New dust aerosol identification method for spaceborne lidar measurements

Journal of Quantitative Spectroscopy and Radiative Transfer

Volumn 112, Issue 2, 2011, Pages 338-345

  Ma, Yingying ^a   Gong, Wei ^a   Wang, Pucai ^b   Hu, Xiuqing ^c  

^a WUHAN UNIVERSITY   (China)

^b INSTITUTE OF ATMOSPHERIC PHYSICS   (China)

^c NATIONAL SATELLITE METEOROLOGICAL CENTER   (China)

Author keywords

Aerosol; CALIPSO; Cloud; SVM (the support vector machine)

Indexed keywords

BACKSCATTER LIDAR; BACKSCATTER PROFILES; CALIPSO; CRITICAL STEPS; DUST AEROSOLS; DUST STORM; IDENTIFICATION METHOD; SPACE-BORNE LIDAR; SVM CLASSIFIERS; TAKLIMAKAN DESERT;

ARID REGIONS; BACKSCATTERING; CLOUDS; DATA PROCESSING; DISTRIBUTION FUNCTIONS; DUST; OPTICAL RADAR; STORMS; SUPPORT VECTOR MACHINES;

ATMOSPHERIC AEROSOLS;

AEROSOL; BACKSCATTER; CALIPSO; CLOUD; DATA PROCESSING; DUST STORM; IDENTIFICATION METHOD; LIDAR; PROBABILITY DENSITY FUNCTION;

EID: 78649493744     PISSN: 00224073     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jqsrt.2010.08.004     Document Type: Article

References (14)

1. Yumimoto K., Uno I., Sugimoto N., Shimizu A., Liu Z.Y., Winker D.M. Adjoint inversion modeling of Asian dust emission using lidar observation. Atmos Chem Phys 2008, 8:2869-2884.
2. Myhre G, Stordal F, Johnsrud M, Diner DJ, Geogdzhayev IV, Haywood JM, et al. Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000. Atmos Chem Phys 2008; 4: 8201-8244.
3. Chu D.A., Kaufman Y.J., Ichoku C., Remer L.A., Tanré D., Holben B.N. Validation of MODIS aerosol optical depth retrieval over land. Geophys Res Lett 2002, 29(12). MOD2. 10.1029/2001GL013205.
4. Winker D.M., Pelon J., McCormick M.P. The CALIPSO mission: spaceborne lidar for observation of aerosols and clouds. Proc SPIE 2003, 4893:1-11.
5. Liu Z.Y., Liu D., Huang J.P., Vaughan M., Uno I., Sugimoto N., et al. Airborne dust distributions over the Tibetan Plateau and surrounding areas derived from the first year of CALIPSO lidar observations. Atmos Chem Phys 2008, 8:5957-5977.
6. Liu Z.Y., Voelger P., Sugimoto N. Simulations of the observation of clouds and aerosols with the Experimental Lidar in Space Equipment system. Appl Opt 2000, 39:3120-3137.
7. Vaughan MA, Young SA, Winker DM. Fully automated analysis of space-based lidar data: an overview of the CALIPSO retrieval algorithms and data products. Laser radar techniques for atmospheric sensing, Gran Canaria, Spain, 2004.
8. Stephens G.L., Vane D.G., Boain R.J., Mace G.G., Sassen K., Wang Z., et al. The CloudSat mission and the A-Train. Bull Am Meteorol Soc 2002, 83:1771-1790.
9. Barnes W., Xiong X., Salomonson V. Status of Terra MODIS and Aqua MODIS. Adv Space Res 2003, 32(11):2099-2106.
10. Bösenberg J, Timm R, Wulfmeyer V. Study on retrieval algorithms for a backscatter lidar. Final report, no. 226, Max-Planck-Institut für Meteorologie, Hamburg, 1997.
11. Liu Z.Y., Vaughan M.A., Winker D.M., Hostetler CA, Poole LR, Hlavka D, et al. Use of probability distribution functions for discriminating between cloud and aerosol in lidar backscatter data. J Geophys Res Atmos 2004, 109:D15202. 10.1029/2004JD004732.
12. Pal M., Mather P. Support vector machines for classification in remote sensing. Int J Remote Sensing 2005, 26(5):1007-1011.
13. Gunn SR. Support vectors machines for classification and regression. Technical report, Image Speech and Intelligent Systems Research Group, University of Southampton, 1997. Available from: http://www.isis.ecs.soton.ac.uk/resource/svminfo/.
14. Liu Z., Vaughan M.A., Winker D.M., Kittaka C., Kuehn R.E., Getzewich B.J., et al. The CALIPSO Lidar Cloud and aerosol discrimination: version 2 algorithm and initial assessment of performance. J Atmos Oceanic Technol 2009, 26:1198-1213. 10.1175/2009JTECHA1229.1.