Atmospheric Remote Sensing 3: Atmospheric Polarization Characteristics and Multi-angular Three-Dimensional Chromatography

Author(s):  
Lei Yan ◽  
Bin Yang ◽  
Feizhou Zhang ◽  
Yun Xiang ◽  
Wei Chen
2006 ◽  
Vol 63 (2) ◽  
pp. 712-725 ◽  
Author(s):  
Likun Wang ◽  
Kenneth Sassen

Abstract The first quantitative and statistical evaluation of cirrus mammatus clouds based on wavelet analysis of remote sensing data is made by analyzing the University of Utah Facility for Atmospheric Remote Sensing (FARS) 10-yr high-cloud dataset. First, a case study of cirrus mammata combining a high-resolution lidar system and a W-band Doppler radar is presented, yielding an assessment of the thermodynamic environment and dynamic mechanisms. Then, 25 cirrus mammatus cases selected from the FARS lidar dataset are used to disclose their characteristic environmental conditions, and vertical and length scales. The results show that cirrus mammata occur in the transition zone from moist (cloudy) to dry air layers with weak wind shear, which suggests that cloud-induced thermal structures play a key role in their formation. Their maximum vertical and horizontal length scales vary from 0.3 to 1.1 km and 0.5 to 8.0 km, respectively. It is also found that small-scale structures develop between the large-scale protuberances. The spectral slopes of the lidar-returned power and mean radar Doppler velocity data extracted from the cirrus cloud-base region further indicate the presence of developed three-dimensional, locally isotropic, homogeneous turbulence generated by buoyancy. Finally, comparisons of anvil and cirrus mammata are made. Although both are generated in a similar environment, cirrus mammata generally do not form fallout fronts like their anvil counterparts, and so do not have their smooth and beautiful outlines.


Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 951-960
Author(s):  
Haiqing Zhang ◽  
Jun Han

Abstract Traditionally, three-dimensional model is used to classify and recognize multi-target optical remote sensing image information, which can only identify a specific class of targets, and has certain limitations. A mathematical model of multi-target optical remote sensing image information classification and recognition is designed, and a local adaptive threshold segmentation algorithm is used to segment multi-target optical remote sensing image to reduce the gray level between images and improve the accuracy of feature extraction. Remote sensing image information is multi-feature, and multi-target optical remote sensing image information is identified by chaotic time series analysis method. The experimental results show that the proposed model can effectively classify and recognize multi-target optical remote sensing image information. The average recognition rate is more than 95%, the maximum robustness is 0.45, the recognition speed is 98%, and the maximum time-consuming average is only 14.30 s. It has high recognition rate, robustness, and recognition efficiency.


2013 ◽  
Vol 295-298 ◽  
pp. 2437-2441
Author(s):  
Xue Mei Yin ◽  
Qiu Yang Ma ◽  
Xue Hong Wu ◽  
Yi Gong ◽  
Yan Li Lu

The calculation of the gas radiation process plays an important role in the study of atmospheric remote sensing and climatic effects of greenhouse gas. The remote sensing of rocket plume has important significance for early warning, interception, detection, identification and tracking of flight vehicle. A model was established to calculate the remote sensing signal of rocket plume by wide band k-distribution, the liquid rocket plume remote sensing signals in atmospheric window region and the detectors’ working spectrum are calculated, and the results were compared with the results calculated by line-by-line approach. The results showed that in some of the detectors’ working spectral regions, the wide band k-distribution model can be used for the calculation of the remote sensing of liquid rocket engine exhaust plume.


1988 ◽  
Author(s):  
Supriya Chakrabarti ◽  
Richard Link ◽  
G. Randall Gladstone

2015 ◽  
Vol 9 (1) ◽  
pp. 1-11
Author(s):  
Gábor Bakó ◽  
Gábor Kovács ◽  
Zsolt Molnár ◽  
Judit Kirisics ◽  
Eszter Góber ◽  
...  

The red mud disaster occurred on 4th October 2010 in Hungary has raised the necessity of rapid intervention and drew attention to the long-term monitoring of such threat. Both the condition assessment and the change monitoring indispensably required the prompt and detailed spatial survey of the impact area. It was conducted by several research groups - independently - with different recent surveying methods. The high spatial resolution multispectral aerial photogrammetry is the spatially detailed (high resolution) and accurate type of remote sensing. The hyperspectral remote sensing provides more information about material quality of pollutants, with less spatial details and lower spatial accuracy, while LIDAR ensures the three-dimensional shape and terrain models. The article focuses on the high spatial resolution, multispectral electrooptical method and the evaluation methodology of the deriving high spatial resolution ortho image map, presenting the derived environmental information database


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