Observation of Chern insulator in crystalline ABCA-tetralayer graphene with spin-orbit coupling

Degeneracies in multilayer graphene, including spin, valley, and layer degrees of freedom, are susceptible to Coulomb interactions and can result into rich broken-symmetry states. In this work, we report a ferromagnetic state in charge neutral ABCA-tetralayer graphene driven by proximity-induced spin-orbit coupling from adjacent WSe2. The ferromagnetic state is further identified as a Chern insulator with Chern number of 4, and its Hall resistance reaches 78% and 100% quantization of h/4e2 at zero and 0.4 tesla, respectively. Three broken-symmetry insulating states, layer-antiferromagnet, Chern insulator and layer-polarized insulator and their transitions can be continuously tuned by the vertical displacement field. Remarkably, the magnetic order of the Chern insulator can be switched by three knobs, including magnetic field, electrical doping, and vertical displacement field

Uncertainty analysis for topographic correction of hyperspectral remote sensing images

Quantitative uncertainty analysis is generally taken as an indispensable step in the calibration of a remote sensor. A full uncertainty propagation chain has not been established to set up the metrological traceability for surface reflectance inversed from remotely sensed images. As a step toward this goal, we proposed an uncertainty analysis method for the two typical semi-empirical topographic correction models, i.e., C and Minnaert, according to the ‘Guide to the Expression of Uncertainty in Measurement (GUM)’. We studied the data link and analyzed the uncertainty propagation chain from the digital elevation model (DEM) and at-sensor radiance data to the topographic corrected radiance. We obtained spectral uncertainty characteristics of the topographic corrected radiance as well as its uncertainty components associated with all of the input quantities by using a set of Earth Observation-1 (EO-1) Hyperion data acquired over a rugged soil surface partly covered with snow. Firstly, the relative uncertainty of cover types with lower radiance values was larger for both C and Minnaert corrections. Secondly, the trend of at-sensor radiance contributed to a spectral feature, where the uncertainty of the topographic corrected radiance was poor in bands below 1400 nm. Thirdly, the uncertainty components associated with at-sensor radiance, slope, and aspect dominated the total combined uncertainty of corrected radiance. It was meaningful to reduce the uncertainties of at-sensor radiance, slope, and aspect for reducing the uncertainty of corrected radiance and improving the data quality. We also gave some suggestions to reduce the uncertainty of slope and aspect data

Automatic Spectral Unmixing of Hyperspectral Data Before Radiation Correction: Application to PHI Data

Radiation correction is often required in popular spectral unmixing of hyperspectral data, followed by interactive endmember determination methods. It involves much heavy work for the huge amount of hyperspectral data. In this paper, an uncorrected image of Push-broom Hyperspectral Imager (PHI) was automatically unmixed based on the linear mixing model, using Minimum Noise Fraction (MNF) transformation to find the inherent dimensionality off the data, convex geometry concepts to extract endmembers and least squares method to estimate the fractional abundances. The result abundance images indicated that hyperspectral data, in subsection of appropriate size, can be unmixed before radiation correction and no apriori ground information is required.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000260989400235&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Geosciences, MultidisciplinaryRemote SensingImaging Science & Photographic TechnologyCPCI-S(ISTP)

Spectral super-resolution reflectance retrieval from remotely sensed imaging spectrometer data

Existing atmospheric correction methods retrieve surface reflectance keeping the same nominal spectral response functions (SRFs) as that of the airborne/spaceborne imaging spectrometer radiance data. Since the SRFs vary dependent on sensor type and configuration, the retrieved reflectance of the same ground object varies from sensor to sensor as well. This imposes evident limitations on data validation efforts between sensors at surface reflectance level. We propose a method to retrieve super-resolution reflectance at the surface, by combining the first-principles atmospheric correction method FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes) with spectral super-resolution of imaging spectrometer radiance data. This approach is validated by comparing airborne AVIRIS (airborne visible/infrared imaging spectrometer) and spaceborne Hyperion data. The results demonstrate that the super-resolution reflectance in spectral bands with sufficiently high signal-to-noise ratio (SNR) serves as intermediate quantity to cross validate data originating from different imaging spectrometers

SWIR AOTF Imaging Spectrometer Based on Single-pixel Imaging

An acousto-optic tunable filter (AOTF) is a new type of mono-wavelength generator, and an AOTF imaging spectrometer can obtain spectral images of interest. However, due to the limitation of AOTF aperture and acceptance angle, the light passing through the AOTF imaging spectrometer is weak, especially in the short-wave infrared (SWIR) region. In weak light conditions, the noise of a non-deep cooling mercury cadmium telluride (MCT) detector is high compared to the camera response. Thus, effective spectral images cannot be obtained. In this study, the single-pixel imaging (SPI) technique was applied to the AOTF imaging spectrometer, which can obtain spectral images due to the short-focus lens that collects light into a small area. In our experiment, we proved that the irradiance of a short-focus system is much higher than that of a long-focus system in relation to the AOTF imaging spectrometer. Then, an SPI experimental setup was built to obtain spectral images in which traditional systems cannot obtain. This work provides an efficient way to detect spectral images from 1000 to 2200 nm

Atmosphere and Terrain Coupling Simulation Framework for High-Resolution Visible-Thermal Spectral Imaging over Heterogeneous Land Surface

Realistic modeling of high-resolution earth radiation signals in the visible-thermal spectral domain remains difficult, due to the complex radiation interdependence induced by the heterogeneous and rugged features of land surface. To find the trade-off between accuracy and efficiency for image simulation, this paper established a unified simulation framework for the entire visible-thermal spectral domain, based on the energy balance between solar-reflected and thermal radiation components over rugged surfaces. Considering the joint contributions of atmospheric and topographic adjacency effects, three spatial–spectral convolution kernels were uniformly designed to quantify the topographic irradiance, the trapping effect, and the atmospheric adjacency effect. Radiation signal simulation was implemented in three forms: land surface temperature (LST), bottom of atmosphere (BOA) radiance, and top of atmosphere (TOA) radiance. The accuracy was validated with onboard data from China’s Gaofen-5 visual and infrared multispectral sensor (VIMS) over rugged desert. The simulation results demonstrate that the root mean square of relative deviations between the simulated and onboard TOA radiance are related to terrain, as 3–17% and 6–38% for the summer and winter scene, respectively. The evaluation of radiance components indicates the utility of the simulation framework to quantify the uncertainty associated with atmosphere and terrain coupling effects, in the sensor design and operation stages

A Digital Sensor Simulator of the Pushbroom Offner Hyperspectral Imaging Spectrometer

Sensor simulators can be used in forecasting the imaging quality of a new hyperspectral imaging spectrometer, and generating simulated data for the development and validation of the data processing algorithms. This paper presents a novel digital sensor simulator for the pushbroom Offner hyperspectral imaging spectrometer, which is widely used in the hyperspectral remote sensing. Based on the imaging process, the sensor simulator consists of a spatial response module, a spectral response module, and a radiometric response module. In order to enhance the simulation accuracy, spatial interpolation-resampling, which is implemented before the spatial degradation, is developed to compromise the direction error and the extra aliasing effect. Instead of using the spectral response function (SRF), the dispersive imaging characteristics of the Offner convex grating optical system is accurately modeled by its configuration parameters. The non-uniformity characteristics, such as keystone and smile effects, are simulated in the corresponding modules. In this work, the spatial, spectral and radiometric calibration processes are simulated to provide the parameters of modulation transfer function (MTF), SRF and radiometric calibration parameters of the sensor simulator. Some uncertainty factors (the stability, band width of the monochromator for the spectral calibration, and the integrating sphere uncertainty for the radiometric calibration) are considered in the simulation of the calibration process. With the calibration parameters, several experiments were designed to validate the spatial, spectral and radiometric response of the sensor simulator, respectively. The experiment results indicate that the sensor simulator is valid

Uncertainty Analysis for Topographic Correction of Hyperspectral Remote Sensing Images

Quantitative uncertainty analysis is generally taken as an indispensable step in the calibration of a remote sensor. A full uncertainty propagation chain has not been established to set up the metrological traceability for surface reflectance inversed from remotely sensed images. As a step toward this goal, we proposed an uncertainty analysis method for the two typical semi-empirical topographic correction models, i.e., C and Minnaert, according to the ‘Guide to the Expression of Uncertainty in Measurement (GUM)’. We studied the data link and analyzed the uncertainty propagation chain from the digital elevation model (DEM) and at-sensor radiance data to the topographic corrected radiance. We obtained spectral uncertainty characteristics of the topographic corrected radiance as well as its uncertainty components associated with all of the input quantities by using a set of Earth Observation-1 (EO-1) Hyperion data acquired over a rugged soil surface partly covered with snow. Firstly, the relative uncertainty of cover types with lower radiance values was larger for both C and Minnaert corrections. Secondly, the trend of at-sensor radiance contributed to a spectral feature, where the uncertainty of the topographic corrected radiance was poor in bands below 1400 nm. Thirdly, the uncertainty components associated with at-sensor radiance, slope, and aspect dominated the total combined uncertainty of corrected radiance. It was meaningful to reduce the uncertainties of at-sensor radiance, slope, and aspect for reducing the uncertainty of corrected radiance and improving the data quality. We also gave some suggestions to reduce the uncertainty of slope and aspect data

Detection and correction of spectral shift effects for the airborne prism experiment

Shifts of center wavelengths (CWLs) and related changes of full-widths at half-maximums (FWHMs) occur during in-flight data acquisitions of push-broom imaging spectrometers such as the airborne prism experiment (APEX). Combined with the spectrally changing properties of the dichroic coating that acts as a beam splitter between the visible and near infrared (VNIR) as well as the short-wave infrared (SWIR) channels, these shifts affect both the spectral and radiometric accuracies of the spectrometer data, and hence the accuracy of higher level products. In this paper, two independent standards, i.e., atmospheric absorption features as well as features of the standard reference material filter built in the APEX in-flight characterization facility, are used in a complementary way to improve in-flight spectral calibration. The CWL shift and FWHM change for each detector element are simultaneously detected by using spectrum-matching and surface fitting techniques under constraints from pregenerated shift realizations. Subsequently, the APEX spectroradiometric response model is improved in the aspect of spectral resolution by using performance parameters of optics and detector modules. The radiometric gain and offset for each detector element are corrected according to the detected CWLs and FWHMs, as well as the improved APEX response model. Compared with the spectral and radiometric parameters acquired during laboratory calibration, the detected CWLs and FWHMs promote the accuracy of the atmospheric feature positions in the SWIR channel by 10 nm, whereas the corrected gains and offsets reduce the radiance deviation in the spectral regions 375-550 nm and 950-1080 nm both by 70% on average