Characterising windthrown gaps from fine spatial resolution remotely sensed data

This paper evaluates the potential of fine spatial resolution remotely sensed data for the identification and characterisation of windthrown gaps. The study site was Cwm Berwyn Forest, in central Wales, a planted forest of predominantly Sitka spruce (Picea sitchensis (Bong.) Carr.) containing windthrown gaps ranging in size from 50 to 3000m2. The remotely sensed data used were acquired by an 11 waveband airborne thematic mapper (ATM) sensor with a spatial resolution of ≈4m. This resolution is finer than the gaps on the site and comparable to that of future satellite sensors. A three class (gap, forest canopy and moorland) thematic land cover map was produced using a conventional maximum-likelihood classification of the data and provided an accurate representation of the classes (>90% of the pixels allocated correctly). This classification provided an accurate means of identifying windthrown gaps and was capable of identifying a greater number of gaps, than manual interpretation of temporally coincident aerial photographs. In addition, the magnitude and spatial distribution of class membership probabilities derived from the classification provided information on various gap properties, such as exposed soil and living, windthrown tree canopies. This may enable other properties such as windthrow direction to be inferred.