Remote sensing of forest canopy gaps

Abstract

This thesis evaluates the potential of fine (<5 m) spatial resolution remotely sensed data and alternative classification methods to characterise 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 3000 m². The remotely sensed data used were acquired by an 11 waveband airborne thematic mapper (ATM) sensor with a spatial resolution of � 4m. This spatial resolution is finer than the windthrown gaps on the site and comparable to that of future satellite sensors. A thematic map depicting land cover was produced using a conventional maximum-likelihood classification of the ATM data and provided an accurate representation of the land cover (> 90% of the pixels allocated correctly). This hard classification was also softened to output typicality and posterior class membership probabilities.

The results indicated that the hard classification provided an accurate means of identifying windthrown gaps (>95% of known gaps identified) and was capable of identifying a greater number of gaps, than manual interpretation of temporally coincident aerial photographs. Estimates of windthrown gap area, perimeter and shape were derived from the hard and softened classifications. The results indicated the potential to derive more accurate spatial representations of windthrown gaps than a conventional hard classification, by softening the output to derive typicality class membership probabilities. However, the major contribution of the research within this thesis to previous work on windthrown gap formation and progression, is the potential to use rate of change of typicality and posterior class membership probabilities to derive information on various windthrown gap properties, such as exposed soil and living windthrown tree canopies.

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