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Peat Mapping Associations of Airborne Radiometric Survey Data
British Geological Survey, Keyworth, Nottingham NG12 5GG, UK
Received: 27 September 2013; in revised form: 13 December 2013 / Accepted: 23 December 2013 / Published: 3 January 2014
Abstract: This study considers recent airborne radiometric (gamma ray) survey data, obtained at high-resolution, across various regions of the UK. The datasets all display a very evident attenuation of signal in association with peat, and intra-peat variations are observed. The geophysical response variations are examined in detail using example data sets across lowland areas (raised bogs, meres, fens and afforested peat) and upland areas of blanket bog, together with associated wetland zones. The radiometric data do not map soils per se. The bedrock (the radiogenic parent) provides a specific amplitude level. Attenuation of this signal level is then controlled by moisture content in conjunction with the density and porosity of the soil cover. Both soil and bedrock variations need to be jointly assessed. The attenuation theory, reviewed here, predicts that the behaviour of wet peat is distinct from most other soil types. Theory also predicts that the attenuation levels observed across wet peatlands cannot be generally used to map variations in peat thickness. Four survey areas at various scales, across England, Scotland, Wales and Ireland are used to demonstrate the ability of the airborne data to map peat zones. A 1:50 k national mapping of deep peat is used to provide control although variability in the definition of peat zones across existing databases is also demonstrated.
Keywords: remote sensing; airborne geophysical; radiometric; peat; wetland; mapping
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MDPI and ACS Style
Beamish, D. Peat Mapping Associations of Airborne Radiometric Survey Data. Remote Sens. 2014, 6, 521-539.
Beamish D. Peat Mapping Associations of Airborne Radiometric Survey Data. Remote Sensing. 2014; 6(1):521-539.
Beamish, David. 2014. "Peat Mapping Associations of Airborne Radiometric Survey Data." Remote Sens. 6, no. 1: 521-539.