Evaluating the type and state of Alaska taiga forests with imaging radar for use in ecosystem models

Changes in the seasonal CO₂ flux of the boreal forests may result from increased atmospheric CO₂ concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO₂ flux and its seasonal amplitude based on meteorological data, are required. The authors address the use of synthetic aperture radar (SAR) to map forest type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO₂ flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO₂ flux. CO ₂ flux maps are generated, from which areal estimates of CO ₂ flux are derived