Lunacruz_atmospheric Processing Sarp Presentation

Atmospheric Processing for MASTER Imagery using Chemical Transport Models and MODTRAN4

Daniel S. Tkacik Department of Earth and Atmospheric Sciences, Georgia Institute of Technology   Yaítza Luna-Cruz NOAA Center for Atmospheric Sciences, Howard University

Outlin e

Introducti TOA solar irradiance on 3 b

3 a

2 b

2 a

1

RS Satellite TOA radiance to sensor Transmitte d Radiation Scattered or Reflected Radiation

Verhoef, 2008

Backgrou Target bynda remote sensor

The signal detected is the result of three main radiative contributions. 1. Atmosphere 2. Target 3. Background

Motivati onplace a Atmospheric effects

bias on remote sensing measurements, preventing the “true” surface measurements from being retrieved remotely. In order to account for this bias, an “atmospheric correction” must be implemented to constrain atmospheric effects and produce unaltered, more accurate results.

Objecti ve: Constrain atmospheric effects over

Monterey Bay and implement the correction in the retrieval of surface-relevant parameters in order to assess its impact.

Data and Steps forMethodology Atmospheric processing: Convert sensor data in radiance units Atmospheric Model to estimate atmospheric properties Establish Relationships (TRa and SRe) Derive Reflectance from target Radiance

The analysis. Running and processing the outpu data. Acquisition of MODTRAN initialization parameters. Selection of point of interest.

Selection of Point of Interest

MASTER True Color C

Flight Track Map

Monterey Bay, CA Lat: 36 57’ 34.99” N, Long: 121 56’ 2.32” W Date: 22/07/2009 Time start: 23:48:43, Time end: 23:53:31 DC-8 Flight Number: 09-010-00 MODIS/ASTER airborne simulator (MASTER) image: MM09-010-00-C

Data and Methodology

The analysis. Running and processing the outpu data. Acquisition of MODTRAN initialization parameters. Selection of point of interest.

MODTRAN4: Brief Introduction

MODTRAN: MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model ü Developed by Air Force Research Labs (AFRL) in collaboration with Spectral Sciences, Inc. (SSI). ü Used to model the spectral absorption, transmission, emission, and scattering characteristics of the atmosphere. - Accomplished by modeling the atmosphere as a set of horizontaly homogeneous layers.

MODTRAN Interface ü A MODTRAN interface was used to simplify the use

of MODTRAN by providing a graphical user interface for the creation of input files.

MODTRAN4: Initialization

Atmospheric Models and Observations 18-layer vertical profiles of model

meteorological conditions were extracted in the Weather Research and Forecasting model (WRF) v. 2.2. ü ü ü ü

Pressure Temperature Dew point Wind speed

Using the STEM-2K3 chemical transport model [Carmichael et al., 2003], in conjunction with WRF meteorology, gas concentrations at each vertical layer were extracted. ü O3 ü ü ü ü ü

CO NO SO2 NO2 NH3

Atmospheric Models and Observations

Example of a tape5 file – Mod/Obs Gas Settings, Radiance Mode

Data and Methodology

The analysis. Running and processing the outpu data. Acquisition of MODTRAN initialization parameters. Selection of point of interest.

Running MODTRAN 4

Tape 7

Processing Output Data Dr. Nick Clinton processes the MODTRAN4 output data (.tp7 files)

Processing Output Techniques from Data Verhoef and Bach, 2003 were implemented in the generation of six atmospheric parameters that describe the alteration of groundemitted and –reflected radiation by atmospheric effects.

Six Atmospheric Parameters ü Derived from MODTRAN4 runs for each wavelength ü Describe the interaction of the whole atmosphere with the land surface.

Data and Methodology

The analysis. Running and processing the outpu data. Acquisition of MODTRAN initialization parameters. Selection of point of interest.

Resul ts Comparison of two sets of results: (3)“Default” gas settings (2) “Input” (mod/obs) gas

Results: Simulated Transmittance

Results: ENVI

ENVI is an environmental imaging program used to process and analyze geospatial imagery. ü “Band Math”, a special tool in ENVI, is used to input equations for surface properties and

Resul True Color Default ts True Color Mod/Obs Gases Gases

Differences üNo visible differences were found in the true color images.

Temperat Temp Default ure Temp Mod/Obs Gases Gases Up nadir

Cente r

Left off nadir Down

Right off nadir

nadir

Differences: ü Default gases retrieved higher temperatures than the model/observations gases. ü C (0.14%), UN (0.29%), DN (0.24%), LON (0.36%) and RON (0.07%)

Normalized Difference Vegetation Index (NDVI) measure that directly relate the photosynthetic

A capacity and hence energy absorption of plant canopies.

NDVI = NIR – Red NIR + Red

Characteristics: ü(0.3 – 0.8) – dense vegetation canopy üNegative values – clouds and snow üLow positive values – free standing water ü(0.1 – 0.2) – soils

Differences

NDVI

Resul NDVI Mod/Obs NDVI Default ts Gases Gases

üInput gases predict higher NDVI than default gases üDifference greater over the greatest NDVI üNDVI is saturated at high values LAI üSeparation of high-reflectance pixels is possible

with

Fluorescence Line Height (FLH) relative measure of the amount of radiance

A leaving the sea surface in the chlorophyll fluorescence emission band, which is presumably a result of chlorophyll fluorescence. 

FLH = L6 – {L7 +(L5 – L7) *[( 5)] Characteristics: üNegative at low concentrations

or

nil

7

-

6)/( 7

chlorophyll

-

Resul FLH Default ts Gases

FLH Mod/Obs Gases

Differences ü Visible difference but the difference does not yield different conclusion

Conclusi ons Applying an “Atmospheric Correction” to MASTER data makes a difference in the reflectance– some large, some small. “Correction” allows for the ability to distinguish between pixels with strong signals, notably in the retrieval of NDVI. MASTER’s temperature “correction”.

overestimation of can be explained

surface through

Future Work & Recommendations

Improve atmospheric profile retrieval methods. Validate with in-situ measurements. Apply “correction” to many cases to gain knowledge of its sensitivity to different input parameters as well as how the resulting reflectance data affect surface properties (FLH, NDVI, etc.)

Referen ces

Carmichael, G.R., et al. (2003). Regional-scale chemical transport modeling in support of intensive field experiments: overview and analysis of the TRACE-P observations. Journal of Geophysical Research 10.1029/2002JD003117. Carter, W.P.L. (2000). Documentation of the SAPRC-99 chemical mechanism for VOC reactivity assessment. Final Report to the California Air Resources Board, Contracts 9232 and 95-308, Riverside, CA (available at http://www.engr.ucr.edu/~carter/absts.htm#saprc99). CGRER (2008). ARCTAS emissions data (available at http://www.cgrer.uiowa.edu/arctas/emission.html). Streets, D. G., et al. (2003), An inventory of gaseous and primary aerosol emissions in Asia in the year 2000, J. Geophys. Res., 108(D21), 8809, doi:10.1029/2002JD003093. D. Schläpferand D. Odermatt, Manual, ReSe, Version 3, (2006).

MODTRAN for Remote Sensing Applications User

Letelier, R.M. and M.R. Abbott, An analysis of chlorophyll fluorescence algorithms for the moderate resolution imaging spectrometer (MODIS)Rem. Sens. Environ. 58, 215-223 (1996). Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang and J. G. Powers (2005). A Description of the Advanced Research WRF Version 2. NCAR Technical Note (available at http://wrf-model.org/wrfadmin/docs/arw_v2.pdf). S.M. Adler-Golden, M.W. Matthew, L.S. Bernstein, R.Y. Levine, A. Berk, S.C. Richtsmeier, P.K. Acharya, G.P. Anderson, G. Felde, J. Gardner, M. Hoke, L.S. Jeong, B. Pukall, J. Mello, A. Ratkowski, and H.-H. Burke, Atmospheric Correction for Short-wave Spectral Imagery based on MODTRAN4, SPIE Proceeding, Imaging Spectrometry V, Volume 3753 (1999).

Acknowledgem NASA NSERC… ents For the opportunity and for fully supporting this research.

SARP Staff…Alexandra, Barbara, Jane, John, Don, Shawn, Walter, David, Scott, Rick and George… For all your help and making this experience fun and educational! MASTER Team especially Nick … For all the grunt work that we didn’t have to do. SARP students ... Pa’ arriba, pa’ bajo, pal centro y pa’ dentro…

¡Gracias!

Questions? "If we knew what it was we were doing, it would not be called research, would it?" Albert Einstein