scholarly journals Introducing the New Generation of Chinese Geostationary Weather Satellites, Fengyun-4

2017 ◽  
Vol 98 (8) ◽  
pp. 1637-1658 ◽  
Author(s):  
Jun Yang ◽  
Zhiqing Zhang ◽  
Caiying Wei ◽  
Feng Lu ◽  
Qiang Guo
Keyword(s):  
Near Infrared ◽  
Space Environment ◽  
High Spectral Resolution ◽  
Imaging Data ◽  
Satellite Systems ◽  
Spectral Bands ◽  
Wide Range ◽  
Geostationary Meteorological Satellite ◽  
Resolution Imaging ◽  
New Generation

Abstract China is developing a new generation of geostationary meteorological satellites called Fengyun-4 (FY-4), which is planned for launch beginning in 2016. Following upon the current FY-2 satellite series, FY-4 will carry four new instruments: the Advanced Geosynchronous Radiation Imager (AGRI), the Geosynchronous Interferometric Infrared Sounder (GIIRS), the Lightning Mapping Imager (LMI), and the Space Environment Package (SEP). The first satellite of the FY-4 series launched on 11 December 2016 is experimental, and the following four or more satellites will be operational. The main objectives of the FY-4 series are to monitor rapidly changing weather systems and to improve warning and forecasting capabilities. The FY-4 measurements are aimed at accomplishing 1) high temporal and spatial resolution imaging in 14 spectral bands from the visible, near-infrared, and infrared (IR) spectral regions; 2) lightning imaging; and 3) high-spectral-resolution IR sounding observations over China and adjacent regions. FY-4 will also enhance the space weather monitoring and warning with SEP. Current products from FY-2 will be improved by FY-4, and a number of new products will also be introduced. FY-4’s sounding and imaging data will be used to improve applications in a wide range of ocean, land, and atmosphere monitoring plus forecasting extreme weather (especially typhoons and thunderstorms); overall, FY-4 will contribute to more accurate understanding and forecasting of China’s weather, climate, environment, and natural disasters. This new generation of Chinese geostationary weather satellites is being developed in parallel with the new generation of geostationary meteorological satellite systems from the international community of satellite providers and is intended to be an important contribution to the global observing system.

scholarly journals Deep learning classifiers for near infrared spectral imaging: a tutorial

2020 ◽  
Author(s):  
Jun-Li Xu ◽  
Cecilia Riccioli ◽  
Ana Herrero-Langreo ◽  
Aoife Gowen
Keyword(s):  
Deep Learning ◽  
Visual Recognition ◽  
Near Infrared ◽  
Three Dimensional ◽  
Spectral Imaging ◽  
Learning Approaches ◽  
Imaging Data ◽  
Spectral Image ◽  
Background Removal ◽  
Wide Range

Deep learning (DL) has recently achieved considerable successes in a wide range of applications, such as speech recognition, machine translation and visual recognition. This tutorial provides guidelines and useful strategies to apply DL techniques to address pixel-wise classification of spectral images. A one-dimensional convolutional neural network (1-D CNN) is used to extract features from the spectral domain, which are subsequently used for classification. In contrast to conventional classification methods for spectral images that examine primarily the spectral context, a three-dimensional (3-D) CNN is applied to simultaneously extract spatial and spectral features to enhance classificationaccuracy. This tutorial paper explains, in a stepwise manner, how to develop 1-D CNN and 3-D CNN models to discriminate spectral imaging data in a food authenticity context. The example image data provided consists of three varieties of puffed cereals imaged in the NIR range (943–1643 nm). The tutorial is presented in the MATLAB environment and scripts and dataset used are provided. Starting from spectral image pre-processing (background removal and spectral pre-treatment), the typical steps encountered in development of CNN models are presented. The example dataset provided demonstrates that deep learning approaches can increase classification accuracy compared to conventional approaches, increasing the accuracy of the model tested on an independent image from 92.33 % using partial least squares-discriminant analysis to 99.4 % using 3-CNN model at pixel level. The paper concludes with a discussion on the challenges and suggestions in the application of DL techniques for spectral image classification.

Indium Antimonide (InSb) Focal Plane Array (FPA) Detection for Near-Infrared Imaging Microscopy

1994 ◽  
Vol 48 (5) ◽  
pp. 607-615 ◽  
Author(s):  
Patrick J. Treado ◽  
Ira W. Levin ◽  
E. Neil Lewis
Keyword(s):  
Indium Antimonide ◽  
High Speed ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Optical Microscope ◽  
Tunable Filter ◽  
Model Systems ◽  
High Spectral Resolution ◽  
Spectral Interval ◽  
Wide Range

Near-infrared spectroscopy is a sensitive, noninvasive method for chemical analyses, and its integration with imaging technologies represents a potent tool for the study of a wide range of materials. In this communication the use of an indium antimonide (InSb) multichannel imaging detector for near-infrared absorption spectroscopic microscopy is described. In particular, a 128 × 128 pixel InSb staring array camera has been combined with a refractive optical microscope and an acousto-optic tunable filter (AOTF) to display chemically discriminative, spatially resolved, vibrational spectroscopic images of biological and polymeric systems. AOTFs are computer-controlled bandpass filters that provide high speed, random wavelength access, wide spectral coverage, and high spectral resolution. Although AOTFs inherently have a wide range of spectroscopic applications, we apply this technology to NIR absorption microscopy between 1 and 2.5 μm. The spectral interval is well matched to the optical characteristics of both the NIR refractive microscope and the AOTF, thereby providing near-diffraction-limited performance with a practical spatial resolution of 1 to 2 μm. Design principles of this novel instrumentation and representative applications of the technique are presented for various model systems.

scholarly journals High-resolution imaging and near-infrared spectroscopy of penumbral decay

2018 ◽  
Vol 614 ◽  
pp. A2 ◽  
Author(s):  
M. Verma ◽  
C. Denker ◽  
H. Balthasar ◽  
C. Kuckein ◽  
R. Rezaei ◽  
...  
Keyword(s):  
Magnetic Field ◽  
High Resolution ◽  
Active Region ◽  
Magnetic Fields ◽  
Near Infrared ◽  
Imaging Spectroscopy ◽  
Imaging Data ◽  
Horizontal Magnetic Field ◽  
Flux System ◽  
Resolution Imaging

Aims. Combining high-resolution spectropolarimetric and imaging data is key to understanding the decay process of sunspots as it allows us to scrutinize the velocity and magnetic fields of sunspots and their surroundings. Methods. Active region NOAA 12597 was observed on 2016 September 24 with the 1.5-meter GREGOR solar telescope using high-spatial-resolution imaging as well as imaging spectroscopy and near-infrared (NIR) spectropolarimetry. Horizontal proper motions were estimated with local correlation tracking, whereas line-of-sight (LOS) velocities were computed with spectral line fitting methods. The magnetic field properties were inferred with the “Stokes Inversions based on Response functions” (SIR) code for the Si I and Ca I NIR lines. Results. At the time of the GREGOR observations, the leading sunspot had two light bridges indicating the onset of its decay. One of the light bridges disappeared, and an elongated, dark umbral core at its edge appeared in a decaying penumbral sector facing the newly emerging flux. The flow and magnetic field properties of this penumbral sector exhibited weak Evershed flow, moat flow, and horizontal magnetic field. The penumbral gap adjacent to the elongated umbral core and the penumbra in that penumbral sector displayed LOS velocities similar to granulation. The separating polarities of a new flux system interacted with the leading and central part of the already established active region. As a consequence, the leading spot rotated 55° clockwise over 12 h. Conclusions. In the high-resolution observations of a decaying sunspot, the penumbral filaments facing the flux emergence site contained a darkened area resembling an umbral core filled with umbral dots. This umbral core had velocity and magnetic field properties similar to the sunspot umbra. This implies that the horizontal magnetic fields in the decaying penumbra became vertical as observed in flare-induced rapid penumbral decay, but on a very different time-scale.

Towards the next generation of near-infrared spectroscopy

2011 ◽  
Vol 369 (1955) ◽  
pp. 4425-4439 ◽  
Author(s):  
Yoko Hoshi
Keyword(s):  
Infrared Spectroscopy ◽  
Data Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Optical Tomography ◽  
Quantitative Detection ◽  
Next Generation ◽  
Imaging Data ◽  
Wide Range ◽  
Detection Of Signals

Although near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, it has also been developing into a useful tool for neuroimaging studies (functional NIRS). Over the past 30 years, technology has developed and NIRS has found a wide range of applications. However, the accuracy and reliability of NIRS have not yet been widely accepted, mainly because of the difficulties in selective and quantitative detection of signals arising in cerebral tissue, which subject the use of NIRS to a number of practical restrictions. This review summarizes the strengths and advantages of NIRS over other neuroimaging modalities and demonstrates specific examples. The issues of selective quantitative measurement of cerebral haemoglobin during brain activation are also discussed, together with the problems of applying the methods of functional magnetic resonance imaging data analysis to NIRS data analysis. Finally, near-infrared optical tomography—the next generation of NIRS—is described as a potential technique to overcome the limitations of NIRS.

scholarly journals Quality Control of Honey Using New Generation Infrared Spectrometers

2017 ◽  
Vol 5 (4) ◽  
pp. 326 ◽  
Author(s):  
Huseyin Ayvaz
Keyword(s):  
Moisture Content ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Quality Parameters ◽  
Handheld Devices ◽  
Least Squares Regression ◽  
Free Acidity ◽  
Regulatory Limits ◽  
Wide Range ◽  
New Generation

The objective of this study was to develop a rapid infrared technique to determine 10 key quality parameters (sucrose, glucose, fructose, reducing sugar, 5-HMF, °Brix, moisture content, water activity, pH and free acidity) in honey by using new generation portable and handheld devices. The composition of honey samples (n=59) collected from different parts of Turkey was analyzed by using established reference methods, giving wide range of concentrations for each parameter. The levels of sucrose and 5-HMF in some samples were above the established regulatory limits (Codex Alimentarius and European Union standards), indicating possible adulteration or process and storage abuse. Spectra were collected by using portable Fourier-Transformed infrared (FTIR) and handheld NIR (Near Infrared) spectrometers. Partial least squares regression (PLSR) approach was used to correlate the spectral features with compositional reference values, giving strong linear correlation coefficients and standard errors of prediction. Although both systems performed similarly, portable FTIR system was superior in predictions of sucrose, 5-HMF and free acidity while portable NIR system performed noticeably better for °Brix and moisture content. The data indicates that all of the 10 parameters can be measured within the minutes using both systems, providing reliable screening capabilities, flexibility and the potential for in-field applications.

scholarly journals Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China

2020 ◽  
Vol 12 (6) ◽  
pp. 978
Author(s):  
Ding Li ◽  
Kai Qin ◽  
Lixin Wu ◽  
Linlu Mei ◽  
Gerrit de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Eastern China ◽  
Surface Reflectance ◽  
Deep Blue ◽  
Spectral Bands ◽  
Geostationary Meteorological Satellite ◽  
New Generation ◽  
Meteorological Satellite

Himawari-8 (H8), as a new generation geostationary meteorological satellite, has great potential for monitoring the spatial–temporal variation of aerosol properties. However, the large amount of spectral data with differing observation geometries require re-formulation of the surface reflectance correction to utilize this new satellite data. This is achieved by using an improved version of the time series (TS) technique proposed by Mei et al., (2012) based on the assumption that the ratio of the surface reflectance in different spectral bands does not change between any two scan times within an hour. In addition, more suitable aerosol models were adopted, based on cluster analysis of local Aerosol Robotic Network (AERONET) data. The improved TS algorithm (ITS) was applied to retrieve the Aerosol Optical Depth (AOD) over eastern China and the results compare favorably with collocated reference AOD data at eleven sun photometer sites (R > 0.8, Root Mean Square Error (RMSE) < 0.2). Comparison with the H8 official AOD product and with MODIS Dark Target (DT)–Deep Blue (DB) combined AOD data shows the good performance of the ITS method for AOD retrieval with different observation angles.

scholarly journals Subpixel Analysis of Primary and Secondary Infrared Emitters with Nighttime VIIRS Data

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 83
Author(s):  
Christopher D. Elvidge ◽  
Mikhail Zhizhin ◽  
Feng Chi Hsu ◽  
Tamara Sparks ◽  
Tilottama Ghosh
Keyword(s):  
Biomass Burning ◽  
Near Infrared ◽  
Spectral Band ◽  
Source Area ◽  
Short Wave ◽  
Test Case ◽  
Source Areas ◽  
Spectral Bands ◽  
Wide Range ◽  
Spectral Ranges

Biomass burning is a coupled exothermic/endothermic system that transfers carbon in several forms to the atmosphere, ultimately leaving mineral ash. The exothermic phases include flaming and smoldering, which produce the heat that drives the endothermic processes. The endothermic components include pre-heating and pyrolysis, which produce the fuel consumed by flaming and smoldering. These components can be broadly distinguished from each other based on temperature. For several years, we have researched the subpixel analysis of two temperature phases present in fire pixels detected in nighttime VIIRS data. Here, we present the flaming subtractive method, with which we have successfully derived temperatures and source areas for two infrared (IR) emitters and a cooler background. This is developed as an add-on to the existing VIIRS nightfire algorithm version 3 (VNF v.3) which uses Planck curve fitting to calculate temperatures and source areas for a single IR emitter and background. The flaming subtractive method works with data collected in four spectral ranges: near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR) and long-wave infrared (LWIR). With sunlight eliminated, the NIR and SWIR radiances can be fully attributed to the primary IR emitter. The analysis begins with Planck curve modeling for the primary emitter based on the NIR and SWIR radiances, yielding temperature, source area and primary emitter radiances in all spectral bands. The primary emitter radiances are subtracted from each spectral band and then the residual radiance is analyzed for a secondary IR emitter and the background. Spurious results are obtained in pixels lacking a discernable secondary emitter. These misfit pixels revert back to the single IR emitter analysis of VNF v.3. In tests run for two California megafires, we found that the primary emitters straddle the temperature ranges for flaming and smoldering, the exothermic portions of biomass burning, which are apparently commingled on the ground. The secondary emitter temperatures span 350–750 K, corresponding to pre-heating and slow pyrolysis. The natural gas flare test case had few numbers of successful secondary emitter retrievals and a wide range of secondary emitter temperatures. The flaming subtractive analysis is the key addition to VNF version 4, which will commence production later in 2021. In 2022, we will seek validation of the VNF v.4 from nighttime Landsat and other data sources.

scholarly journals PhotothermalPhage: A Virus-Based Photothermal Therapeutic Agent

2021 ◽  
Author(s):  
Arezoo Shahrivarkevishahi ◽  
Michael A. Luzuriaga ◽  
Fabian C. Herbert ◽  
Alisia C. Tumac ◽  
Olivia R. Brohlin ◽  
...  
Keyword(s):  
Biomedical Applications ◽  
Near Infrared ◽  
Therapeutic Agent ◽  
Primary Tumors ◽  
Chemically Modified ◽  
Photothermal Ablation ◽  
Wide Range ◽  
Lysine Residues ◽  
New Generation ◽  
Multifunctional Nanocarriers

ABSTRACT: Virus-like particles (VLPs) are multifunctional nanocarriers that mimic the architecture of viruses. They can serve as a safe platform for specific functionalization and immunization, which provides benefits in a wide range of biomedical applications. In this work, a new generation immunophotothermal agent is developed that adjuvants photothermal ablation using a chemically modified VLP called bacteriophage Qβ. The design is based on the conjugation of near-infrared absorbing croconium dyes to lysine residues located on the surface of Qβ, which turns it to a powerful NIR-absorber called Photothermal Phage. This system can generate more heat upon 808 nm NIR laser radiation than free dye and possesses a photothermal efficiency comparable to gold nanostructures, yet it is biodegradable and acts as an immunoadjuvant combined with the heat it produces. The synergistic combination of thermal ablation with the mild immunogenicity of the VLP leads to effective suppression of primary tumors, reduced lung metastasis, and increased survival time.

scholarly journals Portable near Infrared Spectroscopy as a Tool for Fresh Tomato Quality Control Analysis in the Field

2021 ◽  
Vol 11 (7) ◽  
pp. 3209
Author(s):  
Karla R. Borba ◽  
Didem P. Aykas ◽  
Maria I. Milani ◽  
Luiz A. Colnago ◽  
Marcos D. Ferreira ◽  
...  
Keyword(s):  
Citric Acid ◽  
Near Infrared ◽  
Prediction Models ◽  
Quality Attributes ◽  
Internal Quality ◽  
Control Analysis ◽  
Tomato Quality ◽  
Wide Range ◽  
Different Types ◽  
Fresh Tomato

Portable spectrometers are promising tools that can be an alternative way, for various purposes, of analyzing food quality, such as monitoring in a few seconds the internal quality during fruit ripening in the field. A portable/handheld (palm-sized) near-infrared (NIR) spectrometer (Neospectra, Si-ware) with spectral range of 1295–2611 nm, equipped with a micro-electro-mechanical system (MEMs), was used to develop prediction models to evaluate tomato quality attributes non-destructively. Soluble solid content (SSC), fructose, glucose, titratable acidity (TA), ascorbic, and citric acid contents of different types of fresh tomatoes were analyzed with standard methods, and those values were correlated to spectral data by partial least squares regression (PLSR). Fresh tomato samples were obtained in 2018 and 2019 crops in commercial production, and four fruit types were evaluated: Roma, round, grape, and cherry tomatoes. The large variation in tomato types and having the fruits from distinct years resulted in a wide range in quality parameters enabling robust PLSR models. Results showed accurate prediction and good correlation (Rpred) for SSC = 0.87, glucose = 0.83, fructose = 0.87, ascorbic acid = 0.81, and citric acid = 0.86. Our results support the assertion that a handheld NIR spectrometer has a high potential to simultaneously determine several quality attributes of different types of tomatoes in a practical and fast way.

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