3. Application of Radar Theory to Published Research
The effectiveness of the earlier presented theories, models and indices in providing measures of forest aboveground biomass and stand structure is assessed and demonstrated by applying them to actual and modeled data published related works of other investigators. As most of the data and results from the published papers are reported in the form of graphs, interpolation was done to obtain measurements for the backscattering coefficients and the corresponding forest biomass levels.

3.1 Data Sources
Listed and individually described in Table 1 are the different studies used in the assessment of the theories and concepts previously presented. All but two of the studies involved the use of either SIR -C/S-AR or AIRSAR system. In all of these, the HV and VH polarizations were regarded as identical and only the HV data were hence included in the analysis. The incidence angles utilized ranged from 19°-50° and varying but closely related saturation limits were observed.

3.2 Radar backscatter versus forest biomass
All of the studies considered here, and most of the research so afar reported in the literature, have correlated radar backscatter with forest biomass using single radar wavelength and polarization combinations. Although some of the forests investigated are composed of broad-leaved and mixed broad-leaved/needle-leaved species, the majority of the sites are vegetated by managed, even-aged and mono-specific coniferous stands located in temperate zones. Due to known difficulties associated with rugged topography, the different forests areas selected as study sites are located in flat to moderately-sloping areas.

In the interpolation of data from the different studies, only the L-HV backscattering dta were taken into account owing to the concepts discussed earlier. This qualification limited the number of cases considered, as only a few of the related investigations have used either or both of the L-HV and C-HV backscattering data. A maximum of 300 tons/ha was used in view of the typical saturation of radar measurements at all bands beyond this biomass level. For both L-HH and C-HV, so was observed to increase linearly with biomas until the saturation level for each of these wavelength-polarization combinations is reached. The TCB and TCM indices were computed based on the intensity (or true) values of the individual backscattering data i.e. not decibels. The s^o values were converted into intensity values through the formula
X = - log (s° /10)           (8)
where x is intensity or true value and s° the backscattering coefficient (in decibel). No significant variation was observed between the TCBI and TCMI values within the same stand structure category from the different investigations. The similarity in the values of these indices occurred over the entire biomass range, except for some cases at low biomass levels, where inconsistent results were obtained. Factors such as strong influence of terrain/ground conditions on the radar backscatter due to low stand/crown component volume and density, may have caused these results. In general, at biomas levels below the radar saturation limits, positive linear relationships between total aboveground biomass and the two indices were observed. In comparing these index values, the effects on the data of factors such as dissimilarities in the radar systems used (e.g. viewing angle and platform altitude), discrepancies in the applies calibration methods, terrain variations, stand interpolation of the backscattering data and biomass levels, should however be noted.

The correlation between forest biomass and L-HH, and TCBI are presented in Table 2.

3.2.1 TCBI and total forest aboveground biomass
Table 2 indicates that in the case of C-HV, the use of TCBI (L-HH + C-HV) brought about a better correlation between radar backscatter and total forest biomass. On the other hand, in the case of L-HH, mixed results were obtained. Although much is still to be desired regarding both the number of cases and data considered, this finding is generally in support of the theory presented above (see equation (5)). Following are biomass equations derived based on linear regression analysis performed on the TCBI and biomass data from the various studies.
Table 1. List and description of the different studies in the assessment of concepts and theories.

INVESTIGATORS	SAR Backscatter	CORRELATION COEFICIENT
		PINE/CONIFER		BROADLEAF
		Biomass (tons/ha)		Biomass (tons/ha)
		0-300	20 - 150	0 - 300	20 - 150
1.IMHOFF,M.L.(1993)	L-HH	0.7354	0.3140	0.8219	0.9321
	C-HV	0.6378	0.0051	0.6801	0.7926
	L-HH+C-HV	0.6579	0.3002	0.8134	0.9326
2.KARAM,et al.(1995)	L-HH	0.7004	0.6347
	C-HV	-0.0369	-0.2083
	L-HH+C-HV	0.5990	0.5571
3.HSU,C.C.et al. (1993)	L-HH	0.8086	0.7581
	C-HV	0.1037	0.2417
	L-HH+C-HV	0.6792	0.6131
4.SOUYRIS,et al. (1995)	L-HH	0.7907	0.8764
	C-HV	0.4919	-0.0020
	L-HH+C-HV	0.8264	0.8289
5.DOBSON,et al.(1992)	L-HH	0.8731	0.9705
	C-HV	0.7952	0.4900
	L-HH+C-HV	0.8769	0.8996
6.DOBSON,et al.(1995a)	L-HH	0.4037	0.8322	0.0182	0.2317
	C-HV	0.7952	0.4900	0.4431
	L-HH+C-HV	0.8769	0.8996	0.5345	0.7759
7.DOBSON,et al.(1995b)	L-HH		0.7999
8.HARISTENSEN dt al. (1990)	L-HH	0.9888	0.9879
9.CHRISTENSEN et al.(1990)	L-HH	0.9665	0.9659
10.MOGHADDAM,et al.('94)	C-HV*			0.9744
11.RANSON & SUN (1994)	C-HV*			0.5113	0.6393
12. RANSON et al. (1995)	L-HH*			0.8544	0.9557

Note: * = Mixed pine and broad-leaved forest vegetation

Table 2. Correlation between forest biomass and L-HH, C-HV, and L-HH + C-HV backscatter