scholarly journals Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula

2017 ◽  
Vol 17 (19) ◽  
pp. 11861-11876 ◽  
Author(s):  
Alberto Cazorla ◽  
Juan Andrés Casquero-Vera ◽  
Roberto Román ◽  
Juan Luis Guerrero-Rascado ◽  
Carlos Toledano ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Signal To Noise Ratio ◽  
Backscatter Coefficient ◽  
Vast Number ◽  
Real Time Processing ◽  
Time Processing ◽  
Dense Networks ◽  
Lidar Measurements ◽  
Aerosol Characterization

Abstract. The interest in the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars; hence, they can be distributed in dense networks over large areas. However, due to the low signal-to-noise ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast number of data generated require an automated and unsupervised method that ensures the quality of the profiles inversions. In this work we describe a method that uses aerosol optical depth (AOD) measurements from the AERONET network that it is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by co-located multiwavelength lidar measurements. A difference smaller than 15 % in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula between 20 and 24 February 2016 is shown. Results reveal that it is possible to obtain quantitative optical aerosol properties (particle backscatter coefficient) and discriminate the quality of these retrievals with ceilometers over large areas. This information has a great potential for alert systems and model assimilation and evaluation.

scholarly journals Near real time processing of ceilometer network data: characterizing an extraordinary dust outbreak over the Iberian Peninsula

2017 ◽  
Author(s):  
Alberto Cazorla ◽  
Juan Andrés Casquero-Vera ◽  
Roberto Román ◽  
Juan Luis Guerrero-Rascado ◽  
Carlos Toledano ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Signal To Noise Ratio ◽  
Network Data ◽  
Backscatter Coefficient ◽  
Real Time Processing ◽  
Time Processing ◽  
Dense Networks ◽  
Lidar Measurements ◽  
Aerosol Characterization

Abstract. The interest on the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars, hence they can be distributed in dense networks over large areas. However, due to the low signal-to-noise-ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast amount of data generated requires an automated and unsupervised method that ensures the quality of the profiles inversions. In this work a method that uses aerosol optical depth (AOD) measurements from the AERONET network is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by co-located multiwavelength lidar measurements and a difference up to 15 % in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak that affected the Iberian Peninsula on 20 February 2016 and lasted until 24 February 2016 is shown. Results reveal that it is possible to obtain a quantitative optical aerosol characterization (particle backscatter coefficient) with ceilometers over large areas and this information has a great potential for alert systems and model assimilation and evaluation.

REAL-TIME PROCESSING OF OIL SPILL REMOTE SENSING DATA1

1987 ◽  
Vol 1987 (1) ◽  
pp. 71-73
Author(s):  
Yvon J. F. Le Guen ◽  
Marc Brussieux ◽  
Rolland Burkhalter
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Oil Spill ◽  
Infrared Emissivity ◽  
Real Time Processing ◽  
Time Processing ◽  
Oil Slick ◽  
Processing Program ◽  
Thermal Infrared Imagery

ABSTRACT The good quality of thermal infrared imagery and the relation between infrared emissivity and the thickness of an oil slick have led to the development of a visualizing rack and an image processing program. This system, tested on board a surveillance aircraft, has permitted on-site estimation within 20 seconds of the total volume of a 28 cubic meter slick with less than 15% error.

scholarly journals Ceilometer aerosol profiling versus Raman lidar in the frame of the INTERACT campaign of ACTRIS

2015 ◽  
Vol 8 (5) ◽  
pp. 2207-2223 ◽  
Author(s):  
F. Madonna ◽  
F. Amato ◽  
J. Vande Hey ◽  
G. Pappalardo
Keyword(s):  
Atmospheric Aerosols ◽  
Signal To Noise Ratio ◽  
Cloud Base ◽  
Raman Lidar ◽  
Backscatter Coefficient ◽  
Lidar Measurements ◽  
Multi Wavelength ◽  
Strong Motivation ◽  
Technological Improvements ◽  
Aerosol Properties

Abstract. Despite their differences from more advanced and more powerful lidars, the low construction and operation cost of ceilometers (originally designed for cloud base height monitoring) has fostered their use for the quantitative study of aerosol properties. The large number of ceilometers available worldwide represents a strong motivation to investigate both the extent to which they can be used to fill in the geographical gaps between advanced lidar stations and also how their continuous data flow can be linked to existing networks of the more advanced lidars, like EARLINET (European Aerosol Research Lidar Network). In this paper, multi-wavelength Raman lidar measurements are used to investigate the capability of ceilometers to provide reliable information about atmospheric aerosol properties through the INTERACT (INTERcomparison of Aerosol and Cloud Tracking) campaign carried out at the CNR-IMAA Atmospheric Observatory (760 m a.s.l., 40.60° N, 15.72° E), in the framework of the ACTRIS (Aerosol Clouds Trace gases Research InfraStructure) FP7 project. This work is the first time that three different commercial ceilometers with an advanced Raman lidar are compared over a period of 6 months. The comparison of the attenuated backscatter coefficient profiles from a multi-wavelength Raman lidar and three ceilometers (CHM15k, CS135s, CT25K) reveals differences due to the expected discrepancy in the signal to noise ratio (SNR) but also due to changes in the ambient temperature on the short and mid-term stability of ceilometer calibration. Therefore, technological improvements are needed to move ceilometers towards operational use in the monitoring of atmospheric aerosols in the low and free troposphere.

scholarly journals ANALYSIS OF VHR IMAGE CLASSIFICATION BY SINGLE AND ENSEMBLE OF CLASSIFIERS

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 37-42
Author(s):  
M. G. Lacerda ◽  
E. H. Shiguemori ◽  
A. J. Damião ◽  
C. S. Anjos ◽  
M. Habermann
Keyword(s):  
Processing Time ◽  
Computational Cost ◽  
Ensemble Classifiers ◽  
Ensemble Of Classifiers ◽  
Real Time Processing ◽  
Time Processing ◽  
Very High ◽  
Classified Image ◽  
Main Factor

Abstract. Given the wide variety of image classifiers available nowadays, some questions remain about the accuracy and processing time of Very High Resolution (VHR) images. Another question concerns the use of a Single or Ensemble Classifiers. Of course, the main factor to consider is the quality of the classified image, but computational cost is also important, especially in applications that require real-time processing. Given this scenario, this paper aims to relate the accuracy of seven single classifiers and the ensemble of the same classifiers with the processing time. In this paper the ensemble of classifiers had the best results in terms of accuracy, however, it comes to processing time, the decision tree had the best performance.

Pre-Processing of Hyperspectral Images Using Nonlinear Filters

2013 ◽  
Vol 11 (1) ◽  
pp. 8-13
Author(s):  
V. Behar ◽  
V. Bogdanova
Keyword(s):  
Signal To Noise Ratio ◽  
Correlation Coefficients ◽  
Hyperspectral Images ◽  
Spectral Correlation ◽  
Edge Preserving ◽  
Improvement Factor ◽  
Filter Output ◽  
Average Improvement ◽  
Processing Procedure

Abstract In this paper the use of a set of nonlinear edge-preserving filters is proposed as a pre-processing stage with the purpose to improve the quality of hyperspectral images before object detection. The capability of each nonlinear filter to improve images, corrupted by spatially and spectrally correlated Gaussian noise, is evaluated in terms of the average Improvement factor in the Peak Signal to Noise Ratio (IPSNR), estimated at the filter output. The simulation results demonstrate that this pre-processing procedure is efficient only in case the spatial and spectral correlation coefficients of noise do not exceed the value of 0.6

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

GPU Acceleration of Algorithm to Design Directional Volumetric Display for Real-time Processing

2019 ◽  
pp. 989
Author(s):  
Daiki Matsumoto ◽  
Ryuji Hirayama ◽  
Naoto Hoshikawa ◽  
Hirotaka Nakayama ◽  
Tomoyoshi Shimobaba ◽  
...  
Keyword(s):  
Real Time ◽  
Gpu Acceleration ◽  
Real Time Processing ◽  
Time Processing ◽  
Volumetric Display
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