Started in the spring of 2008, this vegetation classification and mapping project being performed for the National Park Service encompasses over 136,000 acres of Redwood National and State Parks. The vegetation and terrain in this project range from the rocky shoreline and beach sands of the Northern California coast through the cathedral‐like redwood forests and up to the meadows, prairies and oak woodlands that crown the coastal ranges. 
GRS field crews were challenged by the steep terrain and extremely dense vegetation that is typical of this temperate rain forest. Field data are collected using quantitative measurement and analysis techniques employing the line-point sampling methodology in conjunction with the use of the GRS Densitometer and our field data collection software, TransIn. This technique has been successfully implemented in most of our image classification/landcover mapping projects.
GRS is implementing our Discrete Classification Mapping Methodology (DCMM) that we have developed over 20+ years of landcover mapping. Our process uses a unique combination of image processing and field data analysis techniques, including terrain correction, signature-driven training (field) site location, and plot-level image classification to produce maps with discrete estimates of measured vegetation components. These vegetation attributes will be used to assign vegetation classes based on the National Vegetation Classification System (NVCS). GRS also incorporates a rules-based pixel aggregation process to build pixels into polygons. This process is based upon an evaluation of the estimated vegetation/floristic characteristics of the different pixel classes to form polygons of similar floristic characteristics.
