) 

Semiannual Report 

2&7& y/b Under 

Contract # NAG - 5 - IOIO 

National Aeronautics and Space Administration 

-‘ f i‘ ,,* L.l 

Improvement and extension of a radar forest backscattering model 

Prepared by: 

David S. Simonett 

Yong Wang 

DEPARTMENT OF GEOGRAPHY 

UN~VERSITY OF CALIFORNIA SANTA BARBARA 

May 10, I989 

~ 

~~ - ~ 

(NASA-CR-184975) IHPROVEHEHT AND EXT ENS IOM N 89- 2 46 86 

OF A RADAR FOREST BACKSCATTERING HODEL 

Semiannual Report (California Univ.) 18 p 

CSCL 02P Unclas 

G3/43 0206416 
1. Introduction 

-2- 

Radar modeling of mangal forest stands, in the Sunmans area of Southern Bangladesh, has been 

developed. The modeling employs radar system parameters with forest data on tree height, spacing, 

biomass, species combinations, and water (including slightly conductive water) content both in leaves 

and trunks of the mangal. For Sundri and Gewa tropical mangal formts, six model components are proposed, which are required to explain the contributions of various forest species combinations in the 

attenuation and scattering of mangal vegetated nonflooded or flooded surfaces. Statistical data of simulated images have been compafed with those of SIR-B images both to refine the modeling procedures 

and to appropriately characterize the model output. The possibility of delineation of flooded or nonflooded boundaries is discussed. 

2. Characteristics of the Study Area 

2.1. Characteristics of Mangal Forests in Southern Bangladesh 

2.1.1. Individual Organs of a Cewa and a Sundri Tree 

Gewa (Excoecaria agallocha) and Sundri (Heritiera minor Sn. H. formes) are mangrove species. 

The shoots are mostly orthotropic with infrequent diffuse branches, which sometimes may branch from 

the base and shrub-like form. Leaves are simple in shapes; and broad in size (Tomlinson, 1986). Gewa 

lacks any elaborated aerial part or pneumatophores, which function to supply oxygen to the roots at 

high tide. Sundri does have pneumatophores. 

Gewa yields a light, yellowish-white, fine-textured, and not very durable wood. mainly used for 

general carpentry work and toys, and (especially) for newsprint and matches (FAO, 1981). 

Sundri yields a heavy, dark red, fine-textured, strong and extremely durable wood. which is used 

for boat building, heavy construction work, beams, and house-posts (FAO, 1981). 

2.1.2. Whole Gewa and Sundri Trees 

A mature Gewa tree, as shown in Figure 2.1, grows intermittently and irregularly. up to 20 meters 

high for a mature tree. Branching is diffuse, irregular, and by prolepsis. Canopy is dense. Models of 

geometric shapes and structure for different ages of Gewa trees were described by Tomlinson (1986): 

with continuous growth of the trunk repeated in the branches, which have lateral inflorescences. 

A mature Sundri tree, as shown in Figure 2.2, is about 10 to 25 meters tall, and low-branched. 

The branches are thick and crooked. Canopy is very dense. Tomlinson (1986) also introduced a series 

of geometric models for Sundri trees of different ages: with rhythmic growth, undifferentiated branches, 

and lateral inflorescences. 

2.13. Cewa and Sundri Forest Stands 

Gewa and Sundri forests occur essentially and dominantly at the tidal mouth of the Baleswar 

River in southern Bangladesh, which belong to closed broadleaved woody tropical rain forests (FAO, 
-3- 

1981). Most of the mouth areas are frequently flooded by fresh water during the monsoon rains (May - 

June to October - November, Chapman, 1973, with salt water intrusion during the rest of a year. 

Gewa and Sundri forests are very difficult of access with soft foolhg, and have extremely high canopy 

and stem densities. Estimations of the mangrove forests in this am are about 590,000 hectares (FAO, 

1982), which contribute very important forest resources and environmental protection for Bangladesh 

they provide marketable products, and also play roles as buffers for storm surges, and tidal waves coming from the Bay of Bengal (Imhoff et al., 1986). The forest becomes poorer and more open as one 

processes towards the sea or salt water intrusion area. Sundri mainly lives in the area where the fresh 

water is available, and becomes smaller and less abundant as one goes from fresh water areas towards 

salt water areas. Gewa is mainly in the saltwater area, and also there are some Gewa forests in the 

fresh area (FAO, 1982). 

2.2. Ground Surfaces 

The Delta soil is a clay loam lying over alternating fayers of clay and sand, highly saturated with 

exchangeable bases (Nu+, Cu”, K’, etc.). The salinity of the soil varies seasonally as a result of the 

changing balance of fresh water and salt water. Chapman (1977) pointed out that there is a very high 

salinity at the beginning of the dry season, and this factor considelably limits the development, maintenance, or regeneration of the less halophilous species such as Suntlri, which is on the way to extinction 

because of excessive salt water intrusion. During the rainy season (when the SIR-B images were 

obtained), the salinity will be low. 

3. Analysis of Ground Truth Data 

Ground truth data of Sundri and Gewa mangal forest in our southern Bangladesh research site 

were originally collected by a NASA and Bangladesh science team concurrently with the SIR-B Mission in October, 1984; and subsequently by Chaffey, et al., (1985). All these data were prepared by 

averaging measurements made for inventory plots each 100 * 100 meters (one hectare) in size, consisting of: 

a. 

b. 

c. 

d. 

e. 

a digitized forest stand map; 

DBH count dism3utions by DBH segments; 

tree heights and canopy depths by their DBHs; 

canopy biomass of in each DBH segment; and 

gravimetric moisture content of canopies and trunks. 

3.1. The Digitized Forest Stand Map 

The digitized forest stand map containing different Sundri 2nd Gewa stands in the test site was 

geo-registered with the SDR-B images obtained in October, 1984. The number of pixels and names of 

each forest stand are shown in Table 3.1. These stands have different tree densities per unit area for 

each DBH segment. The digitized forest stand map is used as a mask to locate and to extract each 

forest stand data from the SIR-B images. The ground surface is either flooded or nonflooded. 
-4- 

3.2. DBH Count Distributions by DBH !%?@ne& per Hectare 

DBH count distributions by DBH segments per hectare are shown in Table 3.2, which are used to 

generate random tree trunk distributions with varying DBHs in one simulated stand area such as twenty 

hectares (assumed in our modeling). Based on both the combinalion of two Sundri and Gewa species 

and the random distributions of the tree trunks, tree counts for each DBH segment of Sundri and Gewa 

in each pixel in the stand area are created. 

33. Tree Heights and Canopy Depths by Their DBHs 

Tree heights and canopy depths determined from their DBHs are obtained by regression, from the 

data collected by a NASA and Bangladesh science team in October 1984, employing the data of tree 

heights, canopy depths and DBHs, and these regression models axe shown in Table 3.3. These regression models were employed to calculate each tree height and mean canopy depth in each simulated 

pixel in a forest stands, using the DBH counts for each DBH segment in each simulated image pixel. 

The effective trunk heights, or dielectric cylinder lengths, &ed in [he modeling were defined as the total 

tree height minus two thirds of the corresponding mean canopy depth. 

3.4. Mean Canopy Biomass in Each DBH Segment 

Mean canopy biomass value in each DBH segment is calculated by dividing the total biomass 

(kg) by the tree numbers in each DBH segment, as shown in Table 3.4. The mean canopy biomass data 

in each simulated pixel is computed by the total trees (with different DBHs) in this pixel multiplying by 

the mean canopy biomass value for corresponding DBH segments. The total biomass is then converted 

to volume ratio (m3/m3> by 1) the total biomass (Sundri and IGewa respectively) dividing by their 

specific weight (kg/m3>, which gives the total canopy volume of the Sundri and the Gewa canopy; 2) 

the total canopy volumes (Sundri and Gewa canopy volumes) are divided by the total volume which is 

defined as pixel size times the mean canopy depth in this pixel. Thus the converted ratio is a volume 

occupied by the tree canopies to the total volume. This volume ratio parameter has been employed as 

an input parameter to compute the attenuation coefficient. and the scattering coefficient of Sundri and 

Gewa trees for each pixel using models developed by Ulaby. et al., (1986). The biomass varies as a 

result of variation in both the total tree numbers in each pixel and the tree number in each DBH segment. 

3.5. Gravimetric Moisture Contents of Canopies and Trunks 

Gravimetric moisture contents of canopieS and trunks are derived from dry and wet biomass data. 

Because of a lack of explicit data to separate Gewa and Sundrii, we assume the water content in the 

canopies and trunks to be the same for each species. The water contents are: canopy, p = 0.402668, CY 

= 0.038955; and trunk, p = 0.453775, CJ = 0.057921. These data are used to compute the dielectric 

constants of the canopies and the trunks following Ulaby and El-byes (1987). 
-5- 

4. Radar Models of Sundri and Gewa Forest Stands 

Based on the above analysis, six model components am proposed. as shown in Figure 4.1 (see 

also Wang, et al., 1989): 

1 

2 

3 

4 

5 

6 

The total radar return is 

Direct backscattering from ground surface (short form a&), 

Direct volume scattering from upper canopy* (short form a;,)', 

Direct volume scattering from lower canopy* (a&), 

Interaction of trunk/ground forward reflection (e&), 

Interaction of groundbpper canopy forward scattering (a&), aind 

Interaction of ground/lower canopy forward scattering (a$c). 

a:t = e&* + 0,9, + o:r + a& + a& + a& 

a,&: the small perturbation model, used for both flooded and nonflooded surfaces, is (Dobson and 

Ulaby, 1986): 

AS 

a& = Ax4(k, f )2cos4ei exp [-(k, I ~ine~)~] I R,,,, (ei) I * 

2x where the €Ii is the radar incidence angle, and k, the radar wavenumber (-; h is the radar h 

wavelength). As is the surface area not shadowed by trunks and A. is the pixel area. h and 1 are the 

rms roughness and surface correlation length, which are assumed ((no measurement data available) as: 

flooded surface, h,,, = 0.01m, f, = 0.15m; non!looded surface, h, = 0.02m, and I, = 0.075m, 

respectively. The basis for these assumptions lies in the requirements of the small perturbation model, 

and the either flooded or nonflooded surface condition. Rhlr(ei). the Frcsnel reflectance coefficient of 

the surface for HH polarization, is (p,=1.0 is assumed): 

where the E, = E' - j E" is the relative dielectric constants of the surfaces (flooded and nonflooded). 

The dielectric constant of the flooded surface is assumed to be equivalent to 1 % salinity, because of 

extensive dilution during the monsoonal rainy season (when the SIR-B images were obtained). The 

dielectric constant of the ground surface is derived from the mixed model of Ulaby, et al., (1986). 

atm: the water cloud model (Auema and Ulaby, 1978) is chosen: this model is simple and functional; no measurement data on orientations of branches or leaves are available; and only HH polarization is studied. The model is: 

*: Upper and lower canopies are defined as the canopies of trees whose DBH's are respectively >= 5.0 cm or < 5.0 an; 

the latter is also termed regrowth. 
-6- 

in which h,,, is the mean upper canopy depth in each simulated pixel. IC" is the upper canopy extinction coefficient, which is derived by a volume ratio and the canopy dielectric constants (Ulaby, et al., 

1986). q,, is a volume scattering coefficient of the upper canopy layer. The ratio of the volume 

scattering coefficient to the extinction coefficient is assumed as 0.3, and 0.4 for the upper and the lower 

canopy layers respectively, because the lower canopy is denser than the upper canopy. These values 

are higher than those used by Sun and Simonett (1988): the mangal forest canopy is much denser than 

the pine forests of northern California which they studied; and Gevva especially may also have a slight 

salinity inside leaves and branches (Snedaker, personal communication, April, 1989). In addition, the 

sensitivity of the model to change in the ratio is low as shown by Richards, et al. (1987). Using the 

ratio and the attenuation coefficient computed in each pixel, fly and ql are then solved. 

oil: basically is the same model as a&, but with different mean canopy depths: and canopy densities or volume ratios, which produces different attenuation coefficients and scattering coefficients. 

a&: is the specular scattering coefficient of dielectric cylinders with finite lengths (Ruck, et al., 

1970) multiplied by the reflection coefficient of the surfm (flmied or nonflooded). Tree trunks are 

modeled as dielectric cylinders with smooth surfaces. If a dielectric cylinder length is much greater 

than the wavelength (I w 2h), the scattered field from the cylinder propagates in 8, = 90.0, - Oi, and 

azimuth angle from 0" to 360". where the 8, is a scattering angle. The bistatic scattering cross section 

of the cylinder with finite length (Ruck, et al., p. 304, 1970) is: 

where I is the cylinder length, and is calculated from the regrwsion models on tree heights. The 

effective trunk length or the dielectric cylinder length is the total tree length minus two thirds of its 

canopy depth. 0" ( Bi ,I$= ) is the scatter width for an infinitely long cylinder at oblique incidence, 

which is (for HH polarization) (Ruck, et al., p.271, 1970): 

... 

where the constant C,, is a function of the cylinder radius, the miterial, as well as the shapes or boundaries. The $, is the scattering azimuth angle. When $= = 0.0" and 8, = - (90.0' - Oi), this is the 

specular scattering. When 4, = 180.0" and 0, = - (90.0" - e,), this is the forward scattering. For the 

specular case, the scattering coefficient is: 

ko12 

OM ( 8i ,go.@' - ei , 0.0 ) = -sinQi c;& ( ei , 0.0 

x 

For the flooded and nonflooded surfaces, the Fresnel reflection coefficients are modified for 

slightly rough surfaces (Ruck, et al., 1970) as: 

The dielectric constants of the Gewa and Sundri trunks an: about (22.0 - j 7.0); (18.5 - j 5.0), 

which are derived from the model developed by Ulaby and El-Raiyes (1987) with gravimetric moisture 
-7- 

content, equivalent salinity, anti temperature as input. These values are slightly higher than those measured by Ulaby and Jedlicka (1984); and El-Ray= and Ulaby (19871, because the mangal has a higher 

salinity inside its leaves and trunks. 

For one single tree (or the k" tree), the interaction of the ground surface/trunk is: 

oigk = ~.oxRL(~, 1x0~ (e,, 90.0" - e,, 0.0) 

where we use 2.0 to account for the double paths from ground surfaceftrunk, and trunk/ground dace. 

Also, the phase produced by range difference is taken into account, or each o& is summed by given a 

random phase for each tree trunk in every single simulated pixel bemuse of the assumption of random 

location of each tree in every single simulated pixel, which is: 

where the n is the total number of trees in one simulated pixel, and the $k is the random phase of the 

kth trunk/ground surface interaction term. 

c:~: the same model as used by Sun and Simonett (1988). originally derived from Engheta and 

Elachi (1982): 

a& = h,q, lRL(Oi) 12[2 + IRL(Bi)12exp(-a,,)sinh(a,)/a,] 

where g, = K, h,, secei. 

02,: a similar model as above, except for different densities, mean canopy depth, and equivalent 

dielectric constants. 

It should be noted that all these model components may or may not be attenuated by the upper 

and/or the lower canopies, depending on their presence or not. The attenuation coefficients for the presence of an upper canopy layer are: 

TAU,=xp(-2.0~, h,, we,) 

and for the lower canopy layer: 

TAU~=~XP(-~.OKI h,lwei) 

where the K, and q are the extinction coefficients of the upper ad the lower canopy layers, respectively. h,, and h,, are the mean canopy depths in each simulated pixel for the upper and lower canopies. 
-8- 

5. Discussion 

The subareas of three forest stands (Table 3.1) are extracted from SIR-B images (DT 120 

incidence angle 26"; and DT 104 incidence angle 46"; see also hnhoff, et al., 1986), and the DNs of 

the images converted to relative radar backscattering coefficients (dB) by 

0" = 10' log(DN2-C+C.L. 

where i = 1, 2, corresponding to DT 120 and DT 104. Cli are the noise levels, Czi constants for calibration. Both CIi and Czi were provided by Marc Imhoff (1988, personal communication), as shown 

in Table 5.1. 

The boxplots of SIR-B images are shown in Figures 5.1 (TIT 120) and 5.2 (DT 104), with the 

modeling results plotted to the right. From these Figures, we conclude that: 

5.1. The Fit of the Models to the SIR-B Images 

The distributions of radar returns for each stand and two incidence angles are almost identical. 

The fit of the model to the image data is good. There are differences in the absolute values (the returns 

from our model are about 5 to 8 dB higher than the returns of SIR.-B images). The reason may be that 

the models are theoretical solutions and each model component is incoherently added, which could produce higher values. Also, the Czi (i = 1, 2, provided by Marc Imhoff, 1988, personal communication) 

may by a littler bit too large. 

5.2. Radar Returns of Nonflooded and Flooded Areas 

At 26" and 46"degree incidence angles, the returns for both SIR-B images and modeling results 

from flooded surfaces are slightly higher than those from nonfloodled surfaces. However, the difference 

appears to be slight because of strong attenuation by the dense canopies. The return difference from 

large to small of each stand is in the order of GS (highest), G, and SG (lowest) stands. There is 

insufficient data in Table 3.2 to account for these differences. 

5.3. Differences in Radar Returns Between Different Stands 

There are no obvious differences between different stands. FVe reason as follows: a) each stand is 

a mix of Sundri and Gewa in varying proportions; b) the number of stems is very large, which is of 

importance in both enhancing the O& (because of the large number of trunks), and in attenuation 

(because of the very dense canopy); and c) the structure of Sundri and Gewa are similar to each other 

(Tomlinson, 1986). The returns from SG stands may be the lowest because the density of the canopy 

layer may be marginally greater than that of other canopies (see Table 3.2). 

5.4. Radar Returns between Two Different Incidence Angles 

The mean (or median) are almost the same, but with greater variance at the smaller incidence 

angle for which there is a shorter path length through the canopy, yielding less attenuation for the a& 

term. The a& is the main component producing the variance for mangal: a similar conclusion was 

reached by Sun and Simonett (1988) for pine forest. 
-9- 

5.5. Penetration of the'canopy and Delineation of Flooded Arcas 

There is penetration to some degree, but it is not very obvious. The difference of radar returns 

between the flooded and nonflooded areas of both the SIR-B images and modeling results are around 

0.5 - 2.0 dB. This is probably not large enough to delineate the flooded boundaries with confidence, 

because of the high inhinsic variance in SIR-B images. 

5.6. Relative Importance of the Six Model Components 

The dominant model components are e&, a&,, and 02,. which are roughly equal for nonflooded 

surfaces. For flooded surfaces a& is increased, and e&, and e:d are unchanged. In areas where there 

are some natural clearings which lack the dense canopy layer, e& is clearly dominant We especially 

note the high returns from those forest edges which face the radar illumination direction. This feature 

has also been widely observed in short wavelength images of forest edges. 

6. Bibliography 

Attema, C. F. and F. T. Ulaby, (1978), "Vegetation modeled as a water cloud". Rodio Science, vol. 13, 

Chaffey, D. R., F. R. Miller, and J. H. Sandom, (1985). "A forest inventory of the Sundarbans, Bangladesh", British Overseas Development Administrarwn Project # 140, Land Resource Development Center, Tolworth, Surbiton, Surrey, England. 

Chapman, V. J. (1973, "Wet coastal ecosystems, Ecosystems of the world I", Elsevier Scientific Publication Company. 

Dobson, M. C. and F. T. Ulaby, (1986), "Preliminary evaluation of the SIR-B response to soil moisture, 

surface roughness, and crop canopy cover", IEEE Transachions on Geoscience and Remote Sensing, vol. GE-24, no. 4, pp. 517-526. 

El-Rayes, M. A. and E T. Ulaby, (1987), "Microwave dielectric spectrum of vegetation - Part I: experimental observations", IEEE Transactions on Geoscience and Remote Sensing, vol. GE-25, no. 5, 

Engheta, N. and C. Elachi, (1982), "Radar scattering from a diffuse vegetation layer over a smooth surface", IEEE Transactions on Geoscience and Remote Sensing, vol. GE-20, no. 2, pp 212-216. 

FAO, Food and Agriculture Organization of the United Nations, (1981), "Tropical resources assessment 

project (in the framework of the global environment nwnitoring system - GEMS)", Forest 

resources of tropical Asia. 

mangroves in Asia and the Pacific". 

pp. 357 - 364. 

_I 

pp. 541-549. 

FAO, Food and Agriculture Organization of the United Nations, (1982), "Management and utikation of 

Fosbery, F. R., (1971). "Mangroves v. tidal waves". Bwl. Consenr., 4: 38-39. 

Imhoff, M. L., M. Story, C. Vermillion, F. Khan, and F. Polcyn, (1986). "Forest canopy characterization 

and vegetation penetration assessment with space-borne ratiar", IEEE Transactions on Geoscience 

and Remote Sensing, vol. GE-24, no. 4, pp. 535-542 

Richards, J. A., G. Q. Sun and D. S. Simonett, (1987). 2-band radar backscatter modeling of forest 

stands", IEEE Transactions on Geoscience and Remote Sensing, vol. GE-25, no. 4, pp. 487498. 
- 10 - 

Ross, J., (1981). Tbe radiation regime and architecture of plant star&, Dr W. Junk Publishers. 

Ruck, G. T., D. E. Barrick, W. D. Stuart, and C. K. Krichbaum, (1970), "Radar cross section handbook", Plenum Press, New York. 

Simonett, David. S., Alan H. Strahler. Guoqing Sun, and Yong Wang, (1987), "Radar Froest Modeling: 

Potentials, Problems, Applications, Models", Advances in Digital Image Processing, Proceedings 

of the Annual Conference of the Remote Sensing Society. Norttingham, England, Sept. 1987. pp. 

Sun, G. Q. and D. S. Simonett, (1988), "Simulation of Lband HH radar backscatter fiom coniferous 

forest stands: a comparison with SIR-B data", International Journal of Remote Sensing, vol. 9, no. 

256 - 269. 

5, pp. 907 - 925. 

Tomlinson, P. B., (1986). "The botany of mangroves", Cambridge University Press. 

Ulaby, F. T., R. K. Moore, and A. K. Fung, (1986), "Microwave Remote Sensing, vol. III: From theory 

Ulaby, F. T and R. P. Jedlicka, (1984). "Microwave dielectric prop:rties of plant materials", IEEE Transactions on Geoscience and Remote Sensing, vol. GE-22, no. 4, pp. 406414. 

Ulaby, F. T and M. A. El-Rayes, (1987), "Microwave dielectric spectrum of vegetation - Part Ik dual - 

dispersion model", IEEE Transactions on Geoscience and Remote Sensing, vol. GE-25, no. 5, pp. 

Wang, Yong, Marc L. Imhoff, David S. Simonett, (1989). "Radar modeling of mangal forest stands", to 

to application", Artech House. 

550-557. 

be pulished in The Proceedings of the IGARSS'89. Vancouver, Canada, July, 1989. 

-. ~ . . . - .- - .- ... . ... . . . - . . - . . . . ..... - 
. . . . . . 

Samples (line * sample) 

- 11 - 

Total pixels 

Table 3.1. Stand samples extracted from SIR-B images 

Stands 

SGn 

SGf 

GSn 

GS f 

Gn 

Gf 

Ground conditions 

nonflooded 

flooded 

nonflooded 

flooded 

nonflooded 

flooded 

(10 * lo), (10 * 10). (11 * 6) 

(4 * 12), (10 * lo), (12 * 12) 

(7 * 20). (18 * 9) 

(17 * 19). (5 * 12:) 

(10 * lo), (10 * lo), (10 * 5) 

(7 * 25), (16 * 7) 

266 

292 

302 

383 

250 

287 

SGn is a stand with Sundri dominant and with Gewa present for ;I nonllooded surface; GSn has Gewa 

dominant and with Sundri present on nonflooded surfaces; and YO on (See also Table 3.2 for stand 

Stands Species < 4.9 5.-9.9 10.-14.9 15.-19.9 

characteristics). 

20.-24.9 25.-29.9 30.-34.9 35.-39.9 

GS 

-Sundri 42560 816 319 125 52 17 2 1 

Gewa 1340 493 250 72 16 5 0 0 

Sundri 42560 502 184 78 21 6 1 1 

Gewa 1340 1084 458 98 15 2 0 1 

Sundri 42560 142 34 16 8 2 0 3 1 I Gewa I 1340 1769 575 136 26 2 5 4 

Source: Chaffey, et al.. (1985). 
- 12 - 

Sundri 

Table 3.3. Regression models 

Hs = 4.769 + 0.414 * DS 0.672 

Height (m) on diameter (cm) for Gewa 

Gewa 

Regression models 

Cg = 1.840 + 0.188 * Dg 0.679 

I Gewa I Hg 0.505 I = 5.549 + 0.258 * Dg 

Sundri CS = 1.768 + 0.331 * Ds 0.589 

Canopy thickness (m) on diameten (cm) 

Regression models R2 value I 

Table 3.4. Mean canopy biomass (kg) per tree for each DBH segment 

DBH segment Species 

cm Gewa SUndri 

2.6 I < 4.9 2.9 I 

.' I 5.0 - 9.9 1 10.0 - 14.9 

15.0 - 19.9 27.6 74.9 

I 20.0 - 24.9 58.8 86.3 I 

86.3* I 25.0 - 29.9 125.4 I ~ I 86.3* 

86.3* 

30.0 - 34.9 267.5 

35.0 - 39.9 393.5 

*: Two sources of data were used to construct this table. In the field cunopy biomass measurements 

were made by a NASA and Bangladesh Science Team in October, 1984. For that data, there were no 

Sundri trees whose DBHs were over 25.0 cm. The second sow: of data was Chaffey, et al., (1985), 

for the same mea. They mapped the area into segments of different DBHs, including DBH's exceeding 

24.9 cm. However, they did not derive any measurements of canopy biomass. On merging the two 

data sets, the three highest DBH segments, lacked canopy biomass data. The same values as for 20.0 - 

24.9 cm were therefore employed. 
- 13 - 

Table 5.1. Conversion constants from DNs to dB for SIR-B images 

DT 104 4389.06 ~~ 

Formulas for conversion of SIR-B image DNs to a" in dBs is: 

a" = 10* log[DiV-C,,] - CZ 

where i = 1, 2, corresponding to I 

Marc Imhoff (1988, personal comn 

I 

0 

co 

0 

rl 

. 

rl 

4 

h 

B 

c 

-4 

6 

4 

a, 

u 

(d 

a 

m 

5 

c 

(d 

w 

u 

-4 

4J 

c 

0 

2 

a, 

4J 

(d 

k 

0 

4J 

u 

a, 

k 

-4 

% 

k 

(d 

5 

(d 

p: 

(d 

+l 

0 

-4 

w 

c 

a, 

4J 

X 

w 

a 

E: 

(d 

4J 

E: 

a,: >f+ 

oa, 

k5 

Dl0 

EX 

H 

:k 

a, 

-4J 

04J 

rlld 

ou rlw 

IX 

mu 

(d 

B 

am 

22 

$E 

22 

2 

.. 

.. 

cw 

W 

4 H 

. 

& 

k 

(d 

a, 

a 
Figure 2.1. Gewa tree models (from Tomlinson, 1986) 
 

- 15 - 

Figure 2.2. Sundri tree models (from Tomlinson, 1986) 
Figure 3.1. Model components of Sundri and Gewa forest stands 

(water-on or water-off) 
~ 

- 17 - 

Fcpre 5.1. Boxplots of forest stands at 26O incidence angle 

Y 

0 

LI 

01 

N 

I 1 

0 

d 

In 

rl 'I@ I 

I if 0 lT 

I 

I 

r i 

7 

I B I 

.. 

I 

I 

.. * I 

I 

i 

I 

I 

Gn Gf GSn GSf SGn SGf 

* 

I 

0 

* 

? 

k 

r 

* 

Gn Gf GSn GSf SGn SGf 

Flooded and/or Nonflooded surfaces 

. - . . .._ . . I . 
- 18- 

- Figure 5.2. Boxplots of forest stands at 46" incidence angle 

Y 

u) 

I I 

0 

FI 

I 

u) 

rl 

I 

0 

$4 al 

No 

(Y 

I i 

-4 

I 

I 

I A 

I 

L 1 

* I 

1 

AA 

- 

I 

Gn Gf GSn GSf SGn SGf 

* T * - * I 

I z 

L 

L - 

Gn Gf GSn GSf SGn SGf 

Flooded and/or Nonflooded surfaces