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dc.contributor.authorGatis, N
dc.contributor.authorLuscombe, D
dc.contributor.authorCarless, D
dc.contributor.authorParry, L
dc.contributor.authorFyfe, R
dc.contributor.authorHarrod, T
dc.contributor.authorBrazier, RE
dc.contributor.authorAnderson, K
dc.date.accessioned2018-08-13T07:50:45Z
dc.date.issued2019-02-01
dc.identifier.issn0016-7061
dc.identifier.issn1872-6259
dc.identifier.urihttp://hdl.handle.net/10026.1/12012
dc.description.abstract

A method to estimate peat depth and extent is vital for accurate estimation of carbon stocks and to facilitate appropriate peatland management. Current methods for direct measurement (e.g. ground penetrating radar, probing) are labour intensive making them unfeasible for capturing spatial information at landscape extents. Attempts to model peat depths using remotely sensed data such as elevation and slope have shown promise but assume a functional relationship between current conditions and gradually accrued peat depth. Herein we combine LiDAR-derived metrics known to influence peat accumulation (elevation, slope, topographic wetness index (TWI)) with passive gamma-ray spectrometric survey data, shown to correlate with peat occurrence, to develop a novel peat depth model for Dartmoor. Total air absorbed dose rates of Thorium, Uranium and Potassium were calculated, referred to as radiometric dose. Relationships between peat depth, radiometric dose, elevation, slope and TWI were trained using 1334 peat depth measurements, a further 445 measurements were used for testing. All variables showed significant relationships with peat depth. Linear stepwise regression of natural log-transformed variables indicated that a radiometric dose and slope model had an r2 = 0.72/0.73 and RMSE 0.31/0.31 m for training/testing respectively. This model estimated an area of 158 ±101 km2 of peaty soil >0.4 m deep across the study area. Much of this area (60 km2) is overlain by grassland and therefore may have been missed if vegetation cover was used to map peat extent. Using published bulk density and carbon content values we estimated 13.1 Mt. C (8.1–21.9 Mt. C) are stored in the peaty soils within the study area. This is an increase on previous estimates due to greater modelled peat depth. The combined use of airborne gamma-ray spectrometric survey and LiDAR data provide a novel, practical and repeatable means to estimate peat depth with no a priori knowledge, at an appropriate resolution (10 m) and extent (406 km2) to facilitate management of entire peatland complexes.

dc.format.extent78-87
dc.languageen
dc.language.isoen
dc.publisherElsevier
dc.subjectGamma-ray attenuation
dc.subjectLiDAR
dc.subjectRemote sensing
dc.subjectPeat depth
dc.subjectSoil organic carbon
dc.subjectPeatland
dc.titleMapping upland peat depth using airborne radiometric and lidar survey data
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000447095700008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.volume335
plymouth.publication-statusPublished
plymouth.journalGeoderma
dc.identifier.doi10.1016/j.geoderma.2018.07.041
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Admin Group - REF
plymouth.organisational-group/Plymouth/Admin Group - REF/REF Admin Group - FoSE
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Geography, Earth and Environmental Sciences
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA14 Geography and Environmental Studies
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2018-07-27
dc.rights.embargodate2018-8-14
dc.identifier.eissn1872-6259
dc.rights.embargoperiodNot known
rioxxterms.funderNatural Environment Research Council
rioxxterms.identifier.projectSouth West Partnership for Environment and Economic Prosperity (SWEEP)
rioxxterms.versionVersion of Record
rioxxterms.versionofrecord10.1016/j.geoderma.2018.07.041
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2019-02-01
rioxxterms.typeJournal Article/Review
plymouth.funderSouth West Partnership for Environment and Economic Prosperity (SWEEP)::Natural Environment Research Council


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