High Spectral Resolution Research Articles

The first ground-based detection of the 752 GHz water line in local ultra-luminous infrared galaxies using APEX-SEPIA

Abstract We report the first ground-based detection of the water line p-H2O (211–202) at 752.033 GHz in three z < 0.08 ultra-luminous infrared galaxies (ULIRGs): IRAS 06035-7102, IRAS 17207-0014 and IRAS 09022-3615. Using the Atacama Pathfinder EXperiment (APEX), with its Swedish-ESO PI Instrument for APEX (SEPIA) band-9 receiver, we detect this H2O line with overall signal-to-noise ratios of 8–10 in all three galaxies. Notably, this is the first detection of this line in IRAS 06035-7102. Our new APEX-measured fluxes, between 145 to 705 Jy km s−1, are compared with previous values taken from Herschel SPIRE FTS. We highlight the great capabilities of APEX for resolving the H2O line profiles with high spectral resolutions while also improving by a factor of two the significance of the detection within moderate integration times. While exploring the correlation between the p-H2O(211–202) and the total infrared luminosity, our galaxies are found to follow the trend at the bright end of the local ULIRG’s distribution. The p-H2O(211–202) line spectra are compared to the mid-J CO and HCN spectra, and dust continuum previously observed with ALMA. In the complex interacting system IRAS 09022-3615, the profile of the water emission line is offset in velocity with respect to the ALMA CO(J = 4 − 3) emission. For IRAS 17207-0014 and IRAS 06035-7102, the profiles between the water line and the CO lines are spectroscopically aligned. This pilot study demonstrates the feasibility of directly conducting ground-based high-frequency observations of this key water line, opening the possibility of detailed follow-up campaigns to tackle its nature.

Refining Photothermal Deflection Spectroscopy: Incorporating Reflectance for Enhanced Accuracy in Light‐Absorption Measurements

A method for measuring light absorption using photothermal deflection spectroscopy (PDS) is investigated. Typical reflectance and transmittance (R & T) absorption measurements have low spectral resolution (SR) with standard setups. It is believed that absorption measurements using PDS solve this problem because of its high sensitivity, even at a high SR. However, accurate absorption measurements have not been obtained using conventional PDS. The reflectance of the sample must be considered in the absorptance calculations. Various absorption measurement methods are compared and a novel calculation method for accurate PDS absorption measurements is proposed. A sample with quantum structures is fabricated and PDS measurements are performed. Exciton absorption peaks are also observed. The high SR of PDS is demonstrated and the measured exciton absorption peaks are confirmed using piezoelectric photothermal measurements. Furthermore, it is confirmed that the absolute values of absorptance derived from the R & T and PDS measurements agree well. The new PDS absorption measurement technique enables to obtain accurate absorption characteristics, which are indispensable for designing and optimizing optoelectronic devices.

Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network

Accurate and up-to-date crop-type maps are essential for efficient management and well-informed decision-making, allowing accurate planning and execution of agricultural operations in the horticultural sector. The assessment of crop-related traits, such as the spatiotemporal variability of phenology, can improve decision-making. The study aimed to extract phenological information from Sentinel-2 data to identify and distinguish between fruit trees and co-existing land use types on subtropical farms in Levubu, South Africa. However, the heterogeneity and complexity of the study area—composed of smallholder mixed cropping systems with overlapping spectra—constituted an obstacle to the application of optical pixel-based classification using machine learning (ML) classifiers. Given the socio-economic importance of fruit tree crops, the research sought to map the phenological dynamics of these crops using deep neural network (DNN) and optical Sentinel-2 data. The models were optimized to determine the best hyperparameters to achieve the best classification results. The classification results showed the maximum overall accuracies of 86.96%, 88.64%, 86.76%, and 87.25% for the April, May, June, and July images, respectively. The results demonstrate the potential of temporal phenological optical-based data in mapping fruit tree crops under different management systems. The availability of remotely sensed data with high spatial and spectral resolutions makes it possible to use deep learning models to support decision-making in agriculture. This creates new possibilities for deep learning to revolutionize and facilitate innovation within smart horticulture.

Prospects for detecting the circum- and intergalactic medium in X-ray absorption using the extended intracluster medium as a backlight

ABSTRACT The warm-hot plasma in cosmic web filaments is thought to comprise a large fraction of the gas in the local Universe. So far, the search for this gas has focused on mapping its emission, or detecting its absorption signatures against bright, point-like sources. Future, non-dispersive, high-spectral resolution X-ray detectors will, for the first time, enable absorption studies against extended objects. Here, we use the Hydrangea cosmological hydrodynamical simulations to predict the expected properties of intergalactic gas in and around massive galaxy clusters, and investigate the prospects of detecting it in absorption against the bright cores of nearby, massive, relaxed galaxy clusters. We probed a total of 138 projections from the simulation volumes, finding 16 directions with a total column density $N_{{\rm O\, {\small VII}}} > 10^{14.5}$ cm−2. The strongest absorbers are typically shifted by ±1000 km s−1 with respect to the rest frame of the cluster they are nearest to. Realistic mock observations with future micro-calorimeters, such as the Athena X-ray Integral Field Unit or the proposed Line Emission Mapper (LEM) X-ray probe, show that the detection of cosmic web filaments in ${\rm O\, {\small VII}}$ and ${\rm O\, {\small VIII}}$ absorption against galaxy cluster cores will be feasible. An ${\rm O\, {\small VII}}$ detection with a 5σ significance can be achieved in 10–250 ks with Athena for most of the galaxy clusters considered. The ${\rm O\, {\small VIII}}$ detection becomes feasible only with a spectral resolution of around 1 eV, comparable to that envisioned for LEM.

Quantitative Analysis of Meteorite Elements Based on the Multidimensional Scaling–Back Propagation Neural Network Algorithm Combined with Raman Mapping-Assisted Micro-Laser Induced Breakdown Spectroscopy

Meteorites are an essential reference for human exploration of the universe and its cosmic evolution and an essential research object for searching for extraterrestrial life. Ways to quickly identify and screen suspected meteorite samples have become the foundation and prerequisite for research on high-value meteorite samples. Therefore, this paper proposes a Raman mapping-assisted micro-laser induced breakdown spectroscopy (micro-LIBS) technology for field detection of suspected meteorite material composition without sample pre-processing, with a high detection speed and cost-effectiveness, to realize the detection of element composition and molecular structure. Raman mapping carries out multispectral imaging with high spectral resolution of the region of interest. The fusion of Raman mapping and optical microscopy images can provide mineral categories and spatial distribution characteristics in regions of interest. A quantitative analysis model for Fe, Mg, and Na elements was constructed based on the multidimensional scaling–back propagation neural network (MDS-BPNN) algorithm. The determination coefficient of the model test set was better than 0.997, and the root mean square error was better than 0.65. The content of Fe, Mg, and Na elements in the meteorite was preliminarily evaluated, providing a reference for further analysis of element information in spectral image fusion data. The Raman–LIBS combined technology has significant application potential in rapidly evaluating suspected meteorite samples. Without high-end precision instruments or field research, this technology can provide scientists with significant reference value atomic and molecular spectral information. At the same time, this technology can be extended to other petrology research. We offer a fast, efficient, cost-effective, and reliable analysis scheme for reference.

Quantitative Analysis of Mixtures Based on Portable Spatial Heterodyne Raman Spectrometer

Spatial heterodyne Raman spectroscopy has been widely applied in various fields due to its non-contact, nondestructive, fast, high stability, and high spectral resolution characteristics. This article integrated spatial heterodyne Raman spectroscopy with chemometric methodologies to assess the feasibility of peak-to-peak ratio regression, partial least squares regression, support vector machine regression, and non-negative matrix factorization for the quantitative analysis of mixtures. Chemometrics methods were used to model and analyze the interference data in the interferogram domain, and variational mode decomposition was used to extract features from the interference data, further improving the interference data’s modeling and prediction accuracy. The results demonstrate that modal intensities obtained through variational mode decomposition of interference data improve the prediction accuracy of regression analysis. Support vector regression exhibited the most favorable predictive performance among the tested models. The root mean square error of cross-validation was reduced from 5.55% to 2.64%, and the prediction root mean square error was reduced from 5.08% to 1.5%. The improved model utilizing interference data showed higher fitting accuracy and more precise sample predictions compared to spectral data modeling.

Assessing the utility of high spectral resolution lidar for measuring particulate backscatter in the ocean and evaluating satellite ocean color retrievals

Airborne high spectral resolution lidar (HSRL) measurements of ocean particulate backscatter (bbp) offer dramatic improvements in spatiotemporal coverage over in situ techniques, filling observational “blind spots” that limit our ability to study ocean processes. However, the technique has been assessed in only a few limited cases, and uncertainties remain regarding its applicability across a diversity of optical domains. In this study, we present the first comprehensive comparison of bbp derived from airborne HSRL, satellite ocean color, and in situ measurements to increase confidence in HSRL bbp retrievals and to demonstrate the value of airborne HSRL for assessing/improving satellite ocean color algorithms. Retrievals of bbp performed using the NASA Langley HSRL-1 instrument agreed with in situ measurements performed across a diversity of optical and ecological domains. Comparisons across multiple campaigns revealed regional and seasonal dependencies in the ocean color retrievals that likely resulted from applying a single configuration of the ocean color retrieval across multiple distinct domains. In two case studies, atmospheric measurements from HSRL-1 and systematic differences in bbp between HSRL and the 2018 NASA ocean color distribution provided evidence of insufficient atmospheric correction of the ocean color retrieval. These differences in bbp were absent from comparisons against the 2022 ocean color distribution, suggesting that changes made to the algorithm resulted in improved retrievals. These cases highlight the advantages of airborne HSRL for assessing and improving ocean color retrievals, namely its ability to provide simultaneous, independent profiles of atmosphere and ocean optical properties, and improvements in the spatiotemporal coverage of satellite matchups.

Clump-scale Gas Infall in High-mass Star Formation: A Multitransition View with James Clerk Maxwell Telescope HCN (4–3) Mapping

Gas infall motions play a crucial role in high-mass star formation and are characterized by observable signatures of blueshifted asymmetric spectral line profiles (“blue profiles”). However, the connection between blue profiles and infall motions is unclear due to complex gas motions at parsec scales. In this study, we present the results of an HCN (4–3) mapping survey conducted with the James Clerk Maxwell Telescope, toward 38 massive clumps exhibiting blue profiles in HCO+ (3–2). We extract 34 HCN cores from the 38 observed fields. The core-averaged spectra show various line profiles, indicating that blue-profile HCO+ (3–2) does not guarantee the same in HCN (4–3). Through non-LTE radiative-transfer calculations, we attribute the low detection rate of high-J blue profiles to a combination of insufficient HCN (4–3) opacity and the intricate gas motion across different density layers. A comparison between the MALT90 and Bolocam Galactic Plane Survey line surveys highlights the importance of appropriate tracers, high spectral resolution, and column density thresholds when searching for blue profiles. We select 11 reliable infall candidates and adopt the Hill5 model to fit the infall velocity of 0.2–1.6 km s−1, corresponding to 5%–74% of freefall velocity. Assuming a spherically collapsing model, we estimate the median and mean mass infall rates to be 4.5 × 10−3 and 7.6 × 10−3 M ⊙ yr−1, respectively. The consistency of the mass infall rates among different transitions suggests a steady accretion process from the clump gas envelope to the inner region.

Subfluvial tunnel layout design: Mapping recent sediment fill in Bilbao Estuary using H/V spectral ratio

Mapping the soil-bedrock interface is crucial for tunnelling projects in engineering geology. This investigation demonstrates the effectiveness of a novel technique to calculate the horizontal-to-vertical (H/V) spectral ratio using ambient vibration measurements to characterize the unconsolidated sediment thickness and geometry of the top of the engineering bedrock in the city of Bilbao (northern Iberian Peninsula). Engineering bedrock is defined here as the consolidated rock layer underlying the Holocene sediments infill in the region. The non-invasive technique was integrated into the geophysical surveys conducted in 2019 for a subfluvial tunnel construction project beneath the Bilbao Estuary. We calculated the H/V transfer function at 37 sites using an AutoRegressive Moving Average (ARMA) model, which has been shown to be robust in extracting the ground fundamental resonant frequency with high spectral resolution. Lithological information from coincident stations and boreholes supports the empirical interpretation of the H/V spectral peaks in terms of peak impedance contrast depth. The estimated engineering bedrock exhibits morphological complexity with depths ranging from ∼10 m to ∼47 m below the surface. The obtained unconsolidated sediment thickness map is consistent with the geology known from the scattered historical borehole data and is supported by the results of the soil geotechnical characterization conducted in 2021 to advance the planning phase of the subfluvial tunnelling project. We show that the novel H/V approach used in this work is robust and yields somewhat higher resolution results than other commonly used H/V methods. The resolution of the method enables the use of H/V estimates to efficiently plan well campaigns and minimise costs, even for relatively shallow targets. We conclude that H/V mapping using this novel technique can help select layout alternatives in the early stages of tunnel construction planning, especially in heavily urbanized areas.

Rapid Determination of Meteorolite Composition Based on X-ray Phase Contrast Imaging-Assisted Raman Spectroscopy

Returning extraterrestrial samples to Earth has become essential for future deep space exploration. Achieving a comprehensive evaluation of the physical and chemical properties of samples with minimal damage is key to analyzing extraterrestrial samples in the future, as well as to the future sampling and returning of heterogeneous solid samples. This article aims to reconstruct the three-dimensional internal structure of high-contrast objects, select sections of interest through internal structure and detail features, and then analyze the physical and chemical properties of the samples based on laser spectroscopy technology. This paper proposes a strategy based on Raman mapping and X-ray phase-contrast imaging technology to reconstruct the three-dimensional internal structure of a heterogeneous solid sample and detect the substance composition of the region of interest. This study takes meteorite samples as an example and uses X-ray phase-contrast imaging technology to distinguish and reconstruct the spatial distribution of different components in the meteorite, providing a three-dimensional visualization reference with a high spatial resolution for the spatial positioning of the region of interest. Raman spectroscopy, in combination with LIBS, was used to further identify the meteorite as pallasite and to achieve the spectral image fusion of high spatial and high spectral resolutions. The experimental results show that the unknown meteorite’s three-dimensional structure and its components’ spatial distribution can be evaluated based on Raman mapping combined with X-ray phase-contrast imaging technology. This article provides a highly valuable analytical strategy by which to analyze samples returned from deep space exploration.

The generation of EarthCARE L1 test data sets using atmospheric model data sets

Abstract. The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation process study mission embarking a high spectral resolution lidar, a cloud profiling radar, a multi-spectral imager, and a three-view broadband radiometer. An important aspect of the EarthCARE mission is its focus on instrument synergy. Many L2 products are the result of L1 inputs from one or more instruments. Since no existing complete observational proxy data sets comprised of co-located and co-temporal “EarthCARE-like” data exists, it has been necessary to create synthetic data sets for the testing and development of various retrieval algorithms and the data processing chain. Given the synergistic nature of the processing chain, it is important that the test data are physically consistent across the various instruments. Within the EarthCARE project, a version of the EarthCARE simulator multi-instrument framework (ECSIM) has been used to create unified realistic test data frames. These simulations have been driven using high-resolution atmospheric model data (described in a companion paper). In this paper, the methods used to create the test data scenes are described. In addition, the simulated L1 data corresponding to each scene are presented and discussed.

Combustion of polyethylene and polypropylene in the fluidized bed with a variable vertical density profile

A new type of fluidized bed with a variable vertical density profile was developed. A mixture of sand (Ønominal = 100–140 μm, 2.6 g/cm3) and cenospheres (Ønominal = 140–160 μm, 0.85 g/cm3) was used to form a binary fluidized bed. The minimum fluidization velocity of the binary fluidized bed was determined experimentally. Two points of inflection on the fluidization curve were observed. Additionally, a measurement of the pressure as a function of height was used to determine the profile of fluidized bed density. It was proven that the fluidized bed made out of cenospheres and sand can be characterized by a variable vertical density profile. The binary fluidized bed was used for the combustion of polyolefins. The results were compared to combustion in a conventional fluidized bed made out of sand. The surface of the fluidized bed was video recorded and the changes in the image brightness were used to identify diffusion combustion in the freeboard. A Fourier Transform Infrared (FTIR) analyzer with high spectral resolution (1 cm−1) was used to record the IR spectra of flue gases. In-house software was used to deconvolve complex IR spectra. In the process performed in the fluidized bed made out of sand, regardless of temperature, around 30 % of the polymeric carbon left the reactor in the form of soot. The lack of dependence on the temperature results from the fact that in such an organized process combustion did not take place inside the fluidized bed but on its surface. The binary fluidized bed eliminated the problem of the presence of diffusion flames and soot formation. High fuel conversion to CO2 (above 90 %) was observed at temperatures above over 800 °C during polyolefin combustion in the binary fluidized bed.

The experimental approach for the interleaved joint modulation of PHIP and NMR.

Nuclear spin hyperpolarization derived from parahydrogen is a technique for enhancing nuclear magnetic resonance (NMR) sensitivity. The key to hyperpolarization experiments is to achieve rapid transfer and detection to minimize relaxation losses, while also avoiding bubbles or turbulence to guarantee high spectral resolution. In this article, we describe an experimental approach for the interleaved joint modulation of parahydrogen-induced polarization and NMR. We provide schematic diagrams of parahydrogen-based polarizer with in situ high-pressure detection capability and low-field polarization transfer. This approach can help to control the experimental process and acquire experimental information, one example of which is the attainment of the highest hyperpolarization signal intensity at 3.6s after closing the valve. The polarizer demonstrates in situ detection capability, allowing sample to be restabilized within 0.3 ± 0.1s and high-resolution NMR sampling under a pressure of 3 bars. Moreover, it can transfer polarized samples from the polarization transfer field to the detection region of NMR within 1 ± 0.3s for completing signal amplification by reversible exchange experiments.

Demonstration of a Rayleigh-Brillouin scattering spectrometer with a high spectral resolution for rapid gas temperature detection.

A novel, to the best of our knowledge, Rayleigh-Brillouin scattering (RBS) spectrometer based on a virtually imaged phased array (VIPA) with a high spectral resolution is proposed for rapid gas temperature detection. CO2 RBS spectra at gas pressure of 0.5-4 bar were acquired with a spectrum acquisition time of 10 s, and temperature inversion analysis was performed using TENTI S6 model. The root-mean-square error (RMSE) of the RBS profile fitting is less than 2.95%, and the maximum absolute error of temperature inversion is less than 2.45 K. Compared with traditional methods, this method has low RBS signal loss and short acquisition time without the frequency scanning process, which is more conducive to real-time detection applications.

Nanoscale chemical characterization of secondary protein structure of F-Actin using mid-infrared photoinduced force microscopy (PiF-IR)

The recently developed photoinduced force microscopy for mid-infrared (PiF-IR) offers high spectral resolution in combination with surface sensitivity and a spatial resolution in the range of a few nanometers. Although PiF-IR has primarily been applied to polymer materials, this technology presents significant potential for the chemical characterization of cellular structures approaching single-molecule sensitivity. We applied PiF-IR to differently polymerized F-Actin samples finding general agreement with FTIR spectra from the same samples. Single PiF-IR spectra of F-Actin show variations in the amide I band spectral region, which is related to secondary protein structure. Local variations are also seen in PiF-IR hyperspectra in this region. Such high sensitivity is a necessary requirement for discriminating Actin organization into bundles and other networks in cells and tissue. We applied PiF-IR to mouse liver tissue ex vivo. Single-frequency PiF-IR scans at three different IR frequencies show significant variations in local contrast. However, the presence of other proteins and the unique spatial resolution of PiF-IR pose a challenge to interpreting and validating such data. Careful design of model systems and further theoretical understanding of PiF-IR data far from bulk averages are needed to fully unfold the potential of PiF-IR for high-resolution chemical investigation in the Life Sciences.

Integrating LEO and GEO Observations: Toward Optimal Summertime Satellite Precipitation Retrieval

Abstract Reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for understanding the Earth’s hydrological cycle. Precipitation estimation over land and coastal regions is necessary for addressing the high degree of spatial heterogeneity of water availability and demand, and for resolving the extremes that modulate and amplify hazards such as flooding and landslides. Advancements in computation power along with unique high spatiotemporal and spectral resolution data streams from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites offer exciting opportunities to retrieve information about surface precipitation phenomena using data-driven machine learning techniques. In this study, the capabilities of U-Net–like architecture are investigated to map instantaneous, summertime surface precipitation intensity at the spatial resolution of 2 km. The calibrated brightness temperature products from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) radiometer are combined with multispectral images (visible, near-infrared, and infrared bands) from the Advanced Baseline Imager (ABI) aboard the GOES-R satellites as main inputs to the U-Net–like precipitation algorithm. Total precipitable water and 2-m temperature from the Global Forecast System (GFS) model are also used as auxiliary inputs to the model. The results show that the U-Net–like algorithm can capture fine-scale patterns and intensity of surface precipitation at high spatial resolution over stratiform and convective precipitation regimes. The evaluations reveal the potential of extracting relevant, high spatial features over complex surface types such as mountainous regions and coastlines. The algorithm allows users to interpret the inputs’ importance and can serve as a starting point for further exploration of precipitation systems within the field of hydrometeorology.

The effects of gravitational waves on a hydrogen atom

We investigate the influence of gravitational waves on a freely falling hydrogen atom by analyzing the dynamics of the bound electron described by the Dirac equation in the curved spacetime of a gravitational wave. From this, we derive the corresponding Dirac Hamiltonian in the local inertial frame of the atom, assuming gravitational waves are described by the linearized theory of general relativity. To maintain meaningful physical interpretations while obtaining a non-relativistic description, we employ the Foldy–Wouthuysen transformation. Through the analysis of resulting interaction terms and comparison with flat spacetime counterparts, valuable insights into the effects of gravitational waves (GWs) on the hydrogen atom are gained. Additionally, we explore selection rules governing the coupling between GWs and the atom and utilize first-order perturbation theory to quantify the induced energy shifts and spectral line splitting. This investigation contributes to our understanding of the interplay between quantum systems and gravitational waves, which could lead to alternative method of GWs indirect detection. However, measuring such tiny energy shifts would require a telescope with very high spectral resolution.

Spatially resolved CO2 carbon stable isotope analyses at the microscale using Raman spectroscopy

Measuring the carbon stable isotope ratio (13C/12C, expressed as δ13CCO2) in geogenic CO2 fluids is a crucial geochemical tool for studying Earth's degassing. Carbon stable isotope analysis is traditionally performed by bulk mass spectrometry. Although Raman spectroscopy distinguishes 12CO2 and 13CO2 isotopologue bands in spectra, using this technique to determine CO2 isotopic signature has been challenging. Here, we report on in-situ non-destructive analyses of the C stable isotopic composition of CO2, applying a novel high-resolution Raman configuration on 42 high-density CO2 fluid inclusions in mantle rocks from the Lake Tana region (Ethiopia) and El Hierro (Canary Islands). We collected two sets of three spectra with different acquisition times at high spectral resolution in each fluid inclusion. Among the 84 sets of spectra, 58 were characterised by integrated 13CO2/12CO2 band area ratios with reproducibility better than 4‰. Our results demonstrate the determination of δ13CCO2 by Raman spectroscopy in individual fluid inclusions with an error better than 2.5 ‰, which satisfactorily matches bulk mass spectrometry analyses in the same rock samples, supporting the accuracy of the measurements. We thus show that Raman Spectroscopy can provide a fundamental methodology for non-destructive, site-specific, and spatially resolved carbon isotope labelling at the microscale.

Optomechanical integrated performance analysis and optimization of a greenhouse gas absorption spectrometer

Design of a space-borne opomechanical system with high spatial resolution, spectral resolution and quality imagery demands a tightly integrated performance optimization method to expand the design space and improve the optical performance of the system. In this paper, a Kriging-based method is proposed for optomechanical integrated performance optimization of a greenhouse gas absorption spectrometer (GGAS). The proposed method combines the thermal-structural-optical (TSO) integrated analysis method and the Kriging meta-modeling technique, in which the latter one is used to replace the former analysis process and approximates the I/O functions implied in the underlying TSO simulation model. Structural deformation characteristics and optical performance of GGAS are evaluated firstly. Then, optomechanical structural optimization of GGAS is carried out to achieve lightweight of three sub-benches. Results show that the proposed method is able to reduce the weight of three sub-benches by 11.85 % compared to the common opomechanical design method while satisfying almost the same constraints.

Review on the development of multi- and hyperspectral remote sensing technology for exploration of copper–gold deposits

Most Copper (Cu) and Gold (Au) deposits are accompanied by hydrothermal alteration, generally related to ore-forming hydrothermal fluids. Multispectral and hyper-spectral Remote Sensing (RS) technology is essential for Cu-Au mineral prospecting. This paper provides an overview of RS data and the research situation and development tendencies of RS exploration technologies related to Cu-Au deposits. Initially, RS geologists applied the Band Ratio (BR) and Principal Component Analysis (PCA) to extract hydroxyl and iron anomalies from Landsat RS data to characterize the hydrothermal alterations associated with Cu-Au deposits. In the era of advanced spaceborne thermal emission and reflection radiometry (ASTER), clay minerals, sulfate minerals, carbonate minerals, silica minerals, and iron minerals can be identified because of three Visible and near-infrared bands (VNIR), six shortwave infrared bands (SWIR), and five Thermal Infrared bands (TIR). Alteration of mineral assemblages can be carried out to map alteration zones, which are essential for calibrating Cu-Au alteration zones, such as the typical alteration zoning characteristics of Porphyry Copper Deposits (PCD). Because of its high spectral resolution, Satellite hyperspectral RS can quantitatively map surface alteration minerals to indicate the exploration of Cu-Au deposits. RS geologists have extensively researched matching libraries and field spectra for Alteration Mineral Mapping (AMM). However, subpixel mineral information caused by low spatial resolution and atmospheric factors has an unavoidable influence on satellite hyperspectral RS AMM, and it is essential to use low-altitude unmanned aerial vehicle (UAV) hyperspectral RS. UAV hyperspectral AMM combined with geochemistry and geophysics is a means of prospecting and exploring Cu-Au deposits.