3.7 AEROSOL RETRIEVALS OVER LAND SURFACES (THE ADVANTAGES OF POLARIZATION)

Brian Cairns∗ , Larry Travis, Michael I. Mishchenko and Jacek ChowdharyNASA Goddard Institute for Space Studies, New York, NY

∗ Corresponding author address: Brian Cairns, ColumbiaUniversity, 2880 Broadway, Room 762 MC 0201, NewYork NY 10025; email: bc25@columbia.edu.

1. INTRODUCTION

The principal difficulties in retrieving aerosolloadings and microphysical properties using passiveremote sensing measurements over land surfaces arethe significant spectral and spatial variations in theobserved intensities that are caused by the land surface.Indeed the unique and highly variable spectralsignatures of land surfaces and their rapid spatialvariations are of considerable value in geologicalprospecting and crop identification and evaluation [Asner1998]

The polarized light reflected by surfaces may alsobe of use in remote sensing of the surface, beingindicative of its roughness, or in the case of vegetationits leaf inclination distribution [Rondeaux and Herman1991]. It is believed that this polarization is generated atthe surface interface and this hypothesis has been usedto develop theoretical models [Bréon et. al. 1995] for thepolarized reflectance of vegetation and of bare soils. Thefact that most surface polarization is generated at thesurface interface and that the refractive index of naturaltargets varies little within the spectral domain of interestsuggests that surface polarized reflectance will bespectrally neutral.

If this is the case, then the use of a measurement ata sufficiently long wavelength that the aerosol load isnegligible could be used to characterize and correct forsurface polarization effects at the shorter wavelengths.Such an approach has also been suggested for use withintensity measurements [Kaufman et. al. 1997] based onthe observation that surface reflectances at 450 and670nm are correlated with reflectances at 2250nm formany surface types. The shorter wavelengths can thenbe used to estimate the aerosol load and microphysicalproperties, for example size and refractive index. Atheoretical examination of such an approach based onthe assumption that the surface polarized reflectance isspectrally neutral has been performed elsewhere [Cairnset. al. 1997]. In this paper we examine the validity ofassuming that surface polarized reflectance is spectrallyneutral and the capabilit ies of polarizationmeasurements for remote sensing of aerosols over landsurfaces using data from the Research ScanningPolarimeter. We also indicate how these measurementsrelate to the type of empirical surface models that havebeen developed for use in retrieving aerosol propertiesover land surfaces from POLDER measurements.

2. DESCRIPTION OF INSTRUMENTATION ANDMETHODS

The Research Scanning Polarimeter (RSP) makespolarization measurements in nine spectral bands. Inthe visible/near infrared (VNIR) blue enhanced siliconphotodiodes are used to make measurements in sixspectral bands at 410, 470, 555, 670, 865 and 960nm.In the short wave infrared (SWIR) HgCdTe detectorscooled to 150K are used to make measurements in threespectral bands at 1590, 1880 and 2250nm. The opticalsystem consists of six boresighted refractive telescopes.Each telescope makes measurements in three spectralbands of two orthogonal polarization states which arespatially separated using a Wollaston prism. Telescopesthat measure the same three spectral bands are pairedso that the orientation of the polarization measurement inone is rotated 45° with respect to the other. This meansthat the Stokes parameters Q and U are measuredsimultaneously, Q in one telescope and U in the other.The instantaneous field of view (14mrad) of eachtelescope is scanned continuously with data being takenover a range of 120° (±60° from nadir) using apolarization-insensitive system. This system consists oftwo mirrors each used at 45° angle of incidence and withtheir planes of incidence oriented orthogonally to eachother. During the course of a scan 152 samples aretaken plus ten dark samples with a sample dwell time of1.875msec. The polarimetric accuracy is better than0.2% and the radiometric accuracy is 3.5% [Cairns et al.1999]. This is based on pre- and post-flight reflectancecalibrations using a spectralon reflectance standard andnearby Multi-Filter Rotating Shadowband Radiometer(MFRSR) data for an atmospheric transmission estimate.The MFRSR measures the intensity of the direct beam ofthe sun and diffuse skylight at six bands: 410, 500, 610,670, 865 and 945nm. These measurements allow for arobust estimate of the column ozone, aerosol opticaldepth and size of the accumulation mode and columnwater vapor.

The RSP instrument was deployed in a Cessna 210aircraft which allowed along-track measurements over arange of ±45° from nadir to be obtained before theaircraft skin vignetted the scan. By having the RSP scanalong the groundtrack, as the aircraft moves forward, thesame point at the ground is seen from multiple viewangles. The aircraft altitude was 3000m and the speedwas 50m/s. An MFRSR instrument was deployed on theground near Oxnard CA., and the aircraft data that weshow here was obtained simultaneously with that from

the sunphotometer and is located within 2km of it. Themeasurements were all taken on 10/14/1999..

3. DATA ANALYSIS AND DISCUSSION

The RSP instrument counts were corrected for darkcurrent and reduced to calibrated reflectances. Thesereflectance measurements contain contributions fromboth the surface and the atmosphere. The atmosphericcontribution is well characterized by the MFRSRmeasurements, which provide accurate estimates ofaerosol optical depth and allow a plausible aerosolmicrophysical model to be inferred. The atmosphericreflectance was then calculated using a vectoradding/doubling code [Cairns et. al. 1997]. The modelatmosphere that is used consists of a two layeratmosphere with a pure molecular layer above theaircraft and an aerosol layer mixed with the remainingmolecular contribution below the aircraft. The verticaldistribution of scattering properties is reasonable for thesuppressed boundary layer that was observed and theaerosol properties were defined by the MFRSRmeasurements. The calculated atmospheric reflectancewas then used to correct the RSP measuredreflectances so that they provide a reasonable estimateof the surface reflectance [Hu et. al. 1999], particularlyfor the low aerosol load (optical depth of 0.14 at 550nm)on 10/14/1999.

a

In Fig. 1 we show scatter plots of theseatmospherically corrected RSP reflectances. Themeasurements come from a 4km segment of flight trackand represent a range of scattering geometries andsurface types with approximately 20,000 measurementsfor each wavelength. In Fig. 1a we show 2250 nmreflectances plotted against the 410, 470 and 670 nmreflectances. The solid lines are based on robustregressions of the 2250 nm reflectance against thevisible reflectances.

b

Figure 1. RSP measurements that have been atmosphericallycorrected based on simultaneous MFRSR measurements.Symbols and lines are offset to allow different bands to bedistinguished. a) Reflectance at 2250nm versus reflectancemeasurements at 410, 470 and 670 nm (ordered from bottom totop). b) Polarized reflectance at 2250nm versus polarizedreflectance measurements at 410, 470, 555, 670 and 865 nm(ordered from bottom to top).

Although the measurements are grouped aboutthese regression lines there is a considerable spreadand it appears that the measurements might representtwo different populations. Fig. 1b shows the polarizedreflectance at 2250nm plotted against the polarizedreflectance at 410, 470, 555, 670 and 865 nm, with solidlines showing the 1:1 line. As can be seen themeasurements are strongly clustered about thetheoretically predicted lines. It should be emphasizedthat these lines are not empirical regressions, but arebased on our understanding that most of the polarizedreflectance from surfaces is generated at the surface airinterface and is therefore determined mostly by the realrefractive index of the material. Since the real refractiveindices of soils and leaves show only weak spectralvariation the polarized reflectance also shows weakspectral variation as demonstrated by Fig. 1b whichshows little variation in polarized surface reflectancebetween 410 and 2250nm.

We will now examine how well the atmosphericreflectance signal can be estimated using the regressionrelations shown in Fig. 1a and how well the polarizedatmospheric reflectance signal can be estimated usingthe physically based relations shown in Fig. 1b. Fig. 2ashows how well the atmospheric reflectance calculatedbased on MFRSR measurements agrees with theatmospheric reflectance measured by the RSP when thesurface contribution is removed using a regressionrelation between the reflectance at 2250nm and that at410, 470 and 670nm [Kaufman et. al. 1997]. As can beseen the agreement is poor. It is certainly possible to findsurface types for which the this approach is valid, but itappears to depend on surface type (i.e. particularly

vegetation type and coverage) and would therefore tendto however uncontrollable seasonal and regional biases.

a

b

Figure 2. RSP measurements that have been corrected forsurface reflectance: a) Atmospheric reflectances that have beencorrected based on the empirical regression model of surfacereflectance (symbols) compared with model calculations basedon MFRSR measurements (solid lines). b) Polarizedatmospheric reflectances that have been corrected for thesurface contribution based on polarized reflectancemeasurements at 2250nm (symbols) compared with modelcalculations based on MFRSR measurements (solid lines).

In contrast the agreement in Fig. 2b between thesimulated polarized reflectances (solid lines) and theRSP measurements corrected for surface polarization,using the 2250nm measurements as a proxy for theactual surface polarized reflectance, is excellent. Thisagreement is true at a pixel level for each pixel (notshown). The dot-dashed lines shown in Fig. 2b aresimulations of the atmospheric polarized reflectancewhen the effective radius of the aerosol model is

perturbed by ±0.05µm from its best estimate value of0.185µm. Comparing these perturbed values with theRSP measurements indicates a sensitivity to aerosolsize, at least for accumulation mode particles, of±0.05µm for downward looking polarizationmeasurements over land.

3. SIMPLE SURFACE POLARIZATION MODELS

Although the results shown above indicate that theassumption that surfaces generate polarization mostly atthe surface-air interface is valid, a separate andimportant question is whether simple models that havebeen developed to link Fresnel reflection coefficientswith the surface polarized reflectance are valid. When ameasurement at 2250nm is not available to characterizesurface polarization it becomes necessary to havereliable surface polarization models that areparameterized based on the surface type and itsvegetation cover, or some other appropriate measure[e.g. Normalized Difference Vegetation Index (NDVI)].These models can then be used to correct observedpolarized reflectances for the surface contribution andtherefore allow aerosol properties to be estimated. Suchan approach has been developed, with encouragingresults, for the analysis of POLDER measurements[Nadal and Bréon 1999]. They found that the originalsimple physical models that had been developed [Bréonet. al. 1995] were not valid and indeed found that nearthe backscatter direction the observed polarizedreflectance was four times larger than that predicted by asimple physical model. Their empirical model (I) for thepolarized reflectance RP is defined by the expression

where FP is simply the polarized Fresnel reflectioncoefficient for the given viewing geometry, Ωv is theviewing zenith [µv =cos(Ωv)] and Ωs is the solar zenithangle. r and ß are the empirical coefficients that aretuned to provide a good match to observations and thatcan then be predicted based on surface type and NDVI.

Above is shown an alternative empirical model (II) for avegetated surface where the S functions allow forshadowing with ß being an empirical coefficient that isindicative of surface roughness and r is an empiricallytunable coefficient, which based on simple theory shouldbe 1/4. The empirical model I of Nadal and Breon, whichis shown as a dashed line in Fig.3, is based on theempirical coefficients for a "low vegetation, high NDVI"case (3a) and on the empirical coefficients for a "desert"case (3b). Based on the preceding analysis the 2250nmpolarized reflectance measurements are a reasonableapproximation to the surface polarized reflectance. Theempirical model I provides a reasonable fit for vegetation(3a) and a somewhat worse fit for bare soil (3b). Thismay simply be because a desert model is notappropriate for a bare soil field. The empirical model II(solid line) fits the data extremely well in both cases.

R rF

P v sP v s

v s( , , ) exp

( , , )Ω Ω Ω Ωϕ β ϕµ µ

= − −+

1 (1)

R r

S S FP v s

v s P v s

v s( , , )

( , ) ( , ) ( , , )Ω Ω Ω Ω Ω Ωϕ β β ϕµ µ

=+

(2)

a

b

Figure 3. Polarized reflectance measurements at 410 (cross),470 (star), 555 (dot), 670 (diamond), 865 (triangle) and 2250(square) nm of a) a vegetated field and b) a bare soil field. Thedashed line (I) and solid line (II) are the empirical models.

This is not an indication that it is a better model thanthat of Nadal and Bréon [1999] since it was tuned to thisdata, but simply that it is an acceptable model that mayexplain some of the observed features of surfacepolarized reflectance using simple physical mechanismse.g. shadowing [Saunders 1967].

4. CONCLUSIONS

The hypothesis that the polarized reflectance ofsurfaces is generated by front facet reflections and istherefore spectrally neutral is born out by the datapresented here. This phenomena allows polarizedreflectance measurements at 2250nm to be used as a

reliable proxy for the surface polarized reflectance over awide spectral range. The agreement between simulatedand measured atmospheric polarized reflectanceindicates that aerosol retrievals over land surfacesshould be possible using such polarized reflectancemeasurements and may have the ability to retrieve theeffective radius of accumulation mode particles with anaccuracy of ±0.05µm. The regression models that linkthe surface reflectance at 2250nm with that at shorterwavelengths to allow the retrieval of aerosol propertiesover land from intensity measurements do not appear tobe as robust.

The larger magnitude of observed surface polarizedreflectance near the backscatter direction compared withsimple physical models, that was observed by Nadal andBréon [1999], is also found in the data presented here.An examination of the effects of higher orders ofscattering that may be responsible for this feature andthat have been used to explain negative polarizationfeatures in the backscatter direction [Wolff 1980] will bethe subject of future work.

Acknowledgements: This research was funded in partby NASA through the EOS and GACP programs and bythe Department of Energy interagency agreement underthe Atmospheric Radiation Measurements program.

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