C-band radar cross section of the Guyana rain forest: Possible use as a reference target for spaceborne radars

REMOTE SENS. ENVIRON. 27:25- 36 (1989)

C-Band Radar Cross Section of the Guyana Rain Forest: Possible Use as a Reference Target for Spaceborne Radars R. Bernard D. Vidal-Madjar CRPE CNET / CNRS, Issy Les Moulineaux

T h e results of a C-band radar campaign over the French Guyana rain forest are analyzed, showing the stability and homogeneity of the forest when seen by a low resolution radar. A 7 value of - 8 . 3 5 +__0.3 dB has been measured during the campaign, nearly constant with the incidence angle. Some possible diurnal variation or rain effect have been identified, of the order of 0.5 dB, with a maximum NRCS at the end of the night (0600 LT), as it was already observed by the SEASAT scatterometer in Ku band. Such a constant T is well represented by a pure and isotropic volume diffusion model, and depends mainly on the single scattering albedo, ratio of the volume extinction to the volume backscattering coefficients. This campaign, organized by the European Space Agency, has shown that the tropical rain forests such as the Amazon Forest can provide a good reference distributed target for the calibration of spaceborne scatterometers, even at C-band, which will be the frequency of the ERS-1 Wind Scatterometer.

Address correspondence to R. Bernard, CRPE CNET/CNRS, 38-40 Rue du G6n6ral Leclerc, 92131 Issy Les Moulineaux, France. Received 22 September 1987; revised 16 August 1988. 0034-4257/89/$3.50 ©Elsevier Science Publishing Co. Inc., 1989 655 Avenue o f the Americas, New York, NY 10010

INTRODUCTION An airborne radar campaign has been organized by the European Space Agency (ESA) over the French Guyana rain forest, which was aimed at the qualification of the ERS-1 Wind Scatterometer calibration method, using the Amazon Rain Forest as a reference target. Another objective of the campaign was also to study the C-band radar wave penetration into the forest, and the possible use of such radars for forest investigations, by using the radar in its high resolution/nadir looking mode (Bernard et al., 1987b). That part of the campaign will be the object of a subsequent paper. The use of tropical rain forests, and specifically of the large Amazon Forest, for spaceborne radar calibration has first been proposed for the Seasat Scatterometer. Birrer et al. (1982) observed that the Seasat Scatterometer measurements over the Amazon Forest were very homogeneous and stable, with a smooth incidence angle variation. They proposed to use these observations to monitor the gain stability and antenna pattern relative calibration for the Seasat SASS (Bracalente and Sweet, 1984). The ERS-1 wind scatterometer is designed for measuring the wind at the sea surface, using the

25

26

Bernard and Vidal-Madjar

surface scattering cross section along three different look directions, and an algorithm relating the Normalized Radar Cross Section (NRCS) to the wind intensity and direction (Long, 1985). In order to be able to extract the wind information from three independent observations at the same point, it is necessary to be able to compare accurately (within 0.5 dB) the radar cross section from three different antennas and incidence angles, and to have a knowledge of the stability of the receivers within the same accuracy along the satellite life. A very good calibration of the radar and of the antennas is then necessary. A point target calibration is possible, either with passive (corner reflectors) or active (transponders) targets. This gives good absolute calibration, but requires a number of data points to calibrate all the incidence angles. A further transformation is still needed to get the equivalent NRCS of a distributed target (integration over the radar range window and transverse antenna pattern). It seems then useful to have access, besides point calibration, to a permanent reference distributed target such as the Amazon Rain Forest. As the Seasat Scatterometer was in Ku band, it was necessary to check the NRCS properties of the

forest at C-band, first to verify the stability of the forest at that lower frequency (where ground effect could introduce some variability, as the radar wave penetrates deeper in the vegetation), and also to obtain a reference absolute NRCS as a function of incidence angle, allowing absolute calibration of the ERS-1 Scatterometer. Results of the ERASME radar, flown aboard the Do228 of the DFVLR (Deutches Forschungs und Versuchsanstalt fur Luft und Ranmfahrt) are reported here, showing the homogeneity and stability of the Guyana forest at C-Band. A simple penetration model is proposed for the interpretation of the incidence angle variation.

CAMPAIGN AND EQUIPMENT DESCRIPTION The ERASME scatterometer is a C-band side-looking FM-CW radar which was designed as a research tool for the development of applications of radar remote sensing. It has been built by the CRPE with the support of CNES (Centre National d'Etudes Spatiales). It is a low power, small radar

Table 1. E R A S M E Radar Characteristics High Resolution

Low Resolution

1 Radar type Center frequency Modulation Bandwith (effective) Transmitted power Polarization Transm. antenna Receiv. antenna Altimeter antenna

225 Mhz I 150

I

FM-CW 5.4 GHZ Triangular, 6 ms period. I 27.2

2

40.8 Mhz 13.6

4 W (36.2 dBm) VV Corrugated horn, gain 18.3 dB 3 dB beamwidth 25.2 ° Planar dipole array, gain 25.1 dB 3 dB beamwidth 4.6 ° × 11.2 ° Scalar horn - nadir looking, gain 17.5 dB

Receiver gain step attenuator 0-60 dB RF IF Cable + radome Signal processing Bandwidth Freq. res. Local oscillator

(Khz) Data acquisition Aux. data

19.9 dB

100 Khz 0.5 Khz

16.4 dB 70 dB - (6.4 + 1.35) dB FFT analyser, 512 pts in 3 ms 100 Khz 0.5 Khz

200 Khz 1.0 Khz

120-150-240-external LS! 11/23, CCT tape recorder 2 × 32b digital lines: clock, antenna pointing 8 analog lines: power detection, aircraft sensors

C-Band Radar of Rain Forests 27

Tab/e 2. Radar Resolution and Footprint Characteristics (High Altitude Flights) 15

25

35

45

53

Altitude (m) Range resolution (m)

3050

3050

3050

3050

2440

(FFTfilter) Actualresolution (VCOnonlinear) Groundresolution (alongtrack × crosstrack), singlecell Integrated (beam+ 7°,

11.0

11.0

22.1

22.1

22.1

46.0

49.0

68.0

78.0

82.0

254 X 46

270 X 49

299 X 68

346 × 78

326 × 82

302 × 398

318 × 389

347 × 650

394 × 1083

374 × 1367

0.6 s integr.)

which may be borne on a small helicopter or aircraft (Bernard and Vidal-Madjar, 1983; Bernard et al., 1986). Its characteristics are given in the Table 1. For this campaign, it was flown aboard the Do228 of the DFVLR. High altitude (3000 m) flights are considered here, giving a large footprint (given in the Table 2 as a function of incidence angle) suitable for average NRCS determination. The radar was fully calibrated in the lab, including the antennas, before and after the campaign. Gain variations during the flight were monitored through a bulk acoustic delay line, and remained within 0.2 dB during the campaign. An external calibration was also undertaken during the campaign, using four corner reflectors (1775 mg), which permitted us to check the internal calibration (within 0.5 dB), and gave some indication about the actual radar range resolution (which is degraded relatively to the theoretical resolution at large distance, due to nonlinearities in the VCO). The actual resolution is reported in the Table 2. Figure 1 gives an example of the measured NRCS of the corner reflectors, as the aircraft is flying in front of them. For that part of the campaign which was devoted to the study of large scale properties of the forest, several flight types have been flown: * "Long distance flights" (about 200 km), between Cayenne and St. Laurent du Maroni, with the antenna pointing at different incidence angles, and at different time of the day or night. * "Octogon flights," with short legs (15 km) along a quasicircular pattern, at different incidence angles, at the beginning and the end of the campaign. Those flights were flown

Corner reflectors data

g ~

32

.

i

30-

2626-

o 0

24 ,

,,~

-0-4-

j ~ "

22 -

corner 1 corner 2

-a- corner 3 -'0- c o r n e r 4

o 20 0

10

20

time step (0.2 sac. / 0.46 °)

Figure 1. Equivalent radar cross-section of the comer reflectors. Four trihedral comer reflectors (32.5 dBm 2) were seen simultaneously at different range positions (i.e. different incidence angles and positions in the antenna beam). The equivalent NRCS shown here is the measured RCS of the target, (including all radar corrections but the antenna pattern correction, as a function of time, when the aircraft is flying in front of the comers. The distance between two consecutive points corresponds to approximately 0.46 ° azimut direction variation. The decrease of the RCS when the aircraft is flying away cannot be seen as the target to background ratio decreases, due to a strong background return from nearby forest. A parabolic fit corresponding to the antenna pattern modulation is shown for the comer at the center of the antenna beam.

over a more rugged part of the Guyana forest. * One "triangular" flight, Cayenne-St. Laurent du Maroni-Saul-Cayenne, allowed us to scan a large part of the Guyana forest, both along the coast and inland on higher elevation ground (600 m). Those different flights are summarized in Table 3 along with the observational data which are discussed below.

28

Bernard and Vidal-Madjar

T a b / e 3.

Summary

Date 09/29/86

10/04/86

10/05/86

10/06/86

10/07/86

10/08/86

of High

Altitude

Flight Data

Time (LT)

Inc. Angle

Mean Sigma 0

Gamma

rms

15:15 15:45

15 25

- 8.59 - 8.84

- 8.40 - 8.41

0.50 0.40

16:15

35

- 9.03

- 8.16

0.26

17:00

45

- 9.63

- 8.12

0.28

17:30

53

- 10.28

- 8.08

0.17

11:30

35

- 9.43

- 8.56

0.28

12:10

35

- 9.43

- 8.56

0.21

12:30

35

- 9.16

- 8.29

0.30

11:10

15

8.44

- 8.25

0.62

12:10

35

- 9.30

- 8.43

0.22

13:15

53

- 10.41

- 8.21

0.22

11:20

25

- 7.84

- 7.41

0.31

12:30

45

- 9.70

- 8.19

0.21

13:00

35

- 9.05

- 8.18

0.28

25:00

35

- 9.18

- 8.31

0.29

06:30

35

- 9.04

- 8.17

0.36

12:00

35

- 9.52

- 8.65

0.27

I6:00

35

- 9.43

- 8.56

0.36

13:00

15

- 8.37

- 8.18

0.51

13:30

25

- 8.30

- 7.82

0.24

14:00

35

- 9.17

- 8.30

0.20

14:30

45

- 9.84

- 8.33

0.20

15:00

53

- 10.12

- 7.92

0.50

Data Processing Although the backscattering process in the forest is mostly a volume phenomenon, it is possible to describe the forest, when viewed from high altitude, as a single horizontal plane surface. The equivalent NRCS of that surface is then defined by the classical radar equation:

ae, x 2

one can assume--and check on the processed data --that 2/= %/cos(R) is constant within the illuminated spot), the data have been processed by integrating the radar return over the main antenna lobe ( _ 7°), with distance compensation. The result is then less sensitive to the aircraft attitude and altitude variations. With those assumptions, the radar equation is written, for a resolution cell (Sr << r),

e' = -~~G°'G°~ (4~r)

cos(O)G(O, (I)) rdrd#

er=B2/off × ffoo(O)C(

r4

(2)

d~

,+) F ,

(1)

where the integral is taken over the radar resolution cell on the surface and the geometry (~, q~) is relative to the antenna axis. The relationship between 0 (incidence angle), ~, and ~b is then obtained through the radar geometry (altitude, antenna pointing,...) relative to the reference surface. The actual position of this reference surface may be at the top of the canopy, or at the ground level, or at the level of maximum return within the canopy. Variation of that level (for instance with incidence angle) will only change the % by 0.2 dB for a flight at 3000 m. From a satellite, this effect is negligible. As a good ground resolution is not required for that experiment, and assuming that the NRCS is varying smoothly with incidence angle (actually,

=

f

ys(O)c(o,

o0 = 2/oCOS(8), where the integral is taken on the antenna pattern and is a radar characteristic. The received power is further integrated for angles 00 _+ 80:

r~(O~) y" ri3eri = B2/0 cos(O(r))dr

(3)

rl( Ol )

x

¢) de

and

Oo=

2/o cos(0o)

CO$( ~O)~J'i3eri

B 8rf~f2~,cos(8 )G( O, dp) dOdO~

(4)

C-Band Radar of Rain Forests 29

The actual resolution cell is then the antenna footprint and is given in the Table 2. This processing gives the advantage that the resulting o0 is not critically dependent on the exact knowledge of the antenna pointing and of the altitude (this being important, as over hilly country the measured altitude is not always representative of the actual altitude at the measurement point). Both notations o0 and 3,0 are used in this paper, o0 being the NRCS referred to the horizontal unit surface and 3,0 being referred to the unit surface normal to the direction of observation, o0 is more commonly used for scatterometry over the ocean, but 3'0 is better suited for volume backscattering characterization.

3000 independent samples, then residual fading fluctuations are lower than 0.02 dB, and the observed variations are actually due to target variability. The figures show that short distance variations are always lower than 0.3 dB, with some long distance variations of the same order of magnitude, which are observed on both ways, and are then actually due to target variations. The most variable part of the flight is observed on the hilly part of the transect. Part of it ( < 0.2 dB) may be due to residual data processing biases (errors on the altitude), the main source of variability being likely due to slope effects and to the existence of some bare steep slopes, corresponding to a lower %. The same features are observed all along the campaign, even when flying over different parts of the forest, as seen on Fig. 4 showing the "triangle"

CAMPAIGN RESULTS AND DISCUSSION

flight.

NRCS Variability

Table 3 and Fig. 5 summarize the data obtained at an incidence angle of 35 ° along the campaign, and show the stability of the NRCS, with a mean 3,0 value of - 8 . 3 5 d B + 0 . 2 dB. (Gamma data are preferred as 3, is expected to be constant with incidence angle for isotropic volume

The Figures 2 and 3 show examples of the recorded NRCS during transect flights from Cayenne to St. Laurent du Maroni and back. Each data point has been integrated over 0.6 s, so that it is representative of a 350 × 650 m cell. It corresponds to about

Figure 2. Variation of the forest NRCS along the Cayenne-St. Laurent path (sunrise flight). The distance is measured from the starting point near Cayenne. The upper two curves correspond to the NRCS, the intermediate ones to the altitude measured by the radar and converted to ground elevation, assuming a constant flight altitude, and the lower curve is the received power in the altimeter mode, where peaks allow to detect river crossings. For the NRCS and the altitude, the return flight data has been shifted upward by 1 dB or 100 m. .

.

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I

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.

.

I

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.

angle 35 flight

o

.

I

.

10/7/86

.

.

.

I

1:30 UT

direction

Sigma 0

-M

-tO

300

-15

"o power

I

M ~5

'

0

-20

0

50

100 Distance (kin)

150

200

30 Bernard and Vidal-Madjar

"' .

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I

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I

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I

35

angle " ~

.

flight

.

.

.

.

I

9:30 LIT

10/7/86 direction

~" - 5 '0

v

sigma

0

o

fi ~-10

300 •

po~er --20

I

~

0

_ I

, .

50

.

.

.

'~ .

1O0 Distance (km)

t

I . W."~-'..~'7"~

150

0

200

Figure 3. Same as Fig. 2, but for a morning flight.

backscattering, and is then a characteristic of the target.) One can compare this result to the value of - 6.5 + 0.3 db measured between 35 ° and 50 ° by the Seasat Scatterometer at Ku band (Bracalente and Sweet, 1984). Some comments may be added about the daily variation: Bracalente and Sweet (1984) observed on the Ku band Seasat data an increase of the NRCS of 0.5 to 1 dB at the end of the night. In our case, four flights were flown at different time of the day or night on the same day (23, 6, 12, and 16 h local time). Most of the other flights on the same transect were flown around noon. It can be seen on Fig. 5 that both nighttime flights show a small increase of the NRCS, but less than 0.5 dB, with the maximum close to the sunrise. This difference is, however, small, and although it seems to be related to an actual nighttime increase, it is not possible to conclude with only one example. One must notice that the campaign occurred at the end of a small "dry" season, with scattered showers starting again. The diurnal effect could be different on other climatic conditions. Whether this increase is due to dew deposition (as stated by Bracalente and Sweet) or to a variation of the water pressure (and of the dielectric constant) in the leaves is unclear. Although rain occurred during some flights, it was not possible to detect any clear effect but for

one case. As rain occurred as scattered showers, it was not possible to know to what extent the radar footprint had received rain. However, during the flight shown on Fig. 6, the aircraft went through a strong storm on its way to St. Laurent (the exact time is easily retrieved from the aircraft attitude record). On the way back, the storm position had changed, and one can see a significant increase of the signal on that part of the transect which has been cleared by the storm. Again the effect is small (lower than 0.5 dB), and it is not really possible to conclude about rain effect with only one case. Incidence

Angle

Variation

The NRCS variation with incidence angle has been measured on three different cases, twice during "octogon" flights, and along the Cayenne-St. Laurent transect. Results are shown in Fig. 7 and given in the Table 3. Gamma values are preferred again. One can see that 3'0 is nearly constant between 15 ° and 55 °, corresponding to isotropic volume diffusion. The only small discrepancy is at 25 °, with a slightly higher 70 value, and higher dispersion of the data between the three cases. Such effect cold be due to ground contribution. (Actually, high resolution experiments show that the radar signal reaches the ground, but is strongly attenuated and the ground effect decreases rapidly when the incidence angle increases.) It is more

C-Band Radar of Rain Forests 31

0

I

!

10/4/86

angle 35

15:00 UT

-5 Saul Cayenne

v

S¢

Cayenne

.

Laurent

0

°l,i

tIJ

300 "-" .¢;

-20

' 0

2OO

0

400 Distance (kin)

Figure 4. Same as Fig. 2, but for the "triangle" flight, with the three legs Cayenne-St. Laurent, St. Lanrent-Saul, and Saul-Cayenne.

Figure 5. Summary of gamma data obtained at 35 ° incidence angle all along the campaign. Each point corresponds to a specific transect flight. The rightmost point corresponds to the overall average.

-6

-'7'

1'

A

"o

Q

O- 8 , i

r.

r~ 7 t -¸

i

- -

i

lil

i

-±

-9

n

a

I

n

i

_J_

.... ]

|

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i

II

li

Date

32 Bernardand Vidal-Mad]ar

I

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I

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I

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10/7/86

angle 35

.

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I

18:30 UT

flight direction i~

turbulences detected on aircraft sensors

.(p

¢

v

Sigma 0

0 d~ ~o tl)

.

.

.

.

.

.

-lO

'

altitude

t~ll ,

4--

300 "-"

,~' ~ fl/,t~,, ,,~,t,,i,~'~%, II ', , 1 ~ I

powers: -20

. ~

. . . .

0

,

50

.

,x - , " ~ -~-.-~-_' r ~ .

100 Distance (kin)

M

~~ . ~ . ~

150

,

c

200

Figure 6. Same as Fig. 2, but the part o~ the transect where high turbulence due to storm was recorded on the aircraft sensors has been underlined.

Figure 7. Mean g a m m a value as a function of incidence angle. The error bars correspond to the rms for each transect.

-6 !A I

OcLogon 1

I

--7

121

Cayen. St Lau.

:~

Octo~on

2

---

A

-8

. . . . . . . . .

I i

,%

-T"

CI

!

-9

-10

I

0

I

I

I

I

I

I

20

i

40 I n c i d e n c e angle

60

C-Band Radar of Rain Forests 33 7" / / /

\ \

dr

Z

\

9 /

\ , ; ' Canopy

,;,1 z

/

likely due to some directional effect in the backscattering properties of the forest (for example, related to limbs or leaves orientation). Anyway it is quite possible to consider ~'0 as constant within 0.5 dB for the whole incidence angle range. One can see also a larger variability at 15 ° and 25 °, which is partly due to a higher sensitivity of the data processing method to actual incidence angle variations, and may be partly due to a higher and more variable ground contribution (Bernard et al., 1987a).

ground

Figure 8. Radar geometry tar the model definition.

resolution cell at distance ri may be written

/ , . - BSr r 3 f2°o~(Os)G(Os,d~) dtb

1

+ fffc(o,

Zto))r z

x sin(0) drdOdO# Xexp cos(0) f~ a(x,O)dx

FOREST NRCS MODEL

A simple "cloud" model (Attema and Ulaby 1978; Bernard et al., 1987b; Hoekman, 1985, 1986) is used to model the radar signal, in which the actual radar geometry is included. It is a diffusion model, where the vegetation acts as a continuous, vertically stratified medium, characterized by its volume extinction and volume backscattering coefficients a and p (both being possibly function of the incidence angle). One can also define the single scattering albedo 7/, the ratio of these coefficients, and include a directionality factor 190 (equal to 1 for isotropic scattering). Using that model, the radar equation giving the received power in a

(5)

]

with

cos(O)=(h-z)/r, cos(0s) = h / r , cos(Oa) = ( h -

Z)/r,

the geometry being defined in Fig. 8. B is a radar constant, h the altitude of the aircraft above the ground, and Z the height of the canopy. The first integral corresponds to the grotmd contribution to the received power, and the second to the vegetation contribution. Using the optical depth • = 2 f 0 a(x)dx, ~'M=fo

Za(x)

dx,

34 Bernard and Vidal-Madjar and some transformations, the equation becomes

BSr

= r3

°° (0s)exp

[ - 2"r~ ]

x f f(O,, ld + fo'%(,,o))po a,

(8)

Xexp[L - - c2(~'°~st ~ )-i ~) ]

x f2, G(O(,),dP)ddP } " From this and Eq. (1), the equivalent NRCS is o° = °°~(0~) exp[ c o s2"M ~- ]

X[f2~rC(Os,~)dt~/f2~rC(Oa,t~)df~ ] +

j?~(')P°d'exp [ co-~(0(~))-.,

(7)

negligible, the equivalent gamma is only dependent on the ratio 7/p0. This ratio may be a function of the forest struc~tre, but is likely less dependent of the density of the canopy than p or a. This may explain the stability of the observed RCS of the forest, even though the forest density is known to be variable, with a density related to the soil properties: Two main structures are observed in Guyana, corresponding either to well-drained soils or to wet softs where the vertical drainage is blocked (Lescure et al., 1983). In Fig. 9, comparing the output of the model (for a constant ,/ and varying absorption coeflL cients) to the campaign results, one can see that the forest NRCS is easily represented with that simple model. One could also explain the observed data with a well-chosen combination of ground o0 and small optical depth, but radar wave penetration studies showed that the ground attenuation is always large, corresponding to an optical depth larger than 2. Then the only valid model is with ,/= 0.3 and a high (but not measureable and possibly variable) optical depth. The ground contribution is then negligible at angles larger than 10 °. Dep~e from a constant ,/ at 25 ° could easily be modeled by allowing the phase function P0 to be a hmction of the incidence angle.

CONCLUSIONS

With a large antenna and at a large distance so that 0 -- O~-- Os, one gets the classical result" °o = °oseXp[

F - 9. -M1 ]

(8) + fo ~l(T)P°dTexp or,

9

ff ~!= Cte, °0 = °oseXp[

r-2 M1j (9)

]~ + 'lP°/2e°s(O)(ll - e x p[[ ~- 2~'M]]. One can see immediately that ff the optical depth is large enough, so that the ground contribution is

This experiment has shown that even at C-band, when seen at coarse resolution, the tropical rain forest behaved like an isotropic volume diffusor, thick enough to hide the ground contribution, with a characteristic y value of - 8.35 ___0.3 dB, which has been measured accurately. Only small variations are expected (less than 0.5 dB), either diurnal, or related to rain occurrence, or due to ground relief. Although the experiment took place over the French Guyana Forest, the results are likely to be applicable to the Amazon basin forest, which is supposed to be even more homogeneous, and with similar forest structure (both for trees species and soft structure). Indeed, this result is valid only for the time of observation (at the end of a small dry season) and cannot be generalized directly to other seasons. However, large seasonal variations are not expected on equatorial rain forests, and one could

C-Band Radar o f Rain Forests

-5

°,

!

35

!

L

~/ = 0.3

---/

-6

~,

A

.I~ - 7

1"=.9.

t~-8 -9

-10 0

20

40

Incidenceangle

e0

a~e (a,u,)

Figure 9. Model output for gamma simulation as a function of incidence angle, for different canopy optical depths (r). The vertical structure of extinction and backscattering coeflacients is sketched on the fight (their ratio is kept constant and equal to 0.3). The vertical structure has no effect on the average gamma, but gives different results when simulating the radar wave penetration into the canopy. The dashed line corresponds to the ground gamma model. The experimental data from Fig. 7 has been added for comparison.

argue that the higher variability is obtained at that period, when drainage contrast is highest. The Amazon Forest is then a good candidate as a reference target for the ERS-1 Scatterometer. Conversely, the experiment shows that, at incidences angles larger than 15 ° , only one characteristic parameter can be extracted from the radar data, which may not be the most significant for forest characterization. However, the other part of the campaign showed that more could be learned from high resolution radars and from wave penetration studies. The Guyana campaign was organized and supported by the European Space Agency, with the participation of the CRPE, the University of Bremen (FRG), the University of Wageningen (Holland), and of the DFVLR (FRG). The ERASME radar has been built with the support of the CNES, and was operated under ESA Contract ESA / ESTEC / 6347/ 85 / NL / MD. REFERENCES Attema, E. P. W., and Ulaby, F. T. (1978), Vegetation modeled as a water cloud, Radio SCI. 13(2):357-364.

Bernard, R., and Vidal-Madjar, D. (1983), ERASME: diffusiom&re h6liportable en bande C. Application h la measure de l'humidit6 des sols, in Proceedings, EARSEL/ESA Symposium on Remote Sensing Applications for Environmental Studies, Brussels, Belgium ESA/SP-188, pp. 59-64. Bernard, R., Vidal-Madjar, D., Baudin, F., and Laurent, G. (1986), Data processing and calibration for an airborne scatterometer, IEEE Trans. GE-RS GE-24:709-716. Bernard, R., Lancelin, P., and Laurent, G. (1987a), Guyana rain forest campaign, Campaign report, Technical Report CRPE/151, C.N.E.T., Issy les Moulineanx, France. Bernard, R., Frezal, M. E., Vidal-Madjar, D., Guyon, D., and Riom, J. (1987b), Nadir looking airborne radar and possible applications to forestry, Remote Sens. Environ. 21:297-309. Birrer, I. J., Bracalente, E. M., Dome, G. J., Sweet, j., and Berthold, G. (1982), The signature of the Amazon rain forest obtained from the Seasat Scatterometer, IEEE Trans. Geosci. Remote Sens. GE-20(1):ll-17. Bracalente, E. M., and Sweet, J. L. (1984), Analysis of normalized Radar Cross Section signature of Amazon rain forest using Seasat Scatterometer data, NASA technical memorandum 85779.

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Bernard and Vidal-Madjar

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