Laser Diodes as Reliable Pump Source for Space-Borne Methane Remote Sensing Lidar System

Author(s):  
K. Häusler ◽  
R. Staske ◽  
A. Maaßdorf ◽  
P. Ressel ◽  
C. Stölmacker ◽  
...  
2018 ◽  
Vol 176 ◽  
pp. 07002
Author(s):  
Guangyu Zhao ◽  
Ming Lian ◽  
Yiyun Li ◽  
Zheng Duan ◽  
Shiming Zhu ◽  
...  

A versatile mobile remote sensing system for multidisciplinary environmental monitoring tasks on the Chinese scene is described. The system includes a 20 Hz Nd:YAG laser-pumped dye laser, optical transmitting/receiving systems with a 30 cm and a 40 cm Newtonian telescope, and electronics, all integrated in a laboratory, installed on a Jiefang truck. Results from field experiments on atomic mercury DIAL mapping and remote laser-induced fluorescence and break-down spectroscopy are given.


Author(s):  
Oleg A. Romanovskii ◽  
Yaroslav O. Romanovskii ◽  
Sergey A. Sadovnikov ◽  
Olga V. Kharchenko ◽  
Semyon Vladimirovich Yakovlev

Author(s):  
Jian Yang ◽  
Wei Gong ◽  
Shuo Shi ◽  
Lin Du ◽  
Jia Sun ◽  
...  

Laser-induced fluorescence (LIF) served as an active technology has been widely used in many field, and it is closely related to excitation wavelength (EW). The objective of this investigation is to discuss the performance of different EWs of LIF LiDAR in identifying plant species. In this study, the 355, 460 and 556 nm lasers were utilized to excite the leaf fluorescence and the fluorescence spectra were measured by using the LIF LiDAR system built in the laboratory. Subsequently, the principal component analysis (PCA) with the help of support vector machine (SVM) was utilized to analyse fluorescence spectra. For the three EWs, the overall identification rates of the six plant species were 80 %, 83.3 % and 90 %. Experimental results demonstrated that 556 nm excitation light source is superior to 355 and 460 nm for the classification of the plant species for the same genus in this study. Thus, an appropriate excitation wavelength should be considered when the LIF LiDAR was utilized in the field of remote sensing based on the LIF technology.


2021 ◽  
Author(s):  
Oleg A. Romanovskii ◽  
Sergey A. Sadovnikov ◽  
Semyon V. Yakovlev ◽  
Dmitry A. Tuzhilkin ◽  
Ol'ga V. Kharchenko ◽  
...  

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