Selection of Greenhouse gases Monitoring Instrument channels for CO2 in near infrared band

An international data science challenge, called NEON NIST data science evaluation, was set up in autumn 2017 with the goal to improve the use of remote sensing data in ecological applications. The competition was divided into three tasks: 1) segmentation of tree crowns; 2) data alignment; and 3) tree species classification. In this paper the methods and results of team FEM in the NEON NIST data science evaluation challenge are presented. The individual tree crown (ITC) segmentation (Task 1 of the challenge) was done using a region growing method applied to a near-infrared band of the hyperspectral images. The optimization of the parameters of the segmentation algorithm was done in a supervised way on the basis of the Jaccard score using the training set provided by the organizers. The alignment (Task 2) between the segmented ITCs and the ground measured trees was done using an Euclidean distance among the position, the height, and the crown radius of the ITCs and the ground trees. The classification (Task 3) was performed using a Support Vector Machine classifier applied to a selection of the hyperspectral bands. The selection of the bands was done using a Sequential Forward Floating Selection method and the Jeffries Matusita distance. The results in the three tasks were very promising: team FEM ranked first in Task 1 and 2, and second in Task 3. The segmentation results showed that the proposed approach segmented both small and large crowns. The alignment was correctly done for all the test samples. The classification results were good, even if the accuracy was biased towards the most represented species.

Download Full-text

Air Quality Measurement and Analysis by TROPOMI, OMI, MLS, OMPS, TANSO-FTS , and MERRA-2

10.5194/egusphere-egu21-8076 ◽

2021 ◽

Author(s):

Jane Zeng ◽

Suhung Shen ◽

James Johnson ◽

Andrey Savtchenko ◽

Lena Iredell ◽

...

Keyword(s):

Air Quality ◽

Greenhouse Gases ◽

Near Infrared ◽

Stratospheric Ozone ◽

Environmental Data ◽

Atmospheric Composition ◽

Electromagnetic Spectrum ◽

Monitoring Instrument ◽

Data Collections ◽

Atmospheric Constituent

Global and regional air quality measurements play an important role in the everyday life of people, inasmuch as atmospheric constituents such as ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), methane (CH4), and aerosols may cause severe threats to human health and agriculture productivity. Space-based sensors on satellites are able to detect these atmospheric constituents directly and indirectly at high spatial and temporal scales. The TROPOspheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel-5 Precursor (Sentinel-5P) satellite provides measurements of O3, NO2, SO2, CH4, CO, formaldehyde (HCHO), aerosols, and cloud in ultraviolet-visible (UV-VIS), near infrared (NIR), and shortwave infrared (SWIR) spectral ranges. The Ozone Monitoring Instrument (OMI) aboard the Aura mission measures ozone, aerosols, clouds, surface UV irradiance, and trace gases including NO2, SO2, HCHO, BrO, and OClO using UV electromagnetic spectrum bands. The Ozone Mapping Profiler Suite (OMPS) on the Suomi National Polar-Orbiting Partnership (Suomi-NPP or SNPP) provides environmental data products including O3, NO2, SO2, and aerosols. The Microwave Limb Sounder (MLS) on Aura has been monitoring atmospheric chemical species (CO, volcanic SO2, O3, N2O, BrO), temperature, humidity, and cloud ice since 2004. MLS measurements help understand stratospheric ozone chemistry, and the effects of air pollutants injected into the upper troposphere and low stratosphere. The Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT) covers a wide spectral range from VIS to thermal infrared (TIR), which enables remote observations of the greenhouse gases carbon dioxide (CO2) and CH4. Furthermore, atmospheric constituent data are also available in the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) NASA's atmospheric reanalysis data collection. MERRA-2 uses an upgraded version of the Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system, enhanced with more aspects of the Earth system. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) supports over a thousand data collections in the focus areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability. Some of these data collections include atmospheric composition products from the ongoing TROPOMI, OMI, OMPS, MLS, TANSO-FTS, and MERRA-2 missions and projects. The GES DISC web site (https://disc.gsfc.nasa.gov) provides multiple tools designed to help data users easily search, subset, visualize, and download data from these diverse sources in a unified way. We will demonstrate several methodologies employing these tools to monitor air quality.

Download Full-text

NEON NIST data science evaluation challenge: methods and results of team FEM

10.7287/peerj.preprints.26973 ◽

2018 ◽

Author(s):

Michele Dalponte ◽

Lorenzo Frizzera ◽

Damiano Gianelle

Keyword(s):

Data Science ◽

Near Infrared ◽

Remote Sensing Data ◽

Region Growing ◽

Support Vector ◽

Infrared Band ◽

Species Classification ◽

Individual Tree ◽

Data Alignment ◽

Selection Of

An international data science challenge, called NEON NIST data science evaluation, was set up in autumn 2017 with the goal to improve the use of remote sensing data in ecological applications. The competition was divided into three tasks: 1) segmentation of tree crowns; 2) data alignment; and 3) tree species classification. In this paper the methods and results of team FEM in the NEON NIST data science evaluation challenge are presented. The individual tree crown (ITC) segmentation (Task 1 of the challenge) was done using a region growing method applied to a near-infrared band of the hyperspectral images. The optimization of the parameters of the segmentation algorithm was done in a supervised way on the basis of the Jaccard score using the training set provided by the organizers. The alignment (Task 2) between the segmented ITCs and the ground measured trees was done using an Euclidean distance among the position, the height, and the crown radius of the ITCs and the ground trees. The classification (Task 3) was performed using a Support Vector Machine classifier applied to a selection of the hyperspectral bands. The selection of the bands was done using a Sequential Forward Floating Selection method and the Jeffries Matusita distance. The results in the three tasks were very promising: team FEM ranked first in Task 1 and 2, and second in Task 3. The segmentation results showed that the proposed approach segmented both small and large crowns. The alignment was correctly done for all the test samples. The classification results were good, even if the accuracy was biased towards the most represented species.

Download Full-text

In Vitro High Throughput Phage Display Selection of Ovarian Cancer Avid Phage Clones for Near-Infrared Optical Imaging

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207317666141031152828 ◽

2015 ◽

Vol 17 (10) ◽

pp. 859-867 ◽

Cited By ~ 6

Author(s):

Mette Soendergaard ◽

Jessica Newton-Northup ◽

Susan Deutscher

Keyword(s):

Ovarian Cancer ◽

Phage Display ◽

Optical Imaging ◽

High Throughput ◽

Near Infrared ◽

Selection Of

Download Full-text

Prediction of meat quality traits in the abattoir using portable near-infrared spectrometers: heritability of predicted traits and genetic correlations with laboratory-measured traits

Journal of Animal Science and Biotechnology ◽

10.1186/s40104-021-00555-5 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Simone Savoia ◽

Andrea Albera ◽

Alberto Brugiapaglia ◽

Liliana Di Stasio ◽

Alessio Cecchinato ◽

...

Keyword(s):

Meat Quality ◽

Near Infrared ◽

External Validation ◽

Genetic Correlations ◽

Genetic Selection ◽

Quality Traits ◽

Eye Muscle ◽

Meat Quality Traits ◽

Color Traits ◽

Selection Of

Abstract Background The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. Results The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). Conclusions Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.

Download Full-text

Kinetic Observations on the Near Infrared Band of Cytochrome c Oxidase

Journal of Biological Chemistry ◽

10.1016/s0021-9258(18)97382-5 ◽

1965 ◽

Vol 240 (6) ◽

pp. 2694-2698 ◽

Cited By ~ 5

Author(s):

Quentin H. Gibson ◽

Colin Greenwood

Keyword(s):

Cytochrome C ◽

Cytochrome C Oxidase ◽

Near Infrared ◽

Infrared Band

Download Full-text

The Equivalent Thermal Conductivity of the Micro/Nano Scaled Periodic Cubic Frame Silver and Its Thermal Radiation Mechanism Analysis

Energies ◽

10.3390/en14144158 ◽

2021 ◽

Vol 14 (14) ◽

pp. 4158

Author(s):

Haiyan Yu ◽

Haochun Zhang ◽

Heming Wang ◽

Dong Zhang

Keyword(s):

Thermal Conductivity ◽

Thermal Radiation ◽

Cell Size ◽

Near Infrared ◽

High Porosity ◽

Mechanism Analysis ◽

Infrared Band ◽

Spectral Radiation ◽

Radiation Mechanism ◽

Equivalent Thermal Conductivity

Currently, there are few studies on the influence of microscale thermal radiation on the equivalent thermal conductivity of microscale porous metal. Therefore, this paper calculated the equivalent thermal conductivity of high-porosity periodic cubic silver frame structures with cell size from 100 nm to 100 µm by using the microscale radiation method. Then, the media radiation characteristics, absorptivity, reflectivity and transmissivity were discussed to explain the phenomenon of the radiative thermal conductivity changes. Furthermore, combined with spectral radiation properties at the different cross-sections and wavelength, the radiative transmission mechanism inside high-porosity periodic cubic frame silver structures was obtained. The results showed that the smaller the cell size, the greater radiative contribution in total equivalent thermal conductivity. Periodic cubic silver frames fluctuate more in the visible band and have better thermal radiation modulation properties in the near infrared band, which is formed by the Surface Plasmon Polariton and Magnetic Polaritons resonance jointly. This work provides design guidance for the application of this kind of periodic microporous metal in the field of thermal utilization and management.

Download Full-text

Design of multi-narrowband metamaterial perfect absorbers in near-infrared band based on resonators asymmetric method and modified resonators stacked method

Optics Communications ◽

10.1016/j.optcom.2018.03.051 ◽

2018 ◽

Vol 420 ◽

pp. 95-103 ◽

Cited By ~ 16

Author(s):

Lei Zhao ◽

Han Liu ◽

Zhihong He ◽

Shikui Dong

Keyword(s):

Near Infrared ◽

Infrared Band ◽

Perfect Absorbers

Download Full-text

Restoration method of sootiness mural images based on dark channel prior and Retinex by bilateral filter

Heritage Science ◽

10.1186/s40494-021-00504-5 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Ning Cao ◽

Shuqiang Lyu ◽

Miaole Hou ◽

Wanfu Wang ◽

Zhenhua Gao ◽

...

Keyword(s):

Near Infrared ◽

Environmental Changes ◽

Color Image ◽

Visual Quality ◽

Bilateral Filter ◽

Dark Channel Prior ◽

Infrared Band ◽

Dark Channel ◽

Restoration Method ◽

Pseudo Color

AbstractEnvironmental changes and human activities can cause serious degradation of murals, where sootiness is one of the most common problems of ancient Chinese indoor murals. In order to improve the visual quality of the murals, a restoration method is proposed for sootiness murals based on dark channel prior and Retinex by bilateral filter using hyperspectral imaging technology. First, radiometric correction and denoising through band clipping and minimum noise fraction rotation forward and inverse transform were applied to the hyperspectral data of the sootiness mural to produce its denoised reflectance image. Second, a near-infrared band was selected from the reflectance image and combined with the green and blue visible bands to produce a pseudo color image for the subsequent sootiness removal processing. The near-infrared band is selected because it is better penetrating the sootiness layer to a certain extent comparing to other bands. Third, the sootiness covered on the pseudo color image was preliminarily removed by using the method of dark channel prior and by adjusting the brightness of the image. Finally, the Retinex by bilateral filter was performed on the image to get the final restored image, where the sootiness was removed. The results show that the images restored by the proposed method are superior in variance, average gradient, information entropy and gray scale contrast comparing to the results from the traditional methods of homomorphic filtering and Gaussian stretching. The results also show the highest score in comprehensive evaluation of edges, hue and structure; thus, the method proposed can support more potential studies or sootiness removal in real mural paintings with more detailed information. The method proposed shows strong evidence that it can effectively reduce the influence of sootiness on the moral images with more details that can reveal the original appearance of the mural and improve its visual quality.

Download Full-text