Analysis of Forest Structure Using Thematic Mapper Simulator Data

Abstract

Remotely sensed data from forested landscapes contain information on both cover type and structure. Structural properties include crown closure, basal area, leaf area index, and tree size. Cover type and structure together are useful variables for designing forest volume inventories. The potential of Thematic Mapper Simulator (TMS) data for sensing forest structure has been explored by principal components and feature selection techniques. Improved discrimination over multispectral scanner (MSS) data proved possible in a mixed conifer forest in Idaho for estimating crown closure and tree size (saplings/seedlings, pole, sawtimber). Classification accuracy increased monotonically with the addition of new channels up to seven; the four optimum channels were 4, 7, 5, and 3. The analysis of TMS data for 123 field sites in Sequoia National Park indicated that canopy closure could be well estimated by a variety of bands or band ratios (r = 0.62-0.69) without reference to forest type. Estimation of basal area was less successful ( r = 0.51 or less) on average, but improved for certain forest types when data were stratified by floristic composition. To achieve such a stratification, sites were ordinated by a detrended correspondence analysis (DECORANA) based on the canopy of dominant species. Within forest types, canopy closure continued to be the best predictor of spectral variation. Total basal area could be predicted in certain forest types with improved or moderate reliability using various linear ratios of TMS bands (e. g., red fir, 5/4, r = 0.76; lodgepole pine, 4/3, r = 0.82).