scholarly journals Ground Validation Experiment and Spectral Detection Capability Evaluation of Mars Mineralogical Spectrometer (MMS) Aboard HX-1 Orbiter

2021 ◽  
Vol 218 (1) ◽  
Author(s):  
Bin Liu ◽  
Xin Ren ◽  
Dawei Liu ◽  
Jianjun Liu ◽  
Qing Zhang ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Spectral Resolution ◽  
Operation Mode ◽  
Spectral Characteristics ◽  
Atmospheric Composition ◽  
Detection Capability ◽  
Validation Experiment ◽  
Ground Validation ◽  
Spectral Detection ◽  
Areas Of Interest

AbstractAs a hyperspectral imager aboard the orbiter “HX-1” of China’s first Mars mission, the Mars Mineralogical Spectrometer (MMS) is designed with hyperspectral and multispectral operation modes to survey the mineral types and their distribution on the surface of Mars, and to study the overall chemical composition and evolution history of Mars. The multispectral modes of MMS are different from hyperspectral modes on the bands selection, spatial and spectral resolution, Signal-to-Noise Ratio (SNR) etc. So the spectral detection capability of each mode of MMS is also different. The ground validation experiment of MMS is conducted to evaluate the hyperspectral and multispectral data quality and detection capabilities. The main conclusions include: (1) The measured hyperspectra of typical mineral samples obtained by MMS agree well with the data acquired by the Standard Comparison Spectrometers (SCS) under the same measurement conditions, and the spectral uncertainty between MMS and SCS is less than 7% in the key spectral ranges ($0.7\sim2.2~\upmu \text{m}$ 0.7 ∼ 2.2 μm ). For some typical minerals, the absorption band positions deviation between MMS and SCS are within $0.69\sim14.86~\text{nm}$ 0.69 ∼ 14.86 nm , which are within the spectral resolution limits of MMS. (2) The six sets of band combinations designed for MMS multispectral modes are slightly superior to CRISM’s multispectral mode in terms of spectral resolutions and bands selection, the water-containing minerals will be more accurately distinguished and identified, such as montmorillonite and kaolinite. Besides, the SNR of each multispectral mode is greater than 400 in the 500–2600 nm spectral range, which meets the requirements for the subtle spectral characteristics of water-containing minerals. (3) Benefiting from the MMS ground validation experiment and the experience of the OMEGA and CRISM, it is recommended that MMS first adopt the spatial continuous 52-sample or 104-sample (spatial resolution is about $0.53\sim1.06~\text{km}$ 0.53 ∼ 1.06 km ) multispectral operation mode for typical minerals global mapping and finding target areas of interest. Then the 208-sample multispectral mode (spatial resolution is about $\sim265~\text{m}$ ∼ 265 m ) or 26-sample hyperspectral mode can be used to survey target areas of interest for the subtle mineral types characteristics and distribution. At last, 26-sample hyperspectral mode could be used to monitor the atmospheric composition of Mars by limb observations.

scholarly journals Capability of Remote Sensing Images to Distinguish the Urban Surface Materials: A Case Study of Venice City

2021 ◽  
Vol 13 (19) ◽  
pp. 3959
Author(s):  
Rosa Maria Cavalli
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Spectral Range ◽  
Spectral Resolution ◽  
Urban Areas ◽  
Spectral Characteristics ◽  
Urban Surface ◽  
Remote Sensing Images ◽  
Surface Materials ◽  
The Impact

Many countries share an effort to understand the impact of growing urban areas on the environment. Spatial, spectral, and temporal resolutions of remote sensing images offer unique access to this information. Nevertheless, their use is limited because urban surface materials exhibit a great diversity of types and are not well spatially and spectrally distinguishable. This work aims to quantify the effect of these spatial and spectral characteristics of urban surface materials on their retrieval from images. To avoid other sources of error, synthetic images of the historical center of Venice were analyzed. A hyperspectral library, which characterizes the main materials of Venice city and knowledge of the city, allowed to create a starting image at a spatial resolution of 30 cm and spectral resolution of 3 nm and with a spectral range of 365–2500 nm, which was spatially and spectrally resampled to match the characteristics of most remote sensing sensors. Linear spectral mixture analysis was applied to every resampled image to evaluate and compare their capabilities to distinguish urban surface materials. In short, the capability depends mainly on spatial resolution, secondarily on spectral range and mixed pixel percentage, and lastly on spectral resolution; impervious surfaces are more distinguishable than pervious surfaces. This analysis of capability behavior is very important to select more suitable remote sensing images and/or to decide the complementarity use of different data.

Precipitation in silicon: Microanalysis

1988 ◽  
Vol 46 ◽  
pp. 474-475
Author(s):  
R.W. Carpenter
Keyword(s):  
Transition Metals ◽  
Spatial Resolution ◽  
Thin Foil ◽  
Precipitation Reaction ◽  
High Current ◽  
Reaction Products ◽  
Carbon And Nitrogen ◽  
Dielectric Layers ◽  
Precipitation Processes ◽  
Areas Of Interest

Interest in precipitation processes in silicon appears to be centered on transition metals (for intrinsic and extrinsic gettering), and oxygen and carbon in thermally aged materials, and on oxygen, carbon, and nitrogen in ion implanted materials to form buried dielectric layers. A steadily increasing number of applications of microanalysis to these problems are appearing. but still far less than the number of imaging/diffraction investigations. Microanalysis applications appear to be paced by instrumentation development. The precipitation reaction products are small and the presence of carbon is often an important consideration. Small high current probes are important and cryogenic specimen holders are required for consistent suppression of contamination buildup on specimen areas of interest. Focussed probes useful for microanalysis should be in the range of 0.1 to 1nA, and estimates of spatial resolution to be expected for thin foil specimens can be made from the curves shown in Fig. 1.

scholarly journals Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-Term Exposure to Surface NO2 over South Korea

2021 ◽  
Vol 13 (10) ◽  
pp. 1877
Author(s):  
Ukkyo Jeong ◽  
Hyunkee Hong
Keyword(s):  
South Korea ◽  
Spatial Resolution ◽  
Atmospheric Composition ◽  
Mixing Ratio ◽  
Mean Values ◽  
Mixing Ratios ◽  
Tropospheric No2 ◽  
Korean Ministry ◽  
Surface Mixing ◽  
Rural Sites

Since April 2018, the TROPOspheric Monitoring Instrument (TROPOMI) has provided data on tropospheric NO2 column concentrations (CTROPOMI) with unprecedented spatial resolution. This study aims to assess the capability of TROPOMI to acquire high spatial resolution data regarding surface NO2 mixing ratios. In general, the instrument effectively detected major and moderate sources of NO2 over South Korea with a clear weekday–weekend distinction. We compared the CTROPOMI with surface NO2 mixing ratio measurements from an extensive ground-based network over South Korea operated by the Korean Ministry of Environment (SKME; more than 570 sites), for 2019. Spatiotemporally collocated CTROPOMI and SKME showed a moderate correlation (correlation coefficient, r = 0.67), whereas their annual mean values at each site showed a higher correlation (r = 0.84). The CTROPOMI and SKME were well correlated around the Seoul metropolitan area, where significant amounts of NO2 prevailed throughout the year, whereas they showed lower correlation at rural sites. We converted the tropospheric NO2 from TROPOMI to the surface mixing ratio (STROPOMI) using the EAC4 (ECMWF Atmospheric Composition Reanalysis 4) profile shape, for quantitative comparison with the SKME. The estimated STROPOMI generally underestimated the in-situ value obtained, SKME (slope = 0.64), as reported in previous studies.

scholarly journals Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

2021 ◽  
Vol 13 (9) ◽  
pp. 1693
Author(s):  
Anushree Badola ◽  
Santosh K. Panda ◽  
Dar A. Roberts ◽  
Christine F. Waigl ◽  
Uma S. Bhatt ◽  
...  
Keyword(s):  
Land Cover ◽  
Spectral Resolution ◽  
Hyperspectral Image ◽  
Spectral Response ◽  
Spectral Characteristics ◽  
Hyperspectral Data ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Fuel Mapping ◽  
Sentinel 2

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.

scholarly journals Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information

2020 ◽  
Vol 12 (6) ◽  
pp. 1009
Author(s):  
Xiaoxiao Feng ◽  
Luxiao He ◽  
Qimin Cheng ◽  
Xiaoyi Long ◽  
Yuxin Yuan
Keyword(s):  
Image Fusion ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Spatial Information ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Remote Sensing Image Fusion ◽  
Fusion Methods ◽  
Invariant Regions ◽  
The Difference

Hyperspectral (HS) images usually have high spectral resolution and low spatial resolution (LSR). However, multispectral (MS) images have high spatial resolution (HSR) and low spectral resolution. HS–MS image fusion technology can combine both advantages, which is beneficial for accurate feature classification. Nevertheless, heterogeneous sensors always have temporal differences between LSR-HS and HSR-MS images in the real cases, which means that the classical fusion methods cannot get effective results. For this problem, we present a fusion method via spectral unmixing and image mask. Considering the difference between the two images, we firstly extracted the endmembers and their corresponding positions from the invariant regions of LSR-HS images. Then we can get the endmembers of HSR-MS images based on the theory that HSR-MS images and LSR-HS images are the spectral and spatial degradation from HSR-HS images, respectively. The fusion image is obtained by two result matrices. Series experimental results on simulated and real datasets substantiated the effectiveness of our method both quantitatively and visually.

scholarly journals Система терагерцевой спектроскопии газовых смесей на основе твердотельных сверхпроводниковых источника и приемника терагерцевого диапазона

2021 ◽  
Vol 63 (9) ◽  
pp. 1204
Author(s):  
Н.В. Кинев ◽  
К.И. Рудаков ◽  
Л.В. Филиппенко ◽  
В.П. Кошелец
Keyword(s):  
Spectral Resolution ◽  
Open Space ◽  
Spectral Characteristics ◽  
Gas Mixture ◽  
Sis Receiver ◽  
Wide Range ◽  
A Cell ◽  
Transmitting Antenna ◽  
Josephson Oscillator ◽  
Better Than

In this paper, we demonstrate the application of a terahertz (THz) Josephson oscillator based on a tunnel superconductor-insulator-superconductor (SIS) long junction coupled to a transmitting antenna and emitting a signal to open space, for gas spectroscopy. The oscillator is utilized as an active source, the signal of which is absorbed by a gas mixture in a cell 60 cm long and then detected by a spectrometer based on a SIS receiver with a spectral resolution of better than 100 kHz. In the experiment, the absorption lines of ammonia and water in the THz range were recorded, and the dependence of the absorption spectral characteristics on the pressure of the gas mixture was shown in a wide range (from 0.005 to 10 mbar).

Postscript

2020 ◽  
pp. 403-404
Author(s):  
Timothy P. L. Roberts ◽  
James W. Wheless ◽  
Andrew C. Papanicolaou
Keyword(s):  
Magnetic Resonance Imaging ◽  
Electrical Conductivity ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Inverse Modeling ◽  
Oscillatory Activity ◽  
Electric Potentials ◽  
Spatial Source

As is evident from the scientific chapters of this book, the technology of magnetoencephalography offers a combination of spatial, temporal, and spectral resolution, unique among neuroimaging technologies. While functional magnetic resonance imaging (fMRI) accommodates spatial resolution, it lacks the millisecond resolution (because of the reliance on a slow hemodynamic response) to identify subtle latency shifts, or the specificity to distinguish theta- versus alpha- versus gamma-band oscillatory activity. While electroencephalography (EEG) offers the needed temporal resolution, it fails to adequately localize brain sources, owing to the physics of inverse modeling and the dependence of scalp electric potentials on tissue electrical conductivity. Thus, although fMRI may see “activity,” it cannot characterize important attributes of its nature. Conversely, EEG may detect “anomalies” but not be able to attribute them to a particular spatial source....

Image processing method to improve AOTF spectral resolution and spatial resolution

2016 ◽  
Vol 63 (21) ◽  
pp. 2203-2210
Author(s):  
Rui Zhang ◽  
Kewu Li ◽  
Yuanyuan Chen ◽  
Yaoli Wang ◽  
Zhibin Wang
Keyword(s):  
Image Processing ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Processing Method ◽  
Image Processing Method

Multichannel Hadamard Transform Raman Microscopy

1990 ◽  
Vol 44 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Patrick J. Treado ◽  
Michael D. Morris
Keyword(s):  
Spatial Resolution ◽  
Spectral Resolution ◽  
Spatial Multiplexing ◽  
Raman Microscopy ◽  
Hadamard Transform ◽  
Multichannel Detection ◽  
Spatial Multiplex

Spatial multiplexing is combined with multichannel detection in a Hadamard transform Raman microscope which provides 127 × 128 pixel images with 12 cm−1 spectral resolution. Spatial resolution of 0.6 μm per pixel has been achieved. A spatial multiplex advantage of better that 104 is demonstrated. Instrumental design details and spectroscopic images are presented.

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