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At least 325 records · Page 18

Depth Thermography: Noninvasive 3D Temperature Profiling Using Infrared Thermal Emission

Here, we introduce a technique based on infrared thermal emission, termed depth thermography, that can remotely measure the temperature distribution beneath the surface of certain objects. Depth thermography utilizes the thermal-emission spectrum in the semitransparent spectral region of the target object to extract its temperature as a function of depth, in contrast with conventional thermography, which uses the spectrally integrated thermally emitted power to measure the surface temperature. Coupled with two-dimensional imaging, for example using an infrared hyperspectral camera or scanning a single-pixel spectrometer, this technique can yield volumetric temperature distributions. Furthermore, we carried out a proof-of-concept experiment on an asymmetrically heated fused-silica window, extracting the temperature distribution throughout the sample. Depth thermography may enable noncontact volumetric temperature measurements of microscopic objects such as multilayer electronic devices or macroscopic volumes of liquids and gases, as well as simultaneous all-optical measurements of optical and thermal properties of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FTIR imaging identifies alterations in lung tissue structure and biochemical composition in human idiopathic pulmonary fibrosis

Idiopathic Pulmonary Fibrosis (IPF) is a chronic, progressive, and fatal lung disease characterized by damage to the epithelial tissue and a reduced ability of the alveoli to repair themselves. This impaired repair process leads to abnormal accumulation of extracellular matrix (ECM), resulting in scarring and stiffening of lung tissue. Fourier transform infrared imaging (FTIRI) is a promising technique for imaging the biochemical changes related to fibrotic changes in a label-free and non-destructive manner, which can be analyzed to mark the progression of IPF. In this study, FTIRI was used to image human lung tissue biopsies with IPF and control biopsies without disease. In-depth spectral analyses were performed to observe the biochemical changes in the tissue composition using FTIRI. The parameters that were analyzed included collagen structure, total lipid content, lipid chain length, and phospholipids. Results showed a significant increase in lipid content in IPF compared to control, where long chain lipids dominated and phospholipids were reduced. Minor changes in collagen structure were also observed in IPF, likely attributed to the excess formation of extracellular matrix in the disease. These findings indicate that FTIRI has the potential to be a promising diagnostic technique to understand the molecular changes during IPF, as analysis of infrared data can reveal detailed biochemical information regarding disease progression and provide spatial insights on the molecular changes across the IPF lung tissue.

59 BASIC BIOLOGICAL SCIENCES↗

Simultaneous imaging of two-phase velocities in particle-laden flows by two-color optical phase discrimination

In this Letter, we present a particle image/tracking velocimetry (PIV/PTV) technique for simultaneous velocity measurement of both fluid and particle phases, adopting newly developed optical phase discrimination methods and novel optical particles. Spherical acrylic (PMMA) particles of diameter ∼ <#comment/> O ( 100 µ <#comment/> m ) were used as the particle phase, while fine B A M : E u 2 + phosphors of diameter ∼ <#comment/> O ( 1 µ <#comment/> m ) were used as the fluid tracer. Under Nd:YAG 355 nm laser excitation, both the laser-induced fluorescence (LIF) from PMMA and laser-induced phosphorescence (LIP) from B A M : E u 2 + provided sufficiently strong signals for PIV imaging with two non-intensified cameras and were clearly separable for phase discrimination using spectral filters and temporal profiles. The advantages of the PIV/PTV method include the relatively low cost of B A M : E u 2 + phosphors, high sphericity and narrow size distribution of PMMA particles with LIF emission, and direct optical discrimination eliminating artifacts, while requiring much less computational capacity for PIV/PTV processing of complex particle-laden flows.

Bi, Xiaopeng (ORCID:0000000190847325)↗

Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum

Unmanned aerial vehicle (UAV)-based remote sensing is gaining momentum in a variety of agricultural and environmental applications. Very-high-resolution remote sensing image sets collected repeatedly throughout a crop growing season are becoming increasingly common. Analytical methods able to learn from both spatial and time dimensions of the data may allow for an improved estimation of crop traits, as well as the effects of genetics and the environment on these traits. Multispectral and geometric time series imagery was collected by UAV on 11 dates, along with ground-truth data, in a field trial of 866 genetically diverse biomass sorghum accessions. We compared the performance of Convolution Neural Network (CNN) architectures that used image data from single dates (two spatial dimensions, 2D) versus multiple dates (two spatial dimensions + temporal dimension, 3D) to estimate lodging detection and severity. Lodging was detected with 3D-CNN analysis of time series imagery with 0.88 accuracy, 0.92 Precision, and 0.83 Recall. This outperformed the best 2D-CNN on a single date with 0.85 accuracy, 0.84 Precision, and 0.76 Recall. The variation in lodging severity was estimated by the best 3D-CNN analysis with 9.4% mean absolute error (MAE), 11.9% root mean square error (RMSE), and goodness-of-fit (R2) of 0.76. This was a significant improvement over the best 2D-CNN analysis with 11.84% MAE, 14.91% RMSE, and 0.63 R2. The success of the improved 3D-CNN analysis approach depended on the inclusion of “before and after” data, i.e., images collected on dates before and after the lodging event. The integration of geometric and spectral features with 3D-CNN architecture was also key to the improved assessment of lodging severity, which is an important and difficult-to-assess phenomenon in bioenergy feedstocks such as biomass sorghum. This demonstrates that spatio-temporal CNN architectures based on UAV time series imagery have significant potential to enhance plant phenotyping capabilities in crop breeding and Precision agriculture applications.

3D-convolution neural networks↗

Catalog of Planetary Nebulae Detected by GALEX and Corollary Optical Surveys

Planetary nebulae (PNs) consist of an ionized envelope surrounding a hot central star (CSPN) that emits mostly at ultraviolet (UV) wavelengths. UV observations, therefore, provide important information on both the CSPN and the nebula. We have matched the PNs in the Hong Kong/Australian Astronomical Observatory/Strasbourg Hα catalog with the Galaxy Evolution Explorer (GALEX) UV sky surveys, the Sloan Digital Sky Survey (SDSS) data release 16, and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) PS1 second release. A total of 671 PNs were observed by GALEX with the far-UV (FUV; 1344 Å–1786 Å) and/or the near-UV (NUV; 1771 Å–2831 Å) detectors on (GUVPNcat); 83 were observed by SDSS (PNcatxSDSSDR16) and 1819 by Pan-STARRS (PNcatxPS1MDS). We merged a distilled version of these matched catalogs into GUVPNcatxSDSSDR16xPS1MDS, which contains a total of 375 PNs with both UV and optical photometry over a total spectral coverage of ~1540 Å–9610 Å. We analyzed separately 170 PNs resolved in GALEX images and determined their UV radius by applying a flux profile analysis. The CSPN flux could be extracted separately from the PN emission for 8 and 50 objects with SDSS and Pan-STARRS counterparts, respectively. The multiband photometry was used to distinguish between compact and extended PNs and CSPNs (binary CSPNs) by color–color diagram analysis. We found that compact PN candidates could be identified by using the r - i < - 0.4 and -1 < FUV-NUV < 1 colors, whereas binary CSPN candidates in given T eff ranges (all with color r-i > -0.4) can be identified in the color region (FUV-NUV) ≤ 6(r-i)+1.3, -0.8 < FUV-NUV < 0.4, and r-i < 0.75.

79 ASTRONOMY AND ASTROPHYSICS↗

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data

Remote sensing data collected from Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group. Data was collected from a single flight over the Kougarok hillslope site on 26 July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model. Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. This dataset includes *.pdf, *.txt, *.tif, *.dat, and *.csv with most zipped in *.tar.gz files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Thermal images collected during large-scale 3D printing with Ingersoll MasterPrint

This data set contains images produced to test the performance of anomaly and fault detection methods in the context of additive manufacturing. Two print jobs were executed using the Ingersoll MasterPrint with the Model 30 Strangpresse extruder. The material used was Techmer compounded polylactic acid (PLA) with wood flour as a filler (80/20 PLA/WF by weight). The first print job consists of the 3D printing of a hexagonal cylinder with a two-bead wall. This print was sliced at a gantry velocity of 3000 millimeter per minute, and an extruder screw speed of 68.14 rotations per minute. This are considered the normal operating conditions. A second hexagonal cylinder was printed using a reduced extruder screw speed, 15% lower than under normal operating conditions. The images were collected with a Teledyne FLIR Lepton 3.5 infra-red camera, a small form factor radiometric long-wave infrared camera with a spectral range of 8 µm to 14 µm. Sensor resolution was 160x120 pixels, with a pixel size of 12 µm, a temperature range of -10 - 450°C, and an accuracy of +/- 10°C in its low gain configuration. Images in this data set were collected with cameras oriented at the printer nozzle. The nozzle camera setup consisted of two cameras located 12.5cm from the nozzle center. These were mounted directly to the print head, so that the camera positions relative to the print direction would remain constant as it rotated around its C-axis to follow the print path. One camera was placed ahead of the nozzle to capture the previous layer immediately before being covered by the new layer of material, while the second camera was placed behind the nozzle and captured the freshly extruded bead. Images are collecting during each phase of the print: (a) idle (i.e., no material deposited), (b) extrusion (i.e., to prime the extruder), and (c) printing (deposition of material to manufacture the hexagonal cylinder).

36 MATERIALS SCIENCE↗

2D coherence imaging measurements of C 2+ ion temperatures in the divertor of Wendelstein 7-X

For the first time, 2D ion temperature values are derived from coherence imaging spectroscopy (CIS) fringe contrast measurements by taking Zeeman line broadening effects into account during the analysis procedure of a spatial-heterodyne CIS instrument. This allowed 2D images of C 2+ ion temperatures (T i ) across the 3D-shaped island divertor of the Wendelstein 7-X stellarator. Ion temperatures ranging from 10 to 20 eV are observed for the C 2+ impurity species in the region above the divertor targets. During the transition from the attached to the detached plasma state, the C 2+ radiation zone moves from close to the divertor target towards the last closed flux surface. Within this radiation zone, C 2+ temperature does not decrease significantly. Experimentally, the coherence imaging measurements were cross-calibrated at one poloidal cross-section using a high resolution Echelle spectrometer, that shared its sightlines with the coherence imaging diagnostic. The spectra demonstrated that, apart from Doppler broadening, the Zeeman effect significantly contributes to the spectral line broadening and cannot be neglected when analyzing the CIS contrast data for T i extraction in the edge and scrape-off-layer of Wendelstein 7-X (W7-X), due to the relatively low temperatures (T i < 100 eV) and high magnetic fields (B ≈ 2.5 T).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Closer Look at Corrugated Au Tips

A series of optical and electron microscopies are utilized in concert to unravel the structural, optical, and plasmonic properties of corrugated metallic tips. While the overall microscopic shapes of the tips dictate their optical resonances and plasmonic field enhancement factors, nanometric structural details govern their tip-enhanced Raman (TER) spectra and images. Using 4-thiobenzonitrile (TBN) as a molecular reporter, spatially resolved TER spectra reveal that optical rectification and molecular charging are among the prominent observables in the tip-tip TER geometry. The comparisons we provide reinforce the complexity of what otherwise may be regarded as sharp tip probes. We show the spurious appearance of anions is driven by highly localized resonances that appear as a result of surface corrugation and their manifestation throughout the course of TER nano-spectroscopy complicates spectral assignments, particularly in works aimed at understanding plasmon-enhanced/induced chemical transformations through enhanced Raman spectroscopy and imaging. Overall, nanoscale spatial variations in the TERS spectra suggest that the tip-tip geometry sustains junction plasmons that appear very different from what may be expected from the hybridization of the bulk tip resonances.

Bhattarai, Ashish↗

Infrared Imaging Using Thermally Stable HgTe/CdS Nanocrystals

Transferring nanocrystals (NCs) from the laboratory environment toward practical applications has raised new challenges. HgTe appears as the most spectrally tunable infrared colloidal platform. Its low-temperature synthesis reduces the growth energy cost yet also favors sintering. Once coupled to a read-out circuit, the Joule effect aggregates the particles, leading to a poorly defined optical edge and large dark current. Here, in this study, we demonstrate that CdS shells bring the expected thermal stability (no redshift upon annealing, reduced tendency to form amalgams, and preservation of photoconduction after an atomic layer deposition process). The electronic structure of these confined particles is unveiled using k.p self-consistent simulations showing a significant exciton binding energy of ~ 200 meV. After shelling, the material displays a p-type behavior that favors the generation of photoconductive gain. The latter is then used to increase the external quantum efficiency of an infrared imager, which now reaches 40% while presenting long-term stability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Beyond green with synthetic chlorophylls – Connecting structural features with spectral properties

The distinct features of chlorophylls in photosynthesis have led to the formation of numerous derivatives for applications encompassing solar energy conversion, molecular photonics, photodynamic therapy, and molecular imaging. Synthetic chlorins created de novo and bearing a geminal dimethyl group in the reduced ring have proved invaluable for fundamental studies. Four decades of research have led to accumulation of tabulated spectra for > 400 such synthetic chlorins with distinct structural frameworks (17-oxochlorins, 13 1 -oxophorbines, chlorinimides) and substituents (alkyl, aryl, ethynyl, phenylethynyl, acetyl, formyl) located at specific (meso, β) positions. In this review, spectral traces (324 absorption, 247 fluorescence) are assembled along with photophysical data including the molar absorption coefficient (ε), fluorescence quantum yield (Φ f ) and singlet excited-state lifetime (τ s ). The review uses the accumulated spectral data derived from chlorins all containing a uniform molecular scaffold to (1) highlight the effects of molecular structure on spectral features, and (2) identify trends including how ε, Φ f and τ s vary with wavelength and other features. Use of a common geminal-dimethyl-substituted chlorin scaffold – beginning with no substituents, to one substituent at designated sites, and to 2 or more substituents – provides a systematic Aufbau approach for understanding the absorption spectra of chlorins on a path to and beyond the native chlorophylls. Finally, the review provides insights concerning the rational design of potent analogues of Nature’s preeminent red-region absorbers for potential utilization in diverse applications and is aimed at multiple audiences: those interested in spectral properties, tetrapyrrole photophysics, and the molecular design of new chromophores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗

Delivering Robust Proton-Only Sensing of Hyperpolarized [1,2- 13 C 2 ]-Pyruvate Using Broad-Spectral-Range Nuclear Magnetic Resonance Pulse Sequences

Hyperpolarized [1- 13 C]pyruvate is the leading hyperpolarized injectable contrast agent and is currently under evaluation in clinical trials for molecular imaging of metabolic diseases, including cardiovascular disease and cancer. One aspect limiting broad scalability of the technique is that hyperpolarized 13 C MRI requires specialized 13 C hardware and software that are not generally available on clinical MRI scanners, which employ proton-only detection. Here, we present an approach that uses pulse sequences to transfer 13 C hyperpolarization to methyl protons for detection of the 13 C– 13 C pyruvate singlet, employing proton-only excitation and detection only. The new pulse sequences are robust to the B 1 and B 0 magnetic field inhomogeneities. The work focuses on singlet-to-magnetization (S2M) and rotor-synchronized (R) pulses, both relying on trains of hard pulses with broad spectral width coverage designed to effectively transform hyperpolarized 13 C 2 -singlet hyperpolarization to 1 H polarization on the CH 3 group of [1,2- 13 C 2 ]pyruvate. Finally, this approach may enable a broader adoption of hyperpolarized MRI as a molecular imaging technique.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-delay coherence imaging spectroscopy optimized for ion temperature measurements in the divertor plasma of the Wendelstein 7-X stellarator

A new coherence imaging spectroscopy (CIS) diagnostic optimized to measure the C 2+ impurity ion temperature T i spatial distribution in the divertor plasma of the W7-X stellarator is designed, tested, and validated. Using CIS to obtain T i in the edge of magnetically confined plasmas has historically been challenging because Doppler broadening and Zeeman splitting have comparable effects on the shape of spectral emission lines. To distinguish between these two mechanisms, a novel approach to birefringent crystal design is employed to minimize the diagnostic’s sensitivity to Zeeman splitting. The recently developed pixelated multi-delay CIS approach is also used to obtain four times as much spectral information as traditional CIS approaches. The T i -optimized CIS diagnostic is validated in a long-pulse W7-X plasma by comparison with a high-resolution spectrometer whose sightlines overlap with the CIS field of view. The CIS and spectrometer T i profiles have the same shape and agree to within 10% on average and 25% in the worst case. Images of the T i distribution near the divertor show toroidally elongated bands aligned with the magnetic field, with T i ranging between 10 and 40 eV.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Host Star Metallicity of Directly Imaged Wide-orbit Planets: Implications for Planet Formation

Directly imaged planets (DIPs) are self-luminous companions of pre-main-sequence and young main-sequence stars. They reside in wider orbits (∼tens to thousands of astronomical units) and generally are more massive compared to the close-in (≲10 au) planets. Determining the host star properties of these outstretched planetary systems is important to understand and discern various planet formation and evolution scenarios. We present the stellar parameters and metallicity ([Fe/H]) for a subsample of 18 stars known to host planets discovered by the direct imaging technique. We retrieved the high-resolution spectra for these stars from public archives and used the synthetic spectral fitting technique and Bayesian analysis to determine the stellar properties in a uniform and consistent way. For eight sources, the metallicities are reported for the first time, while the results are consistent with the previous estimates for the other sources. Our analysis shows that metallicities of stars hosting DIPs are close to solar with a mean [Fe/H] = −0.04 ± 0.27 dex. The large scatter in metallicity suggests that a metal-rich environment may not be necessary to form massive planets at large orbital distances. We also find that the planet mass–host star metallicity relation for the directly imaged massive planets in wide orbits is very similar to that found for the well-studied population of short-period (≲1 yr) super-Jupiters and brown dwarfs around main-sequence stars.

36 MATERIALS SCIENCE↗

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗

Tailoring spectral properties for entangled photon generation

The linear intensity scaling of entangled two-photon absorption (ETPA) offers a fundamental mechanism to enable nonlinear optical spectroscopy and microscopy under a substantially lower excitation power than is currently feasible. However, the long data acquisition time and low signal-to-noise ratio in reported ETPA-based spectroscopic and microscopic studies prevent its widespread application. To gain the full potential of this novel quantum light approach, it is essential to optimize entangled photon generation for significantly enhanced ETPA responses. Here, we report a new quantum light source by combining entangled photon generation with free-space femtosecond pump-pulse shaping. Here, through measurements of singles and coincidence counts by varying the patterns applied to a spatial light modulator to control the spectral widths of the pump pulses, we reveal strong dependence of the singles and coincidence count rates as well as their ratios on the spectral widths of pump pulses. An optimal spectral width for the highest ratios between the coincidence photon and the signal or idler photon count rates is also determined. Identification of such optimal spectral widths for entangled photon generation in the presence of postgeneration spectral selection makes this quantum light source a promising choice for ETPA-based spectroscopy and imaging.

Photon pairs & parametric down-conversion↗

Mapping Geothermal Indicator Minerals Using Fusion of Target Detection Algorithms

Mineral mapping from satellite images provides valuable insights into subsurface mineral alteration for geothermal exploration. In previous studies, eight fundamental algorithms were used for mineral mapping utilizing USGS spectra, a collection of reflectance spectra containing samples of minerals, rocks, and soils created by the USGS. We used an ASD FieldSpec 4 Hi-RES NG portable spectrometer to collect spectra for analyzing ASTER images of the Coso Geothermal Field. Then, we established the ground-truth information and the spectral library by analyzing 97 samples. Samples collected from the field were analyzed using the CSIRO TSG (The Spectral Geologist of the Commonwealth Scientific and Industrial Research Organization). Based on the mineralogy study, multiple high-purity spectra of geothermal alteration minerals were selected from collected data, including alunite, chalcedony, hematite, kaolinite, and opal. Eight mineral spectral target detection algorithms were applied to the preprocessed satellite data with a proposed local spectral library. We measured the highest overall accuracy of 87% for alunite, 95% for opal, 83% for chalcedony, 60% for hematite, and 96% for kaolinite out of these eight algorithms. Three, four, five, and eight algorithms were fused to extract mineral alteration with the obtained target detection results. The results prove that the fusion of algorithms gives better results than using individual ones. In conclusion, this paper discusses the significance of evaluating different mapping algorithms. It proposes a robust fusion approach to extract mineral maps as an indicator for geothermal exploration.

Cavur, Mahmut↗