Cheng Fan Li

Shanghai University

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Jun Zhao

Academia Sinica

Fei Liu

Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)

Jing Yin

Beijing University of Civil Engineering and Architecture

Yuan Yuan

Jilin University

Xian Sun

Shanghai University of Engineering Science

Yang Dai

The Synergetic Innovation Center for Advanced Materials

Lan Liu

Henan University

Jin Yuan Yin

Shanghai University

Cooperative Institutions

Shanghai University

Chinese Academy of Sciences

Sun Yat-sen University

Nanjing Tech University

Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)

Beijing Institute of Petrochemical Technology

Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

Nanjing University of Information Science and Technology

Institute of Atmospheric Physics

University of Chinese Academy of Sciences

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Inversion of Aerosol Optical Depth Based on MODIS Remote Sensor

Applied Mechanics and Materials (2015)

Cheng Fan Li Yang Dai Fei Liu Jun Zhao

The remote sensing technology can accurate inverse the aerosol optical depth so as to demonstrate the haze distribution. Taking the moderate resolution imaging spectroradiometer (MODIS) remote sensor data as the data source, the aerosol optical depth of Shanghai area on December 6, 2013 is inversed from the use of second simulation of satellite signal in the solar spectrum (6S) and NASA V5.2 algorithm, and then the formation has already been analyzed from the three aspects of human activities, weather situation and foreign pollutants. The results show that the inversion aerosol optical depth from MODIS remote sensing image gradually decreased mainly from northwest to southeast, and the foreign pollutants plays the leading role in this haze pollution incidents in a certain weather condition. It can provide the references for haze pollution monitoring and early warning using remote sensor data.

Haze

Moderate-resolution imaging spectroradiometer

10.4028/www.scientific.net/amm.738-739.209

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Citations (2)

Spatiotemporal Evolution Simulation of Volcanic Ash Cloud from Remote Sensing Image

Advances in intelligent systems and computing (2019)

Cheng Fan Li Lan Liu Xian Sun Jun Zhao Yuan Yuan

Volcanic ash

10.1007/978-981-13-9406-5_51

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RCS Simulation of Dihedral Corner Reflector Based FEKO

Applied Mechanics and Materials (2013)

Jun Zhao Jin Yuan Yin Cheng Fan Li

CR-InSAR is developing continuously in recent years. It is an important technology in the field of monitoring crustal micro-deformation. Radar cross section of corner reflector is an important work foundation because only radar cross section of artificial corner reflector achieves maximum, it is easier to recognize it from SAR image and increase monitoring accuracy. Dihedral corner reflector is the simplest type in proving ground of Northwest of Beijing; its RCS research is a beneficial attempt helping to build up reasonable corner reflector layout. In the paper, establishing geometric model and subdivision model of dihedral corner reflector are based on FEKO software, and choosing physical optics to simulate RCS. The simulation result is good consistency with theoretical max value. Through analyzing RCS curve, it can help to provide guidance on how to set up corner reflector in the proving ground.

FEKO

Corner reflector

Ground-Penetrating Radar

Reflector (photography)

Radar cross-section

Dihedral angle

10.4028/www.scientific.net/amm.321-324.108

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Citations (2)