The Inference on the Results of Atmospheric Environment Prediction by the Different Cloud Data

2014 ◽  
Vol 1010-1012 ◽  
pp. 329-332
Author(s):  
Xian Lin Meng ◽  
Xiao Hui Cao ◽  
Shi You Guo
Keyword(s):  
Relative Error ◽  
Atmospheric Environment ◽  
Weather Station ◽  
Cloud Data ◽  
Climatological Station ◽  
Aermod Model ◽  
Project Location ◽  
Environmental Prediction

In order to provide reference for using the different cloud data in environmental prediction, based on AERMOD model, the standard cloud scenario and the reference cloud scenarios were constructed by using the 2010 reference climatological station-observed data and general weather station-observed data, and the d index and relative error on pollutant prediction concentration between the reference cloud scenarios and the standard cloud scenario were analyzed. The results show that the 4 or 3 observational cloud data of the project location, or less than 50km or more than 50km to the project location can be used in atmospheric environment prediction.

scholarly journals ENVIRONMENTAL INFLUENCES ON THE STABILITY OF A PERMANENTLY INSTALLED LASER SCANNER

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 745-752
Author(s):  
M. Kuschnerus ◽  
D. Schröder ◽  
R. Lindenbergh
Keyword(s):  
Systematic Error ◽  
Point Cloud ◽  
Laser Scanner ◽  
Weather Station ◽  
Point Cloud Data ◽  
Cloud Data ◽  
The Mean ◽  
The Stability ◽  
The Impact ◽  
Mean Square Errors

Abstract. The advancement of permanently measuring laser scanners has opened up a wide range of new applications, but also led to the need for more advanced approaches on error quantification and correction. Time-dependent and systematic error influences may only become visible in data of quasi-permanent measurements. During a scan experiment in February/March 2020 point clouds were acquired every thirty minutes with a Riegl VZ-2000 laser scanner, and various other sensors (inclination sensors, weather station and GNSS sensors) were used to survey the environment of the laser scanner and the study site. Using this measurement configuration, our aim is to identify apparent displacements in multi-temporal scans due to systematic error influences and to investigate data quality for assessment of geomorphic changes in coastal regions. We analyse scan data collected around two storm events around 09/02/2020 (Ciara) and around 22/02/2020 (Yulia) and derive the impact of heavy storms on the point cloud data through comparison with the collected auxiliary data. To investigate the systematic residuals on data acquired by permanent laser scanning, we extracted several stable flat surfaces from the point cloud data. From a plane fitted through the respective surfaces of each scan, we estimated the mean displacement of each plane with the respective root mean square errors. Inclination sensors, internal and external, recorded pitch and roll values during each scan. We derived a mean inclination per scan (in pitch and roll) and the standard deviation from the mean as a measure of the stability of the laser scanner during each scan. Evaluation of the data recorded by a weather station together with knowledge of the movement behaviour, allows to derive possible causes of displacements and/or noise and correction models. The results are compared to independent measurements from GNSS sensors for validation. For wind speeds of 10 m/s and higher, movements of the scanner considerably increase the noise level in the point cloud data.

scholarly journals Comparação de Modelos de Estimativa da Radiação de Onda Curta a partir de dados MODIS/Terra (Comparision Models for estimating the Shortwave Radiation from MODIS / Terra data)

2013 ◽  
Vol 6 (5) ◽  
pp. 1037 ◽  
Author(s):  
Francineide Amorim Santos ◽  
Bernardo Barbosa da Silva ◽  
Argemiro Lucena Araújo ◽  
Madson Tavares Silva ◽  
Alexandra Chaves Braga
Keyword(s):  
Relative Humidity ◽  
Key Words ◽  
Relative Error ◽  
Air Temperature ◽  
Cane Sugar ◽  
Dew Point ◽  
Shortwave Radiation ◽  
Weather Station ◽  
Error Percentage ◽  
Relative Humidity Data

O objetivo do presente estudo é analisar a precisão de diferentes metodologias na estimativa da radiação de onda curta incidente a partir de dados MODIS/TERRA em diferentes ecossistemas (cerrado e cana-de-açúcar). Foram utilizados três métodos que se convencionou denominar SEBAL (S), METRIC (M) e Bisht (B). Para aplicação do método SEBAL são necessários apenas dados de temperatura do ar e para o METRIC, de temperatura do ar e umidade relativa, dados que são facilmente obtidos em estações meteorológicas. A metodologia Bisht, porém, processou-se de forma totalmente autônoma, pois a temperatura do ar, assim como a temperatura do ponto do orvalho, foram obtidas de dados MODIS. O método que demonstrou maior precisão foi Bisht, com erro relativo percentual (ERP) de 3,94% no Cerrado e de 7,6% na cana-de-açúcar, seguido do METRIC e do SEBAL. No entanto, o METRIC foi o que proporcionou melhor correlação entre observações versus estimativas para a área do cerrado (R2 = 0,897) contra R2 = 0,847 do Bisht. Já para a área de cana-de-açúcar, o Bisht apresentou melhor correlação (R2 = 0,772), enquanto a correlação obtida com o METRIC foi de 0,744. A B S T R A C T The objective of this study is to analyze the accuracy of different methodologies to estimate the incident shortwave radiation from MODIS / TERRA in different ecosystems (savanna and cane sugar). Were used three methods that been conventionally called SEBAL (S), METRIC (M) and Bisht (B). To apply the method SEBAL requires only data of air temperature and for the METRIC, air temperature and relative humidity, data that are easily obtained from weather station. The methodology Bisht, however, was processed in a totally autonomous because the air temperature as well as the temperature of the dew point, were obtained from MODIS data. The method Bisht demonstrated greater accuracy, with relative error percentage (REP) of 3.94% in the Cerrado and 7.6% in cane sugar, followed by METRIC and SEBAL. However, METRIC was what provided the best correlation between observations versus estimates for the area of cerrado (R2 = 0.897) against R2 = 0.847 the Bisht. Already for the area of cane sugar, Bisht showed better correlation (R2 = 0.772), whereas the correlation with the METRIC obtained was 0.744. Key-Words: ecosystem, methodologies, accuracy, autonomous

scholarly journals Variability and Trends in U.S. Cloud Cover: ISCCP, PATMOS-x, and CLARA-A1 Compared to Homogeneity-Adjusted Weather Observations

2015 ◽  
Vol 28 (11) ◽  
pp. 4373-4389 ◽  
Author(s):  
Bomin Sun ◽  
Melissa Free ◽  
Hye Lim Yoo ◽  
Michael J. Foster ◽  
Andrew Heidinger ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Ground Truth ◽  
Weather Station ◽  
Surface Solar Radiation ◽  
Cloud Data ◽  
Long Term Stability ◽  
Station Data ◽  
Weather Observations ◽  
Avhrr Data

Abstract Variability and trends in total cloud cover for 1982–2009 across the contiguous United States from the International Satellite Cloud Climatology Project (ISCCP), AVHRR Pathfinder Atmospheres–Extended (PATMOS-x), and EUMETSAT Satellite Application Facility on Climate Monitoring Clouds, Albedo and Radiation from AVHRR Data Edition 1 (CLARA-A1) satellite datasets are assessed using homogeneity-adjusted weather station data. The station data, considered as “ground truth” in the evaluation, are generally well correlated with the ISCCP and PATMOS-x data and with the physically related variables diurnal temperature range, precipitation, and surface solar radiation. Among the satellite products, overall, the PATMOS-x data have the highest interannual correlations with the weather station cloud data and those other physically related variables. The CLARA-A1 daytime dataset generally shows the lowest correlations, even after trends are removed. For the U.S. mean, the station dataset shows a negative but not statistically significant trend of −0.40% decade−1, and satellite products show larger downward trends ranging from −0.55% to −5.00% decade−1 for 1984–2007. PATMOS-x 1330 local time trends for U.S. mean cloud cover are closest to those in the station data, followed by the PATMOS-x diurnally corrected dataset and ISCCP, with CLARA-A1 having a large negative trend contrasting strongly with the station data. These results tend to validate the usefulness of weather station cloud data for monitoring changes in cloud cover, and they show that the long-term stability of satellite cloud datasets can be assessed by comparison to homogeneity-adjusted station data and other physically related variables.

Application of pyrometer and standard sample to determine surface temperature of studied materials

2019 ◽  
pp. 9-13
Author(s):  
V.Ya. Mendeleyev ◽  
V.A. Petrov ◽  
A.V. Yashin ◽  
A.I. Vangonen ◽  
O.K. Taganov
Keyword(s):  
Composite Material ◽  
Surface Temperature ◽  
Relative Error ◽  
Wavelength Range ◽  
Standard Sample ◽  
A Priori ◽  
Temperature Changes ◽  
Surface Temperatures ◽  
Relative Errors ◽  
Normal Emissivity

Determining the surface temperature of materials with unknown emissivity is studied. A method for determining the surface temperature using a standard sample of average spectral normal emissivity in the wavelength range of 1,65–1,80 μm and an industrially produced Metis M322 pyrometer operating in the same wavelength range. The surface temperature of studied samples of the composite material and platinum was determined experimentally from the temperature of a standard sample located on the studied surfaces. The relative error in determining the surface temperature of the studied materials, introduced by the proposed method, was calculated taking into account the temperatures of the platinum and the composite material, determined from the temperature of the standard sample located on the studied surfaces, and from the temperature of the studied surfaces in the absence of the standard sample. The relative errors thus obtained did not exceed 1,7 % for the composite material and 0,5% for the platinum at surface temperatures of about 973 K. It was also found that: the inaccuracy of a priori data on the emissivity of the standard sample in the range (–0,01; 0,01) relative to the average emissivity increases the relative error in determining the temperature of the composite material by 0,68 %, and the installation of a standard sample on the studied materials leads to temperature changes on the periphery of the surface not exceeding 0,47 % for composite material and 0,05 % for platinum.

Registration and Fusion of UAV LiDAR System Sequence Images and Laser Point Clouds

2020 ◽  
Author(s):  
Jiayong Yu ◽  
Longchen Ma ◽  
Maoyi Tian, ◽  
Xiushan Lu
Keyword(s):  
Point Cloud ◽  
Image Data ◽  
Point Clouds ◽  
Optical Image ◽  
Point Cloud Data ◽  
Feature Points ◽  
Lidar System ◽  
Registration Accuracy ◽  
Cloud Data ◽  
Intensity Image

The unmanned aerial vehicle (UAV)-mounted mobile LiDAR system (ULS) is widely used for geomatics owing to its efficient data acquisition and convenient operation. However, due to limited carrying capacity of a UAV, sensors integrated in the ULS should be small and lightweight, which results in decrease in the density of the collected scanning points. This affects registration between image data and point cloud data. To address this issue, the authors propose a method for registering and fusing ULS sequence images and laser point clouds, wherein they convert the problem of registering point cloud data and image data into a problem of matching feature points between the two images. First, a point cloud is selected to produce an intensity image. Subsequently, the corresponding feature points of the intensity image and the optical image are matched, and exterior orientation parameters are solved using a collinear equation based on image position and orientation. Finally, the sequence images are fused with the laser point cloud, based on the Global Navigation Satellite System (GNSS) time index of the optical image, to generate a true color point cloud. The experimental results show the higher registration accuracy and fusion speed of the proposed method, thereby demonstrating its accuracy and effectiveness.

Control Cloud Data Access Privilge Anonymity with Attributed Based Encryption

2017 ◽  
Vol 7 (8) ◽  
pp. 279
Author(s):  
P. Sudheer ◽  
T. Lakshmi Surekha
Keyword(s):  
Data Privacy ◽  
Low Cost ◽  
Data Access ◽  
Privacy Concerns ◽  
Cloud Data ◽  
Computing Paradigm ◽  
Attribute Based Encryption ◽  
Data Content ◽  
Identity Privacy ◽  
Cloud Servers

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been to secure the cloud storage. Data content privacy. A semi anonymous privilege control scheme AnonyControl to address not only the data privacy. But also the user identity privacy. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. The  Anonymity –F which fully prevent the identity leakage and achieve the full anonymity.

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