Predicting tropical forest carbon from EO-1 hyperspectral imagery in Noel Kempff Mercado National Park, Bolivia

Abstract

An increasing interest in the ability of tropical forests to sequester large amounts of carbon has pushed scientists to look for new ways to acquire accurate estimates of biomass and other forest structural attributes over large, remote areas. We used hyperspectral images acquired in the fall of 2001 from the Hyperion imaging spectrometer to predict aboveground biomass in Noel Kempff Mercado National Park in the Bolivian Amazon. Forest structure data was collected from plots throughout the park in 1997 and 1999. We employed multiple linear regression to predict total carbon, aboveground carbon, carbon in wood, understory carbon and soil carbon as a function of reflectance at wavelengths in the visible, near infrared and short-wave infrared. The results are promising, although some uncertainty remains due to striping and geolocation error.