Share Email Print
cover

Proceedings Paper

Methodology of dimensionless multiplicative decomposition for atmospheric lidar evaluation
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In the present paper, we show application examples of united generalized methodology for atmospheric lidar assessment, which uses the dimensionless-parameterization as a core component. It is based on a series of our previous works where the problem of universal parameterization over many lidar technologies were described and analyzed from different points of view. A methodology of spatial-angular filtering efficiency was used for comparison of different receiving system designs on the criterion of stability against background radiation. The dimensionless parameterization concept applied to photodetectors of remote sensing instruments allowed predicting the lidar receiver performance in presence of sky background. The approach can be widely used to evaluate a broad range of lidar system capabilities for a variety of lidar remote sensing applications, as well as to serve as a basis for selection of appropriate lidar system parameters for a specific application. Such a methodology provides generalized, uniform and objective approach for the evaluation of a broad range of lidar types and systems (aerosol, Raman, DIAL), operating on different targets (backscatter or topographic) and under intense sky background conditions, and can be used within the lidar community to compare different lidar instruments.

Paper Details

Date Published: 3 October 2006
PDF: 7 pages
Proc. SPIE 6367, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II, 63670R (3 October 2006); doi: 10.1117/12.683886
Show Author Affiliations
Ravil Agishev, Kazan State Technical Univ. (Russia)
Barry Gross, City College of the City Univ. of New York (United States)
Adolfo Comeron, Polytechnic Univ.of Catalonia (Spain)


Published in SPIE Proceedings Vol. 6367:
Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II
Upendra N. Singh, Editor(s)

© SPIE. Terms of Use
Back to Top