A. Luckman et al., TROPICAL FOREST BIOMASS DENSITY-ESTIMATION USING JERS-1 SAR - SEASONAL-VARIATION, CONFIDENCE-LIMITS, AND APPLICATION TO IMAGE MOSAICS, Remote sensing of environment, 63(2), 1998, pp. 126-139
This study describes the development of a semiempirical model for the
retrieval of above-ground biomass density of regenerating tropical for
est using JERS-1 Synthetic Aperture Radar (SAR). The magnitude and var
iability of the response of the L-band SAR to above-ground biomass den
sity was quantified using field data collected at Tapajos in central A
mazonia and imagery from a series of dates. A simple backscatter model
was fitted to this response and validated using image and field data
acquired independently at Manaus, 500 km to the west of Tapajos. The s
ources of variability in biomass density and SAR back-scatter were inv
estigated so as to determine confidence limits for the subsequent retr
ieval of biomass density using the model. This analysis suggested that
only three broad classes of regenerating forest biomass density may b
e positively distinguished. While the backscatter appears to saturate
at around 60 tonnes per hectare, the biomass limit for retrieval purpo
ses which is tolerant to both speckle and image texture is only 31 ton
nes per hectare. The spatial distribution of biomass density in centra
l Amazonia was estimated by applying the model to a mosaic of 90 JERS-
1 images. A favorable comparison of this distribution to a map of rege
neration derived from NOAA AVHRR imagery suggested that L-band SAR wil
l provide a useful method of monitoring tropical forests on a regional
scale. (C) Elsevier Science Inc., 1998.