A Comparison of Multispectral and Multitemporal Information in High Spatial Resolution Imagery for Classification of Individual Tree Species in a Temperate Hardwood Forest

Multitemporal, small-format 35-mm aerial photographs were combined in a coregistered database to determine the relative value of spectral and phenological information for overstory tree crown classification of digital images of the Eastern Deciduous Forest. A one-hectare study site, located in a second-growth forest 15 km east of Morgantown, West Virginia, USA, was photographed from a light aircraft nine times from May to October 1997 using both true-color and false-color infrared film. Using this imagery, differences in the spectral properties and timing of phenologic events between tree species made it possible to discriminate four deciduous tree species, namely Liriodendron tulipifera, Acer rubrum, Quercus rubra, and Quercus alba, which made up nearly 99% of the trees at this study site. Optimally timed photography acquired during peak autumn colors provided the best single date of imagery, while photography from spring leaf-out was the second best. The best individual image band for tree species discrimination was the blue band. Classifications using all four spectral bands (blue, green, red, and infrared) and four dates (05/23/97, 06/23/97, 10/11/97, and 10/30/97) provided the best classification accuracies. Variable canopy illumination made digital classification of individual trees complex. A Likelihood Ratio test confirmed that the number of spectral bands included in the classification procedure (spectral resolution) and the number of dates (temporal resolution) significantly influenced the ability to identify tree species correctly. This study suggests that although multispectral data appear to be more valuable than multitemporal data, it may be possible to compensate for the limited spectral resolution of planned high-resolution sensors by combining multiple dates of low spectral resolution images.