4.5 Article

Mapping hydraulic biotopes using terrestrial laser scan data of water surface properties

Journal

EARTH SURFACE PROCESSES AND LANDFORMS
Volume 35, Issue 8, Pages 918-931

Publisher

WILEY
DOI: 10.1002/esp.1948

Keywords

terrestrial laser scanning (TLS); LiDAR; biotope; water surface roughness; hydraulic habitat

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For more than a decade, habitat mapping using biotopes (in-channel hydraulically-defined habitats) has underpinned aquatic conservation in the UK through (a) providing baseline information on system complexity and (b) allowing environmental and ecological change to be monitored and evaluated. The traditional method used is the subjective river habitat or corridor survey. This has recently been revised to include the floodplain via GeoRHS, but issues still exist concerning development of a national database clue to the labour intensive nature of the data collection, subjectivity issues between samplers, temporal changes, the fuzzy nature of perceived habitats and habitat boundaries. This paper takes an innovative approach to biotope definition using high resolution spatial data to define water surface roughness for two representative reaches of the River South Tyne, Cumbria, and the River Rede, Northumberland, UK. Data was collected using a terrestrial laser scanner (TLS) and hydraulic variability simply expressed through assigning a local standard deviation value to a set of adjacent water surface values. Statistical linkage of these data with biotope locations defined visually in the field allowed complete mapping of the surveyed reach defining habitat and biotope areas to the fine scale resolution of the TLS data. Despite issues of data loss due to absorption and transmission through the water, the reflected signal generated an extremely detailed and objective map of the water surface roughness, which may be compared with known biotope locations as defined by visual identification in the field. The TLS accuracy achieved in the present study is comparable with those obtained using hyperspectral imagery: with 84% of the pool/glide/marginal deadwater amalgamated biotope, 88% of riffles, 57% of runs and 50% of the amalgamated cascade/rapid biotope successfully plotted. It is clear from this exercise that biotope distribution is more complex than previously mapped using subjective techniques, and based upon the water surface roughness delimiters presented in this study, the amalgamation of pools with glides and marginal dead-waters, riffles with unbroken standing waves, and cascades with rapids, is proposed. Copyright (C) 2010 John Wiley & Sons, Ltd.

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