A Continuous Field Remote Sensing Method for Estimating Net Primary Production of a Deciduous Forest

  • Abdullah F. Rahman Department of Range Wildlife and Fisheries Management, Texas Tech University
  • Vicente D. Cordova Department of Geography, Indiana University


A novel approach is developed for estimating Net Primary Production (NPP) of terrestrial ecosystems by combined use of image data from ocean and land bands of the moderate resolution imaging spectroradiometer (MODIS). Here we show how the MODIS ocean bands 11 and 12 can be used to derive a physiologically-driven spectral index, termed the photochemical reflectance index (PRI) that can track changes in landscape-level photosynthetic activity of a deciduous forest throughout the growing season. Combining this PRI with normalized difference vegetation index (NDVI) in a physiologically meaningful fashion resulted in a simple model capable of estimating landscape level NPP with remarkable accuracy (R2 = 0.88). Validation of the model with data from a different year produced less than 15% error in NPP estimation. Two inputs to our model are obtained from satellite data and the third one from ground-based flux tower. This model has the potential to produce a per-pixel ' continuous field' NPP output, contrary to the current pseudo-dynamic MODIS NPP products that depend on a priori assumptions, lookup tables, or literature values in addition to satellite and ground-based data.