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COMBINING LIDAR ESTIMATES OF BIOMASS AND LANDSAT ESTIMATES OF STAND AGE FOR SPATIALLY EXTENSIVE VALIDATION OF MODELED FOREST PRODUCTIVITY. (R828309)
Citation:
Lefsky, M. A., D. P. Turner, M. Guzy, AND W. B. Cohen. COMBINING LIDAR ESTIMATES OF BIOMASS AND LANDSAT ESTIMATES OF STAND AGE FOR SPATIALLY EXTENSIVE VALIDATION OF MODELED FOREST PRODUCTIVITY. (R828309). REMOTE SENSING OF ENVIRONMENT (2005).
Description:
Extensive estimates of forest productivity are required to understand the
relationships between shifting land use, changing climate and carbon storage
and fluxes. Aboveground net primary production of wood (NPPAw) is a major component
of total NPP and of net ecosystem production (NEP). Remote sensing of NPP and
NPPAw is generally based on light use efficiency or process-based biogeochemistry
models. However, validating these large area flux estimates remains a major
challenge. In this study we develop an independent approach to estimating NPPAw,
based on stand age and biomass, that could be implemented over a large area
and used in validation efforts. Stand age is first mapped by iterative unsupervised
classification of a multi-temporal sequence of images from a passive optical
sensor (e.g. Landsat TM). Stand age is then cross-tabulated with estimates
of stand height and aboveground biomass from lidar remote sensing. NPPAw is
then calculated as the average increment in lidar-estimated biomass over the
time period determined using change detection. In western Oregon, productivity
estimates made using this method compared well with forest inventory estimates
and were significantly different than estimates from a spatially distributed
biogeochemistry model. The generality of the relationship between lidar-based
canopy characteristics and stand biomass means that this approach could potentially
be widely applicable to landscapes with stand replacing disturbance regimes,
notably in regions where forest inventories are not routinely maintained.
Keywords: Lidar estimates; Aboveground biomass; Landsat