{'fraction_non_alphanumeric': 0.021119324181626188, 'fraction_numerical': 0.0, 'mean_word_length': 5.076923076923077, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Forest canopy gap detection and characterisation by the use of high- resolution Digital Elevation Models

The remote identification of forest canopy gaps from Digital Elevation Models (DEMs) built from aerial photographs is potentially a viable alternative to ground-based field surveys. In this study a DEM-based gap-finding algorithm, given suitable experimentally determined input parameters, yielded canopy gap statistics for a study area that were consistent with ground-based survey data from the same area. The method could thus be 'trained' to replicate ground-based results for a small test area of beech (Nothofagus) forest, with the potential for it to be applied to larger areas of forest of a similar type to gather canopy gap data with relatively little additional field work. The use of a DEM-based method also has the advantage that the results are easily analysed and mapped using commonly available GIS and cartographic software.