Canopy Estimation in Logged Forests in the Brazilian Amazon using IKONOS Imagery

Structural properties of forests are closely linked with ecosystem functioning. Forest disturbance and canopy gaps are important in an ecological sense because tree regeneration dynamics are a major component of the carbon cycle and closely linked to species diversity. Previously, we developed a crown detection algorithm that used high resolution satellite image data. We applied this algorithm in an undisturbed tropical forest with good results. In this work we have further developed the algorithm to examine logged forests and the disturbances of such forests. Patios and gaps created by logging have high reflectance in the visible bands, but also have a spectral signature that is distinguishable from local maxima associated with tree tops. By using the multi- spectral image of IKONOS along with the higher resolution panchromatic image, our refined algorithm was able to identify and filter out these non-vegetated features. Differences were found between the undisturbed and logged sites within each image. Temporal differences were also found for the same area between the two images. Logged areas had smaller average crown sizes and more trees. The removal of larger trees for timber likely exposed smaller canopies previously shaded by the large trees. These initial results suggest that our automated crown detection algorithm may be useful for identification of logged areas and diagnosis of logging damage and regeneration.