Improved Estimates Of Net Primary Productivity From MODIS Satellite Data At Regional And Local Scales

Abstract

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak-hickory forests in the region. However, MODIS underestimated NPP for less-dominant northern hardwood forests and overestimated NPP for coniferous forests. Causes of inaccurate estimates of NPP by MODIS were (1) an aggregated classification and parameterization of diverse deciduous forests in different climatic environments into a single class that averages different radiation conversion efficiencies; and (2) lack of soil water constraints on NPP for forests or areas that occur on thin or sandy, coarse-grained soil. We developed the "available soil water index" for adjusting the MODIS NPP estimates, which significantly improved NPP estimates for coniferous forests. The MODIS NPP estimates have many advantages such as globally continuous monitoring and remarkable accuracy for large scales. However, at regional or local scales, our study indicates that it is necessary to adjust estimates to specific vegetation types and soil water conditions.