Image modelling of forest changes associated with acid mine drainage
A planar cellular transition model was investigated as a predictive methodology for modeling tree canopy dynamics along a chemical contamination gradient adjacent to an acid mine. Stochastic raster transitions were developed as a function of both proximity to the tailings and local stem density neighborhood configuration. Model inputs consisted of scanned and registered archival photographs that were segmented into three forest classes using two different apex delineation techniques, one incorporating double-aspect calculations and the other using a high-pass filter. The results for each were integrated over selected sample windows. The accuracy of the two techniques was compared using a synthetic data set. The double-aspect technique was better able to identify and delineate tree crowns in synthetic data with significant noise and shadow representative of typical forest conditions. However, the window integration results were more visually interpretable when classes were derived from the high-pass technique. Application of these techniques to the archival photography and subsequent temporal analysis using the MannKrendall statistic revealed significant forest degradation over a 40-year period nearer the tailings and within areas of mixed canopy types.
acid mine drainage tree density mapping geographic raster modeling mixed forest canopy automata archival air photography landscape change