Modeling Forest Net Primary Productivity with Reduced Uncertainty by Remote Sensing of Cover Type and Leaf Area Index

  • Steven E. Franklin


Process-based ecosystem models have emerged as a powerful new tool in forest management with applications at multiple scales (Landsberg and Gower 1997; Waring and Running 1998; see also Running et al. 1989; Running 1990; Peterson and Waring 1994; Ruimy et al. 1994; Green et al. 1996; Hunt et al. 1996; Milner et al. 1996; McNulty et al. 1997; Coops 1999; Landsberg and Coops 1999). Resource managers can use ecosystem models to describe the state of a forest at a point in time relative to a range of potential management treatments, and to generate projections of future growth and stand development. As commercial forestry approaches the sustainable limit of resource use in a wide range of ecological settings, the value of these process models as new tools and an information source for managers in a wide variety of applications, including wildlife habitat mapping, biodiversity monitoring, and forest growth assessment, is increasingly clear. For example, the models can be used to estimate stand or site net primary production (NPP) when the necessary information on species, soils, topography, and climate are available. Improved ecosystem process models in the future may replace empirical stand growth and yield models (Landsberg and Coops 1999).


Remote Sensing Cover Type Leaf Area Index Forest Inventory Photogrammetric Engineer 
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