FPGA-based data processing module design of on-board radiometric calibration in visible/near infrared bands

2015 ◽  
Author(s):  
Guoqing Zhou ◽  
Chenyang Li ◽  
Tao Yue ◽  
Na Liu ◽  
Linjun Jiang ◽  
...  
Keyword(s):  
Data Processing ◽  
Near Infrared ◽  
Radiometric Calibration ◽  
Module Design ◽  
Processing Module

Detection of cardiovascular drugs and marine toxins using a multifunctional cell-based impedance biosensor system

2015 ◽  
Vol 7 (18) ◽  
pp. 7715-7723 ◽  
Author(s):  
Hongbo Li ◽  
Quchao Zou ◽  
Ling Zou ◽  
Qin Wang ◽  
Kaiqi Su ◽  
...  
Keyword(s):  
Data Processing ◽  
Cardiovascular Drugs ◽  
System Structure ◽  
Marine Toxins ◽  
System P ◽  
Biosensor System ◽  
Processing Module ◽  
Detection Instrument

The system structure of the CIB detection instrument: cell-based impedance biosensor units, hardware module, and data processing module.

scholarly journals Applying satellite images to spectral signature development of maize production (Zea mays L.) under colombia’s middle tropics conditions

ENTRAMADO ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 256-262
Author(s):  
Edier Fernando Ávila Vélez ◽  
Natalia Escobar Escobar ◽  
Carlos Francisco Morantes Choconta
Keyword(s):  
Satellite Images ◽  
Near Infrared ◽  
Spectral Response ◽  
Spectral Signature ◽  
Growth Stages ◽  
Total Production ◽  
Radiometric Calibration ◽  
Maize Crop ◽  
Maize Production ◽  
Production Stages

Maize is currently the world’s second largest crop in terms of production, after wheat and rice. It is the first cereal as for grain yield per hectare and the second, after wheat, regarding total production. Maize has great economic importance worldwide, both as human and/or animal food, and as a source of a large number of industrial products. New digital technologies are allowing greater monitoring of farming production stages. This research developed the spectral signature of maize fields ground covers across different growth stages (2 months, 2.3 months and 4.3 months). Similarly, this research paper proposes the application of a methodology based on four phases: 1. Maize crop georeferencing, 2. Satellite images selection, 3. Radiometric calibration of images 4. Spectral signature development of maize crops. Spectral response or signature of maize crops at visible and near-infrared wavelengths was obtained, indicating significant changes in crops growth. The use of satellite imagery becomes an interesting tool that introduces an approach towards more accurate and controlled monitoring systems in agricultural production.

scholarly journals Multi-group cross section library generation for HTGR lattice physics code XPZ

2021 ◽  
Vol 2048 (1) ◽  
pp. 012028
Author(s):  
Lerui Zhang ◽  
Ding She ◽  
Lei Shi ◽  
Richard Chambon ◽  
Alain Hébert
Keyword(s):  
Data Processing ◽  
Cross Section ◽  
Nuclear Data ◽  
Automatic Generation ◽  
Detailed Data ◽  
Processing Scheme ◽  
Processing Module ◽  
Complete Set ◽  
Evaluated Nuclear Data ◽  
High Temperature Gas

Abstract The XPZ code was previously developed for the lattice physics computation in High Temperature Gas-cooled Reactors (HTGRs), which adopted the multi-group cross section library converted from the existing open-source DRAGON library. In this paper, a new format of multi-group cross section library named XPZLIB has been implemented in XPZ code. XPZLIB is designed in binary and HDF5 formats, including detailed data contents for resonance, transport and depletion calculations. A new data-processing module named XPZR is developed based on NJOY-2016 to generate nuclide dependent XPZLIB from the most recent evaluated nuclear data, and besides, the PyNjoy-2016 system is developed for automatic generation of integrated XPZLIB including a complete set of nuclides. The new generated XPZLIB is presented with the XPZ code. Numerical results demonstrate the accuracy of the new library XPZLIB and the reliability of the data processing scheme. Moreover, the influence of different versions of ENDF/B data is investigated.

scholarly journals Acoustic Detection Module Design of a Quartz-Enhanced Photoacoustic Sensor

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1093 ◽  
Author(s):  
Tingting Wei ◽  
Hongpeng Wu ◽  
Lei Dong ◽  
Frank Tittel
Keyword(s):  
Near Infrared ◽  
Tuning Fork ◽  
Quartz Tuning Fork ◽  
Acoustic Detection ◽  
Numerous Application ◽  
Mid Infrared ◽  
Module Design ◽  
Laser Sources ◽  
Infrared Laser Sources ◽  
Reliability And Robustness

This review aims to discuss the latest advancements of an acoustic detection module (ADM) based on quartz-enhanced photoacoustic spectroscopy (QEPAS). Starting from guidelines for the design of an ADM, the ADM design philosophy is described. This is followed by a review of the earliest standard quartz tuning fork (QTF)-based ADM for laboratory applications. Subsequently, the design of industrial fiber-coupled and free-space ADMs based on a standard QTF for near-infrared and mid-infrared laser sources respectively are described. Furthermore, an overview of the latest development of a QEPAS ADM employing a custom QTF is reported. Numerous application examples of four QEPAS ADMs are described in order to demonstrate their reliability and robustness.

scholarly journals Coastal Dune Vegetation Mapping Using a Multispectral Sensor Mounted on an UAS

2019 ◽  
Vol 11 (15) ◽  
pp. 1814 ◽  
Author(s):  
Suo ◽  
McGovern ◽  
Gilmer
Keyword(s):  
High Resolution ◽  
Data Processing ◽  
Spatial Patterns ◽  
Near Infrared ◽  
Environmental Changes ◽  
Vegetation Mapping ◽  
Coastal Dune ◽  
Sensor Data ◽  
Surface Model ◽  
Dune Vegetation

Vegetation mapping, identifying the type and distribution of plant species, is important for analysing vegetation dynamics, quantifying spatial patterns of vegetation evolution, analysing the effects of environmental changes and predicting spatial patterns of species diversity. Such analysis can contribute to the development of targeted land management actions that maintain biodiversity and ecological functions. This paper presents a methodology for 3D vegetation mapping of a coastal dune complex using a multispectral camera mounted on an unmanned aerial system with particular reference to the Buckroney dune complex in Co. Wicklow, Ireland. Unmanned aerial systems (UAS), also known as unmanned aerial vehicles (UAV) or drones, have enabled high-resolution and high-accuracy ground-based data to be gathered quickly and easily on-site. The Sequoia multispectral sensor used in this study has green, red, red edge and near-infrared wavebands, and a regular camer with red, green and blue wavebands (RGB camera), to capture both visible and near-infrared (NIR) imagery of the land surface. The workflow of 3D vegetation mapping of the study site included establishing coordinated ground control points, planning the flight mission and camera parameters, acquiring the imagery, processing the image data and performing features classification. The data processing outcomes included an orthomosaic model, a 3D surface model and multispectral imagery of the study site, in the Irish Transverse Mercator (ITM) coordinate system. The planimetric resolution of the RGB sensor-based outcomes was 0.024 m while multispectral sensor-based outcomes had a planimetric resolution of 0.096 m. High-resolution vegetation mapping was successfully generated from these data processing outcomes. There were 235 sample areas (1 m × 1 m) used for the accuracy assessment of the classification of the vegetation mapping. Feature classification was conducted using nine different classification strategies to examine the efficiency of multispectral sensor data for vegetation and contiguous land cover mapping. The nine classification strategies included combinations of spectral bands and vegetation indices. Results show classification accuracies, based on the nine different classification strategies, ranging from 52% to 75%.

scholarly journals Radiometric Calibration of UAV Remote Sensing Image with Spectral Angle Constraint

2019 ◽  
Vol 11 (11) ◽  
pp. 1291 ◽  
Author(s):  
Kaiqiu Xu ◽  
Yan Gong ◽  
Shenghui Fang ◽  
Ke Wang ◽  
Zhiheng Lin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Linear Method ◽  
Radiometric Calibration ◽  
Constraint Condition ◽  
Infrared Band ◽  
Spectral Bands ◽  
Quantitative Remote Sensing ◽  
Spectral Channels ◽  
Spectral Angle

In recent years, the acquisition of high-resolution multi-spectral images by unmanned aerial vehicles (UAV) for quantitative remote sensing research has attracted more and more attention, and radiometric calibration is the premise and key to the quantification of remote sensing information. The traditional empirical linear method independently calibrates each channel, ignoring the correlation between spectral bands. However, the correlation between spectral bands is very valuable information, which becomes more prominent as the number of spectral channels increases. Based on the empirical linear method, this paper introduces the constraint condition of spectral angle, and makes full use of the information of each band for radiometric calibration. The results show that, compared with the empirical linear method, the proposed method can effectively improve the accuracy of radiometric calibration, with the improvement range of Mean Relative Percent Error (MRPE) being more than 3% in the range of visible band and within 1% in the range of near-infrared band. Besides, the method has great advantages in agricultural remote sensing quantitative inversion.

scholarly journals High-Speed Data Processing Module for LLRF

2015 ◽  
Vol 62 (3) ◽  
pp. 1083-1090 ◽  
Author(s):  
D. Makowski ◽  
A. Mielczarek ◽  
P. Perek ◽  
A. Napieralski ◽  
L. Butkowski ◽  
...  
Keyword(s):  
Data Processing ◽  
High Speed ◽  
Processing Module ◽  
High Speed Data
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