scholarly journals Sky Quality Meter and satellite correlation for night cloud-cover analysis at astronomical sites

2020 ◽  
Vol 493 (2) ◽  
pp. 2463-2471 ◽  
Author(s):  
S Cavazzani ◽  
S Ortolani ◽  
A Bertolo ◽  
R Binotto ◽  
P Fiorentin ◽  
...  
Keyword(s):  
Real Time ◽  
Cloud Cover ◽  
Large Data ◽  
Temporal Analysis ◽  
Observation Time ◽  
Astronomical Observation ◽  
Cloud Detection ◽  
Night Time ◽  
Total Percentage ◽  
A Site

ABSTRACT The analysis of night cloud cover is very important for astronomical observations in real time, considering a typical observation time of about 15 minutes, and to provide statistics. In this article, we use the Sky Quality Meter (SQM) for high-resolution temporal analysis of the La Silla and Asiago (Ekar Observatory) sky: 3 and 5 minutes respectively. We investigate the annual temporal evolution of the natural contributions of the sky at a site not influenced by artificial light at night (ALAN) and at one highly influenced. We also make a correlation between GOES and Aqua satellite data and ground-based SQM data to confirm the relationship between the SQM data and cloud cover. We develop an algorithm that allows the use of the SQM for night cloud detection and reach correlations with the nighttime cloud cover detected by the GOES and Aqua satellites of 97.2 per cent at La Silla and 94.6 per cent at Asiago. Our algorithm also classifies photometric (PN) and spectroscopic nights (SN). We measure 59.1 per cent PN and 21.7 per cent SN for a total percentage of clear nights of 80.8 per cent at La Silla in 2018. The respective Ekar Observatory values are 31.1 per cent PN, 24.0 per cent SN and 55.1 per cent of total clear night time. Application to the SQM network would involve the development of long-term statistics and large data forecasting models for site testing and real-time astronomical observation.

scholarly journals Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites

2021 ◽  
Vol 13 (9) ◽  
pp. 1627
Author(s):  
Chermelle B. Engel ◽  
Simon D. Jones ◽  
Karin J. Reinke
Keyword(s):  
Real Time ◽  
Infrared Imaging ◽  
Night Time ◽  
Clear Link ◽  
Radiative Power ◽  
Biogeographical Region ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fire Radiative Power

This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.

scholarly journals Caffeine may disrupt the impact of real-time drowsiness on cognitive performance: a double-blind, placebo-controlled small-sample study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
E. Aidman ◽  
M. Balin ◽  
K. Johnson ◽  
S. Jackson ◽  
G. M. Paech ◽  
...  
Keyword(s):  
Real Time ◽  
Cognitive Performance ◽  
Small Sample ◽  
Night Time ◽  
Double Blind ◽  
Infra Red ◽  
Procedural Decisions ◽  
Performance Gains ◽  
The Impact ◽  
Modest Reduction

AbstractCaffeine is widely used to promote alertness and cognitive performance under challenging conditions, such as sleep loss. Non-digestive modes of delivery typically reduce variability of its effect. In a placebo-controlled, 50-h total sleep deprivation (TSD) protocol we administered four 200 mg doses of caffeine-infused chewing-gum during night-time circadian trough and monitored participants' drowsiness during task performance with infra-red oculography. In addition to the expected reduction of sleepiness, caffeine was found to disrupt its degrading impact on performance errors in tasks ranging from standard cognitive tests to simulated driving. Real-time drowsiness data showed that caffeine produced only a modest reduction in sleepiness (compared to our placebo group) but substantial performance gains in vigilance and procedural decisions, that were largely independent of the actual alertness dynamics achieved. The magnitude of this disrupting effect was greater for more complex cognitive tasks.

Real-Time Web GIS Analysis Using WebGL

2012 ◽  
Vol 1 (3) ◽  
pp. 49-61 ◽  
Author(s):  
Michael Auer
Keyword(s):  
Parallel Processing ◽  
Real Time ◽  
Large Data ◽  
Web Gis ◽  
3D Graphics ◽  
Gis Analysis ◽  
User Interactions ◽  
Algorithm Performance ◽  
Gis Applications ◽  
Client Side

Parallel processing methods in Geographic Information Systems (GIS) are traditionally used to accelerate the calculation of large data volumes with sophisticated spatial algorithms. Such kinds of acceleration can also be applied to provide real-time GIS applications to improve the responsiveness of user interactions with the data. This paper presents a method to enable this approach for Web GIS applications. It uses the JavaScript 3D graphics API (WebGL) to perform client-side parallel real-time computations of 2D or 2.5D spatial raster algorithms on the graphics card. The potential of this approach is evaluated using an example implementation of a hillshade algorithm. Performance comparisons of parallel and sequential computations reveal acceleration factors between 25 and 100, mainly depending on mobile or desktop environments.

scholarly journals Seasonal cycle of cloud cover analyzed using Meteosat images

1998 ◽  
Vol 16 (3) ◽  
pp. 331-341 ◽  
Author(s):  
J. Massons ◽  
D. Domingo ◽  
J. Lorente
Keyword(s):  
Spatial Resolution ◽  
Seasonal Cycle ◽  
Cloud Cover ◽  
High Spatial Resolution ◽  
Detection Method ◽  
Cloud Amount ◽  
Cloud Detection ◽  
Total Cloud Amount ◽  
Cloud Parameters ◽  
Cloud Properties

Abstract. A cloud-detection method was used to retrieve cloudy pixels from Meteosat images. High spatial resolution (one pixel), monthly averaged cloud-cover distribution was obtained for a 1-year period. The seasonal cycle of cloud amount was analyzed. Cloud parameters obtained include the total cloud amount and the percentage of occurrence of clouds at three altitudes. Hourly variations of cloud cover are also analyzed. Cloud properties determined are coherent with those obtained in previous studies.Key words. Cloud cover · Meteosat

Design of FPGA-Based Missile-Borne Image Acquisition and Storage Recorder

2015 ◽  
Vol 713-715 ◽  
pp. 1448-1451
Author(s):  
Lin Lu ◽  
Yan Feng Zhang ◽  
Xiao Feng Li
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Storage System ◽  
Large Data ◽  
Engineering Practice ◽  
Image Storage ◽  
Video Images ◽  
Stable Performance ◽  
And Storage ◽  
Time Image

The high-altitude missile and other special application occasions have requirements on image storage system, such as small size, high storage speed, low temperature resistance, etc. Commonly used image storage system in the market cannot meet such requirement. In the paper, real-time image storage system solutions on missile based on FPGA should be proposed. The system mainly consists of acquisition module and memory reading module. The whole system adopts FPGA as main control chip for mainly completing real-time decoding and acquisition on one path of PAL format video images, reading and writing of NandFlash chipset, erasure, bad block management and so on. The solution has passed various environmental tests with stable performance, large data storage capacity and easy expansion, which has been used in engineering practice.

scholarly journals PSIX-24 Comparison of serial real-time A-mode vs. B-mode ultrasound fat depth measures on prediction of final carcass value endpoints

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 332-332
Author(s):  
Chandler A Dockray ◽  
Tommy L Perkins ◽  
Flavio Riberio ◽  
Tylo J Kirkpatrick ◽  
Kaitlyn R Wesley ◽  
...  
Keyword(s):  
Real Time ◽  
Feeding Period ◽  
Ultrasound Scanning ◽  
Marbling Score ◽  
Trenbolone Acetate ◽  
Total Percentage ◽  
Ultrasound Measurements ◽  
Fat Thickness ◽  
Growth Promoting ◽  
Positive Correlations

Abstract Charolais x Angus steers (n = 80) were evaluated across a 378-day feeding period in response to administration of a growth promoting implant containing trenbolone acetate (TBA) and estradiol (E2) using A-mode and B-mode ultrasound. Steers were scanned at 42-d intervals (0, 42, 84, 126, 168, 210, 252, 294, 336) during 10 separate ultrasound scanning sessions 24-h prior to harvest. Ultrasound B-mode rump fat images (BRFU) were obtained by a certified Ultrasound Guidelines Council (UGC) technician using an ALOKA 500V console equipped with a 17.2 cm carcass probe. Ultrasound A-mode images (ARFU) were obtained by a non-UGC certified technician using a RENCO Lean Meater. Images of BRFU were analyzed by the CUP lab whereas ARFU image results were determined chute side by the scanning technician. Carcasses were dissected into total lean, fat and bone post-harvest. Rump fat thickness ultrasound measurements were compared to carcass traits used to determine carcass value. Carcass endpoints included 12th–rib fat thickness (FTC), 12th rib-eye area (REAC), marbling score (MARB), and total percentage of carcass fat (PCF). The correlation between BRFU and ARFU was 0.70 (P < 0.01). Positive correlations (P < 0.01) between ultrasound rump fat measures taken the day before harvest and carcass measurements indicated moderate relationships between BRFU and FTC (r=0.80); BRFU and REAC (r=0.66); BRFU and MARB (r=0.68); BRFU and PCF (r=0.75); ARFU and FTC (r=0.69); ARFU and REAC (r=0.76); ARFU and MARB (r=0.79); and ARFU and PCF (r=0.80). These results indicate A- and B-mode ultrasound measures of rump fat may be adequate measures for estimation of total percent carcass fat.

scholarly journals AN OPTIONAL THRESHOLD WITH SVM CLOUD DETECTION ALGORITHM AND DSP IMPLEMENTATION

2016 ◽  
Vol XLI-B8 ◽  
pp. 771-777 ◽  
Author(s):  
Guoqing Zhou ◽  
Xiang Zhou ◽  
Tao Yue ◽  
Yilong Liu
Keyword(s):  
Real Time ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Svm Classifier ◽  
Detection Accuracy ◽  
Landsat 8 ◽  
Cloud Detection ◽  
Threshold Method ◽  
Dsp Implementation ◽  
Svm Algorithm

This paper presents a method which combines the traditional threshold method and SVM method, to detect the cloud of Landsat-8 images. The proposed method is implemented using DSP for real-time cloud detection. The DSP platform connects with emulator and personal computer. The threshold method is firstly utilized to obtain a coarse cloud detection result, and then the SVM classifier is used to obtain high accuracy of cloud detection. More than 200 cloudy images from Lansat-8 were experimented to test the proposed method. Comparing the proposed method with SVM method, it is demonstrated that the cloud detection accuracy of each image using the proposed algorithm is higher than those of SVM algorithm. The results of the experiment demonstrate that the implementation of the proposed method on DSP can effectively realize the real-time cloud detection accurately.

scholarly journals Waterborne illness and injury: a feasibility study of a site-specific predictive model for beach water quality at Beachway Park in the City of Burlington

2021 ◽  
Author(s):  
Ramien Sereshk
Keyword(s):  
Water Quality ◽  
Predictive Model ◽  
Real Time ◽  
Site Specific ◽  
E Coli ◽  
Time Basis ◽  
A Site ◽  
Persistence Model ◽  
Beach Water Quality ◽  
Beach Water

It is commonly assumed that the persistence model, using day-old monitoring results, will provide accurate estimates of real-time bacteriological concentrations in beach water. However, the persistence model frequently provides incorrect results. This study: 1. develops a site-specific predictive model, based on factors significantly influencing water quality at Beachway Park; 2. determines the feasibility of the site-specific predictive model for use in accurately predicting near real-time E. coli levels. A site-specific predictive model, developed for Beachway Park, was evaluated and the results were compared to the persistence model. This critical performance evaluation helped to identify the inherent inaccuracy of the persistence model for Beachway Park, which renders it an unacceptable approach for safeguarding public health from recreational water-borne illnesses. The persistence model, supplemented with a site-specific predictive model, is recommended as a feasible method to accurately predict bacterial levels in water on a near real-time basis.

Towards a continuous NASA cloud climate data record from MODIS to VIIRS

2021 ◽  
Author(s):  
Kerry Meyer ◽  
Steven Platnick ◽  
Robert Holz ◽  
Steven Ackerman ◽  
Andrew Heidinger ◽  
...  
Keyword(s):  
Observation Time ◽  
Radiometric Calibration ◽  
Cloud Detection ◽  
Climate Data ◽  
Cloud Data ◽  
Microphysical Properties ◽  
Data Record ◽  
Climate Data Record ◽  
Relative Radiometric Calibration

<p>The Suomi NPP and JPSS series VIIRS imagers provide an opportunity to extend the NASA EOS Terra (20+ year) and Aqua (18+ year) MODIS cloud climate data record into the new generation NOAA operational weather satellite era. However, while building a consistent, long-term cloud data record has proven challenging for the two MODIS sensors alone, the transition to VIIRS presents additional challenges due to its lack of key water vapor and CO<sub>2</sub> absorbing channels available on MODIS that are used for high cloud detection and cloud-top property retrievals, and a mismatch in the spectral location of the 2.2µm shortwave infrared channels on MODIS and VIIRS that has important implications on inter-sensor consistency of cloud optical/microphysical property retrievals and cloud thermodynamic phase. Moreover, sampling differences between MODIS and VIIRS, including spatial resolution and local observation time, and inter-sensor relative radiometric calibration pose additional challenges. To create a continuous, long-term cloud climate data record that merges the observational records of MODIS and VIIRS while mitigating the impacts of these sensor differences, a common algorithm approach was pursued that utilizes a subset of spectral channels available on each imager. The resulting NASA CLDMSK (cloud mask) and CLDPROP (cloud-top and optical/microphysical properties) products were publicly released for Aqua MODIS and SNPP VIIRS in early 2020, with NOAA-20 (JPSS-1) VIIRS following in early 2021. Here, we present an overview of the MODIS-VIIRS CLDMSK and CLDPROP common algorithm approach, discuss efforts to monitor and address relative radiometric calibration differences, and highlight early analysis of inter-sensor cloud product dataset continuity.</p>

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