Separation of dead tree crowns from the oak woodland forest mosaic by integrating spatial information

Abstract

A stratified method of separating dead tree crowns from the forest mosaic, especially bare soil, is proposed. Both spectral and spatial information extracted from 1 m high-resolution digital airborne imagery was used. First, spectrally homogeneous objects were recognized based on a Normalized Difference Vegetation Index (NDVI) image. From this image, large patches of bare soil and small patches of noise were excluded by object-size thresholding. Next, an incomplete bare soil image was generated from thresholding the red band using a histogram-based method. A region-based subtraction algorithm was developed and performed on the homogeneous object image and the bare soil image to remove most small patches of bare soil. Finally, medium-sized patches of bare soil were deleted using the assumption that bare soil areas are spatially much closer to larger, pure bare soil areas. The method proved to be effective. The classification accuracy of dead tree crowns was increased from 21% to 75%.