Airborne radiometric survey data and a DTM as covariates for regional scale mapping of soil organic carbon across Northern Ireland

Rawlins, Barry; Marchant, B. P.; Smyth, David H.; Scheib, C.; Lark, R. M.; Jordan, Colm

doi:10.1111/j.1365-2389.2008.01092.x

Cited by 73 publications

(50 citation statements)

References 21 publications

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“…Across the soils of eastern England, the study by Rawlins et al (2007) indicated that the radiometric signals are useful for making thematic maps of soil and confirmed that a large proportion of the thorium (Th) and potassium (K) signals can be accounted for by parent material. Additionally, the airborne data (K signal) from Northern Ireland (NI) were used to study methods for improving current estimates of soil organic carbon (SOC) (Rawlins et al, 2009). The use of gamma ray attenuation (considered here) in conjunction with other airborne geophysical data (conductivity) was discussed in relation to the characterisation of wetland sites in North Wales by Beamish and Farr (2011).…”

Section: Introductionmentioning

confidence: 99%

Gamma ray attenuation in the soils of Northern Ireland, with special reference to peat

Beamish

2013

Journal of Environmental Radioactivity

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This study considers gamma ray attenuation in relation to the soils and bedrock of Northern Ireland using simple theory and data from a high resolution airborne survey. The bedrock is considered as a source of radiogenic material acting as parent to the soil. Attenuation in the near-surface is then controlled by water content in conjunction with the porosity and density of the soil cover. The Total Count radiometric data together with 1:250k mapping of the soils and bedrock of Northern Ireland are used to perform statistical analyses emphasising the nature of the low count behaviour. Estimations of the bedrock response characteristics are improved by excluding areas covered by low count soils (organic/humic). Equally, estimations of soil response characteristics are improved by excluding areas underlain by low count bedrock (basalt). When the spatial characteristics of the soilclassified data are examined in detail, the low values form spatially-coherent zones (natural clusters) that can potentially be interpreted as areas of increased water content for each soil type. As predicted by theory, the highest attenuation factors are associated with the three organic soil types studied here. Peat, in particular, is remarkably skewed to low count behaviour in its radiometric response. Two detailed studies of blanket bogs reveal the extent to which peat may be mapped by its radiometric response while the intra-peat variations in the observed response may indicate areas of thin cover together with areas of increased water content.

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Section: Introductionmentioning

confidence: 99%

Gamma ray attenuation in the soils of Northern Ireland, with special reference to peat

Beamish

2013

Journal of Environmental Radioactivity

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“…Sampling depths will vary according to the soil density. For example, gamma-rays measured from low-density organic-rich soils are thought to emanate from up to one meter depth (Rawlins et al, 2009). Almost all gamma radiation detected near or at the Earth's surface results from the radioactive decay of K, Th and U. Potassium abundance is measured by gamma-ray photons emitted when 40 K decays to argon ( 40 Ar).…”

Section: Background -Gamma-ray Spectrometrymentioning

confidence: 99%

A weathering intensity index for the Australian continent using airborne gamma-ray spectrometry and digital terrain analysis

Wilford

2012

Geoderma

149

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“…We may also expect that, as our soil knowledge becomes increasingly comprehensive, and as proximal remote sensors become increasingly well-tailored to measuring soil properties, and increase in resolution, so the extent to which we can explain the spatially correlated component of the variation of soil properties should increase. This is illustrated, for example, by Rawlins et al (2009) who showed the variogram function for the random effects in a model of soil organic carbon decreasing both in sill variance and in the range as more terms were added to the fixed effects part of the model. In short, as we increase the content and sophistication of the soil knowledge of our statistical models so we should examine the possibility that the unexplained variation will not show spatial dependence within the frequency range resolved by the sampling.…”

Section: Introductionmentioning

confidence: 99%

Distinguishing spatially correlated random variation in soil from a ‘pure nugget’ process

Lark

2012

Geoderma

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In most spatial analysis of soil variation it is assumed that the random variation not captured by fixed effects (class means or continuous covariates) is spatially dependent. It is proposed that this should be tested formally, both to justify the kriging component in subsequent spatial prediction and as evidence of the extent to which the included fixed effects have succeeded in accounting for soil variation that is spatially dependent at the scales resolved by the soil sampling. A formal test is possible by computing the log ratio of the likelihoods for a full model with spatially dependent random effects and a null model which is pure nugget. It is shown that the sampling distribution of the log likelihood-ratio under the null model is not χ 2 (p) where p is the number of additional random effects parameters in the model with spatial dependence. This is because, while the null model is nested in the full model, parameters of the full model take bounding values in the null case. The sampling distribution may be computed by Monte Carlo simulations. It is shown that the power to reject the null model by the log likelihood-ratio test depends on the importance of the nugget effect in the underlying model, and on the sampling scheme. In many circumstances it may be hard to demonstrate spatial dependence. The recommended procedure was applied to some data on the organic carbon content of the topsoil and subsoil of a field inEngland. This was modelled either with the overall mean the only fixed effects, or with separate means for different soil map units as fixed effects. There was significant evidence for spatial dependence in the random effects at both depths when the overall mean was the only fixed effect. When map unit means were used as fixed effects there was significant, though weaker, spatial dependence in the topsoil, but the null model could not be rejected for the subsoil. This has implications for any further sampling to map organic carbon in the subsoil.

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Airborne radiometric survey data and a DTM as covariates for regional scale mapping of soil organic carbon across Northern Ireland

Abstract: (non-peat) could be achieved.

Cited by 73 publications

References 21 publications

Gamma ray attenuation in the soils of Northern Ireland, with special reference to peat

Gamma ray attenuation in the soils of Northern Ireland, with special reference to peat

A weathering intensity index for the Australian continent using airborne gamma-ray spectrometry and digital terrain analysis

Distinguishing spatially correlated random variation in soil from a ‘pure nugget’ process

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