Structural stage in Pacific Northwest forests estimated using simple mixing models of multispectral images

We identified stages of regrowth in replanted clearcuts in Douglas-fir/western hemlock forests in the Gifford Pinchot National Forest, southern Washington, USA, using a simple four-endmember constrained linear spectral mixing model applied to a multispectral Landsat Thematic Mapper image in order to separate and quantify spectral contributions from significant scene components. Spectral unmixing produces images of the fractional amount of the spectral endmembers, which were green vegetation, nonphotosynthetic vegetation, soil and “shade,” which includes topographic shading and shadows. Changes in endmember fractions correspond to changes in surface composition (as viewed from above). Unresolved shadows comprise the primary indicator of canopy structure and hence, regrowth stage. To isolate shadows, shading predicted from a digital elevation model was removed from the image before mixture analysis. As stands regrow, the surface cover shifts from initial high proportion of slash and exposed soil, and low proportions of green vegetation and shadows, to low fractions of stems and soil with high fractions of green vegetation and shadows. This shift in surface composition defines a regrowth trend in an endmember fraction data space. Projection of data onto this line allows estimation of structural stage and stand age, and provides a framework for remote mapping and monitoring of forest regrowth. Field analysis of 495 forest stands, representing stand structural stages ranging from newly replanted cuts to stands greater than 250 years in age, was used to assess the accuracy and precision of predicted structural stages and stand ages. The spectral unmixing approach can be used to evaluate and monitor forest regrowth quickly over large areas of the Pacific Northwest forests, and is extendible to mapping basic vegetation community type as well as structural stage.