fluctuations, resulting in the generation of steered and vortex photon pairs out of vacuum. Space-time quantum metasurfaces have the potential to enable novel photonic functionalities, such as encoding quantum information into high-dimensional color qudits using designer modulation protocols, sculpting multispectral and multispatial modes in spontaneous emission, and generating reconfigurable hyperentanglement for high-capacity quantum communications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splitting of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.

58 GEOSCIENCES↗

Cycle-Consistent Adversarial Networks for Realistic Pervasive Change Generation in Remote Sensing Imagery

This paper introduces a new method of generating realistic pervasive changes in the context of evaluating the effectiveness of change detection algorithms in controlled settings. The method - a cycle-consistent adversarial network (CycleGAN) - requires low quantities of training data to generate realistic changes. Here we show an application of CycleGAN in creating realistic snow-covered scenes of multispectral Sentinel-2 imagery, and demonstrate how these images can be used as a test bed for anomalous change detection algorithms.

97 MATHEMATICS AND COMPUTING↗

ColorMap ND : A Data-Driven Approach and Tool for Mapping Multivariate Data to Color

A wide variety of color schemes have been devised for mapping scalar data to color. We address the challenge of color-mapping multivariate data. While a number of methods can map low-dimensional data to color, for example, using bilinear or barycentric interpolation for two or three variables, these methods do not scale to higher data dimensions. Likewise, schemes that take a more artistic approach through color mixing and the like also face limits when it comes to the number of variables they can encode. Our approach does not have these limitations. It is data driven in that it determines a proper and consistent color map from first embedding the data samples into a circular interactive multivariate color mapping display (ICD) and then fusing this display with a convex (CIE HCL) color space. The variables (data attributes) are arranged in terms of their similarity and mapped to the ICD’s boundary to control the embedding. Using this layout, the color of a multivariate data sample is then obtained via modified generalized barycentric coordinate interpolation of the map. In conclusion, the system we devised has facilities for contrast and feature enhancement, supports both regular and irregular grids, can deal with multi-field as well as multispectral data, and can produce heat maps, choropleth maps, and diagrams such as scatterplots.

97 MATHEMATICS AND COMPUTING↗

Beyond the visible: Accounting for ultraviolet and far‐red radiation in vegetation productivity and surface energy budgets

Photosynthetically active radiation (PAR) is typically defined as light with a wavelength within 400–700 nm. However, ultra-violet (UV) radiation within 280–400 nm and far-red (FR) radiation within 700–750 nm can also excite photosystems, though not as efficiently as PAR. Vegetation and land surface models (LSMs) typically do not explicitly account for UV's contribution to energy budgets or photosynthesis, nor FR's contribution to photosynthesis. However, whether neglecting UV and FR has significant impacts remains unknown. Here, we explored how canopy radiative transfer (RT) and photosynthesis are impacted when explicitly implementing UV in the canopy RT model and accounting for UV and FR in the photosynthesis models within a next-generation LSM that can simulate hyperspectral canopy RT. We validated our improvements using photosynthesis measurements from plants under different light sources and intensities and surface reflection from an eddy-covariance tower. Our model simulations suggested that at the whole plant level, after accounting for UV and FR explicitly, chlorophyll content, leaf area index (LAI), clumping index, and solar radiation all impact the modeling of gross primary productivity (GPP). At the global scale, mean annual GPP within a grid would increase by up to 7.3% and the increase is proportional to LAI; globally integrated GPP increases by 4.6 PgC year −1 (3.8% of the GPP without accounting for UV + FR). Further, using PAR to proxy UV could overestimate surface albedo by more than 0.1, particularly in the boreal forests. Our results highlight the importance of improving UV and FR in canopy RT and photosynthesis modeling and the necessity to implement hyperspectral or multispectral canopy RT schemes in future vegetation and LSMs.

energy budget↗

Artificial illumination identification from an unmanned aerial vehicle

Artificial illumination identification within images is a useful tool for many applications. Performing such identification allows for an estimation of the illumination source spectrum, which in turn can be used for additional applications ranging from spectral detection and exploitation to statistics about nighttime light usage. Illumination identification has been performed in laboratory settings but not from an unmanned aerial vehicle (UAV) platform. Here, we test the feasibility of using a UAV and commercial off-the-shelf multispectral imaging sensor to perform such artificial illumination identification through linear discriminant analysis using nighttime UAV images. The results are very promising, showing source classification accuracies of 83.3%, 92.3%, 100%, and 100% for the incandescent, light-emitting diode, high pressure sodium, and metal halide illumination sources, respectively. We show that the information gained from the source identification can be further used to inform additional analysis, such as spectral identification. The high resolution of UAV imaging techniques combined with the knowledge of the illumination source can lead to better exploitation of such nighttime data for many applications.

42 ENGINEERING↗

Remote-sensing application for facilitating land resource assessment and monitoring for utility-scale solar energy development

A monitoring plan that incorporates regional datasets and integrates cost-effective data collection methods is necessary to sustain the long-term environmental monitoring of utility-scale solar energy development in expansive, environmentally sensitive desert environments. Using very high spatial resolution (VHSR; 15 cm) multispectral imagery collected in November 2012 and January 2014, an image processing routine was developed to characterize ephemeral streams, vegetation, and land surface in the southwestern United States where increased utility-scale solar development is anticipated. In addition to knowledge about desert landscapes, the methodology integrates existing spectral indices and transformation (e.g., visible atmospherically resistant index and principal components); a newly developed index, erosion resistance index (ERI); and digital terrain and surface models, all of which were derived from a common VHSR image. The methodology identified fine-scale ephemeral streams with greater detail than the National Hydrography Dataset and accurately estimated vegetation distribution and fractional cover of various surface types. The ERI classified surface types that have a range of erosive potentials. The remote-sensing methodology could ultimately reduce uncertainty and monitoring costs for all stakeholders by providing a cost-effective monitoring approach that accurately characterizes the land resources at potential development sites.

Desert regions↗

Intensity offset and correction of solid spectral library samples measured behind glass

Accurate and calibrated diffuse reflectance spectra libraries of solids are becoming more important for hyperspectral and multispectral remote sensing exploitation. Many solids are in the form of powders or granules and in order to measure their diffuse reflectance spectra in the laboratory, it is often necessary to place the samples behind a transparent medium such as glass or quartz for the UV, visible or near-infrared spectral regions to prevent their unwanted dispersal into the instrument or laboratory environment. Using both experimental and theoretical methods we have found that for the case of fused quartz this leads to an intensity offset in the reflectance values. Although expected dispersive effects were observed for the fused quartz window in the UV, the measured hemispherical reflectance values are predominantly vertically shifted by the reflectance from the air-quartz and sample-quartz interfaces with intensity dependent offsets leading to measured values up to nearly 6% too high for a 2% reflectance surface, 3.8% too high for 10% reflecting materials, approximately correct (to within experimental error) for 40% to 60% diffuse reflecting surfaces, and 2% too low for 99% reflecting Spectralon surfaces. For the diffuse reflectance case, the measured values are uniformly too low due to the glass, with differences nearly 6% too high for reflectance values approaching 99%. The deviations arise from the added reflections from the quartz surfaces as verified by theory, modeling and experiment. Empirical correction factors were implemented into post-processing software to redress the artifact for hemispherical and diffuse reflectance data across the 300 nm to 2300 nm range.

36 MATERIALS SCIENCE↗

Subwavelength resonant nanostructured films for sensing

We present a novel subwavelength nanostructure architecture that may be utilized for optical standoff sensing applications. The subwavelength structures are fabricated via a combination of nanoimprint lithography and metal sputtering to create metallic nanostructured films encased within a transparent media. The structures are based on the open ring resonator (ORR) architecture and have their analog in resonant LC circuits, which display a resonance frequency that is inversely proportional to the square root of the product of the inductance and capacitance. Therefore, any perturbation of the nanostructured films due to chemical or environmental effects can alter the inductive or capacitive behavior of the subwavelength features, which can shift the resonant frequency and provide an indication of the external stimulus. This shift in resonance can be interrogated remotely either actively using either laser illumination or passively using hyperspectral or multispectral sensing. These structures may be designed to be either anisotropic or isotropic, which can also provide polarization-sensitive interrogation. Due to the nanometer-scale of the structures, they can be tailored to be optically responsive in the visible or near infrared spectrum with a highly reflective resonant peak that is dependent solely on structural dimensions and material characteristics. We present experimental measurements of the optical response of these structures as a function of wavelength, polarization, and incident angle demonstrating the resonant effect in the near infrared region. Numerical modeling data showing the effect of different fabrication parameters such as structure parameters are also discussed.

Environmental Molecular Sciences Laboratory↗

Subwavelength films for standoff radiation dosimetry

We present optical subwavelength nanostructure architecture suitable for standoff radiation dosimetry with remote optical readout in the visible or infrared spectral regions. To achieve this, films of subwavelength structures are fabricated over several square inches via the creation of a 2D non-close packed (NCP) array template of radiation-sensitive polymeric nanoparticles, followed by magnetron sputtering of a metallic coating to form a 2D array of separated hemispherical nanoscale metallic shells. The nanoshells are highly reflective at resonance in the visible or infrared depending on design. These structures and their behavior are based on the open ring resonator (ORR) architecture and have their analog in resonant inductive-capacitive (LC) circuits, which display a resonance wavelength that is inversely proportional to the square root of the product of the inductance and capacitance. Therefore, any modification of the nanostructure material properties due to radiation alters the inductive or capacitive behavior of the subwavelength features, which in turn changes their optical properties resulting in a shift in the optical resonance. This shift in resonance may be remotely interrogated actively using either laser illumination or passively by hyperspectral or multispectral sensing with broadband illumination. These structures may be designed to be either anisotropic or isotropic, which can also offer polarization-sensitive interrogation. We present experimental measurements of a radiation induced shift in the optical resonance of a subwavelength film after exposure to an absorbed dose of gamma radiation from 2 Mrad up to 62 Mrad demonstrating the effect. Interestingly the resonance shift is non-monotonic for this material system and possible radiation damage mechanisms to the nanoparticles are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing

Compressive sensing (CS) is a method of sampling which permits some classes of signals to be reconstructed with high accuracy even when they were sampled at sub-Nyquist rates. In this paper we explore a phenomenon in which bandwise CS sampling of a hyperspectral data cube followed by reconstruction can actually result in amplification of chemical signals contained in the cube. Perhaps most surprisingly, chemical signal amplification generally seems to increase as the level of sampling decreases. In some examples, the chemical signal is significantly stronger in a data cube reconstructed from 10% CS sampling than it is in the raw, 100% sampled data cube. We explore this phenomenon in two real-world datasets including the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset and the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset. Each of these datasets contains the release of a chemical simulant, such as glacial acetic acid, triethyl phospate, and sulfur hexafluoride, and in all cases we use the adaptive coherence estimator (ACE) to detect a target signal in the hyperspectral data cube. We end the paper by suggesting some theoretical justifications for why chemical signals would be amplified in CS sampled and reconstructed hyperspectral data cubes and discuss some practical implications.

Hyperspectral imagery, Compressive Sensing, single↗

A data-driven approach to sampling matrix selection for compressive sensing

Sampling is a fundamental aspect of any implementation of compressive sensing. Typically, the choice of sampling method is guided by the reconstruction basis. However, this approach can be problematic with respect to certain hardware constraints and is not responsive to domain-specific context. We propose a method for defining an order for a sampling basis that is optimal with respect to capturing variance in data, thus allowing for meaningful sensing at any desired level of compression. We focus on the Walsh-Hadamard sampling basis for its relevance to hardware constraints, but our approach applies to any sampling basis of interest. We illustrate the effectiveness of our method on the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset, the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset, and a Colorado State University Swiss Ranger depth image dataset. The spectral datasets consist of simulant experiments, including releases of chemicals such as GAA and SF6. We combine our sampling and reconstruction with the adaptive coherence estimator (ACE) and bulk coherence for chemical detection and we incorporate an algorithmic threshold for ACE values to determine the presence or absence of a chemical. We compare results across sampling methods in this context. We have successful chemical detection at a compression rate of 90%. For all three datasets, we compare our sampling approach to standard orderings of sampling basis such as random, sequency, and an analog of sequency that we term `frequency.' In one instance, the peak signal to noise ratio was improved by over 30% across a test set of depth images.

compressive sensing, hyperspectral imaging, Walsh-↗

SU-E-T-20: A Novel Hybrid CBCT, Bioluminescence and Fluorescence Tomography System for Preclinical Radiation Research

Purpose: A novel standalone bioluminescence and fluorescence tomography (BLT and FT) system equipped with high resolution CBCT has been built in our group. In this work, we present the system calibration method and validate our system in both phantom and in vivo environment. Methods: The CBCT is acquired by rotating the animal stage while keeping the x-ray source and detector panel static. The optical signal is reflected by the 3-mirror system to a multispectral filter set and then delivered to the CCD camera with f/1.4 lens mounted. Nine fibers passing through the stage and in contact with the mouse skin serve as the light sources for diffuse optical tomography (DOT) and FT. The anatomical information and optical properties acquired from the CBCT and DOT, respectively, are used as the priori information to improve the BLT/FT reconstruction accuracy. Flat field correction for the optical system was acquired at multiple wavelengths. A home-built phantom is used to register the optical and CBCT coordinates. An absolute calibration relating the CCD photon counts rate to the light fluence rate emitted at animal surface was developed to quantify the bioluminescence power or fluorophore concentration. Results: An optical inhomogeneous phantom with 2 light sources (3mm separation) imbedded is used to test the system. The optical signal is mapped onto the mesh generated from CBCT for optical reconstruction. Our preliminary results show that the center of mass can be reconstructed within 2.8mm accuracy. A live mouse with the light source imbedded is also used to validate our system. Liver or lung metastatic luminescence tumor model will be used for further testing. Conclusion: This hybrid system transforms preclinical research to a level that even sub-palpable volume of cells can be imaged rapidly and non-invasively, which largely extends the scope of radiobiological research. The research is supported by the NCI grant R01CA158100-01.

60 APPLIED LIFE SCIENCES↗