Using LiDAR for Classification and

Transcription

1 Using LiDAR for Classification and Recognition of Particulate Matter in the Atmosphere M. Elbakary, K. Iftekharuddin, and K. AFRIFA ECE Dept., Old Dominion University, Norfolk, VA

2 Outline Goals of the Project Introducing the Lidar Optical Parameters of Aerosols Optical Parameters and Classification of Aerosols Collecting Data and Preliminary Results Old Dominion University 2

3 Goals of The Project Upgrade the lidar to measure aerosol depolarization ratio in addition to the color ratio Analyze the lidar data to retrieve aerosol intensive optical parameters (color and depolarization ratios) Detect the presence of vehicles related aerosols (e.g. smoke and soot) in a wide area of atmosphere by using the retrieved optical parameters Investigate correlation between measured PM concentration over large area and traffic flow patterns Old Dominion University 3

4 Lidar A compact light detection and ranging (Lidar) is a remote sensing technology that illuminates a target with a laser and records the reflected light Lidar system is used for the purpose of aerosols profiling by identifying and analyzing the aerosol scattering as function of the altitude Old Dominion University 4

5 Lidar cont. The aerosols profiles (measurements) by Lidar together create images (high intensities referring to high scattering ratios and low intensities referring to low scattering ratios) One profile Many Profiles create an image x-axis is the time and y-axis is the altitude. Old Dominion University 5

6 Altitude -km Lidar cont. Time A typical example for an atmospheric profiling Old Dominion University 6

7 Lidar Description The lidar system is mounted onto an aluminum frame of dimensions 108 cm length, 53 cm width and 76 cm. Old Dominion University 7

8 Lidar Description Lidar has two channels Old Dominion University 8

9 Lidar Description The main components of the Lidar: The laser (two channels: 532 nm and 1064 nm pulses are transmitted collinear into the atmosphere). Voltage supply and cooling system for the laser The receiver (electro-optic system and receiver telescope with 28 cm diameter) Data acquisition system (digitizer installed into computer) LCD monitors allow the lidar aerosol profile to be observed as a function of altitude. The lidar measurements are conducted at wavelengths of 532nm and 1064nm where absorption is negligible and aerosol scattering dominates. Old Dominion University 9

10 Advantages of Lidar Lidar measures aerosols in the atmosphere and can sample aerosols within the lowest 12 km of the atmosphere in microseconds Lidar is easier to move (provides much better spatial and temporal resolution) The lidar system can determine the concentration of emission gases as a function of range, enabling the system to localize the source of emissions The transmitter and receiver is co-located, eliminating the need for the retro-reflector Old Dominion University 10

11 Lidar Equation The lidar equation is a quantitative approach to relate the received energy with the transmitted laser energy, light propagation in background atmosphere, physical interaction between light and objects, and lidar system efficiency and geometry. P z = EC z 2 β a Z + β m Z exp 2 0 z σa z + σ m z dz (1) where P z = the return signal that is proportional to the received power from a scattering volume at slant range Z E = an output energy monitor pulse which is proportional to the transmitted energy C = calibration constant of the instrument β a Z and β m Z = backscattering coefficients of the aerosols and molecules respectively σ a z and σ m z = extinction coefficients of the aerosols and molecules respectively Old Dominion University 11

12 Lidar Equation cont. Lidar observations are supplemented with simultaneous measurements of the total optical depth (that is the degree to which aerosols prevent the transmission of light by absorption or scattering) of the atmosphere. Also, the extinction (that is a measure of light reduction over path length, either by scattering or absorption) is supplemented with the Lidar measurements.. Old Dominion University 12

13 Optical Parameters Aerosols have physical properties such as size, shape, and particle composition. These physical properties can be estimated from the knowledge of the optical properties of the aerosol (aerosols parameters) Extensive aerosol parameters Intensive aerosol parameters Old Dominion University 13

14 Extensive Aerosol Parameters Backscatter coefficient at 532nm and 1064nm Extinction coefficient at 532nm Total column optical depth at 532nm Old Dominion University 14

15 Intensive Aerosol Parameters cont. 1)Backscatter color ratio ( BCR ) is the ratio of the backscatter coefficient of the 532nm channel, β a 532, to the backscatter coefficient of the 1064nm channel,β a 1064, BCR = β a 532 (z) β a 1064 (z) 2)Aerosol lidar ratio, S a, is the ratio of extinction coefficient σ a (z) to the backscatter coefficient β a (z). S a = σ a (z) βa (z) Old Dominion University 15

16 Intensive Aerosol Parameters 3)Aerosol depolarization ratio, δ a, is the ratio of the backscatter coefficient of perpendicular polarization, β, to the backscatter coefficient of parallel polarization, β, δ z = β z /β (z) 4)Spectral depolarization ratio ( SDR ) is the ratio of the aerosol depolarization of the 1064nm channel, δ a 1064, to the aerosol depolarization of the 532nm channel, δ a 532, SDR = δ a 1064 δ a 532 Old Dominion University 16

17 Depolarization Ratio Estimation The digitized signal, Q, stored by the lidar acquisition subsystem is proportional to the received optical power, that is, Q = g. P where g is proportional gain. Therefore the digitized signal in the parallel and perpendicular directions can be written as and (2) (3)

18 Depolarization Ratio Estimation For typical lidar, the digitized parallel and perpendicular signals share several factors in common, we can define the measured ratio of the two signals as Where G = g g is the depolarization gain ratio and δ r = β r / β (r) is the depolarization ratio. All that is necessary is an accurate estimate of G. G =1 in our Lidar because we measure the two signals by the same receiver (we don t use two receivers).

19 Intensive Parameters Vs Extensive Parameters The intensive parameters depend on aerosol type whiles the extensive parameters depend on the aerosol amount. The intensive parameters are related to particulate matter (size, shape, and composition) Old Dominion University 19

20 Physical Properties from Aerosols Parameters Backscatter color ratio is inversely related to aerosol particle sizes. High backscatter color ratio implies that the particles are small and low backscatter color ratio implies the particles being large. Aerosol backscatter color ratio 532nm/1064nm Old Dominion University 20

21 Physical Properties from Aerosols Parameters Depolarization ratio is related to the shape of aerosol particles. The degree of depolarization varies with the shape and increasing the sphericalness of particles decreases their depolarization ratio. Aerosol depolarization ratio 532nm Old Dominion University 21

22 Collecting Data Old Dominion University 22

23 Color and Depolarization Ratios Profiling Preliminary results: Depolarization ratio Preliminary results: Color ratio Old Dominion University 23

24 References [1] Aerosol classification using airborne High Spectral Resolution Lidar measurementsmethodology and examples by S.P. Burton, R.A. Ferrare, C.A. Hostetler, R.R. Rogers, M.D. Obland, C.F. Butler. A.L. Cook, D.B. Harper and K.D. Froyd, 2012 [2] Airborne High Spectral Resolution Lidar for profiling aerosol optical properties by J. W. Hair, C. A. Hostetler, A. L. Cook, D. B. Harper, R. A. Ferrare, T. L. Mack, W. Welch, L. R. Izquierdo and F. E. Hovis, Appl. Optics, 47, page 6743, 2008 [3] Elastic Lidar, Theory, Practice and Analysis Methods by V.A. Kovalev and W.E. Eichinger, pages 33-34, 2004 [4] Determination of Aerosol Height Distribution by Lidar by F.G. Fernald, B.M. Herman and J.A. Reagan, Journal of Applied Meteorology, vol. 11, pages , 1972 [5] Analysis of atmospheric lidar observations: some comments by F.G. Fernald, Appl. Optics, vol. 23, No. 5, 1984 [6]Ali H. Omar and et al, The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm, Journal of Atmosphereic and Oceanic Technology, Vol. 36, [7] S. P. Burton and et al, Aerosol Classification Using Airborne High Spectral Resolution Lidar Measurements Methodology and Examples, Atmos. Meas. Tech. Discuss., September 7, Old Dominion University 24

25 Questions? Old Dominion University 25