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Estimation of forest biophysical characteristics in Northern Michigan with SIR-C/X-SAR

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12 Author(s)
Dobson, M.C. ; Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA ; Ulaby, F.T. ; Pierce, L.E. ; Sharik, T.L.
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A three-step process is presented for estimation of forest biophysical properties from orbital polarimetric SAR data. Simple direct retrieval of total aboveground biomass is shown to be ill-posed unless the effects of forest structure are explicitly taken into account. The process first involves classification by (1) using SAR data to classify terrain on the basis of structural categories or (2) a priori classification of vegetation type on some other basis. Next, polarimetric SAR data at L- and C-bands are used to estimate basal area, height and dry crown biomass for forested areas. The estimation algorithms are empirically determined and are specific to each structural class. The last step uses a simple biophysical model to combine the estimates of basal area and height with ancillary information on trunk taper factor and wood density to estimate trunk biomass. Total biomass is estimated as the sum of crown and trunk biomass. The methodology is tested using SIR-C data obtained from the Raco Supersite in Northern Michigan on Apr. 15, 1994. This site is located at the ecotone between the boreal forest and northern temperate forests, and includes forest communities common to both. The results show that for the forest communities examined, biophysical attributes can be estimated with relatively small rms errors: (1) height (0-23 m) with rms error of 2.4 m, (2) basal area (0-72 m2/ha) with rms error of 3.5 m2/ha, (3) dry trunk biomass (0-19 kg/m2 ) with rms error of 1.1 kg/m2, (4) dry crown biomass (0-6 kg/m2) with rms error of 0.5 kg/m2, and (5) total aboveground biomass (0-25 kg/m2) with rms error of 1.4 kg/m2. The addition of X-SAR data to SIR-C was found to yield substantial further improvement in estimates of crown biomass in particular. However, due to a small sample size resulting from antenna misalignment between SIR-C and X-SAR, the statistical significance of this improvement cannot be reliably established until further data are analyzed. Finally, the results reported are for a small subset of the data acquired by SIR-C/X-SAR

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:33 ,  Issue: 4 )