Gamma-ray remote sensing of aeolian salt sources in the Murray–Darling Basin, Australia

Bierwirth, P. N.; Brodie, Ross

doi:10.1016/j.rse.2007.05.012

Cited by 16 publications

(11 citation statements)

References 20 publications

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“…Due to limited amount of sampling sites (only 68 sites were sampled) and available funds and labor, the sampling might not be a good representation for large areas. Remote sensing technology, on the other hand, provides a viable alternative to traditional field work due to its large area coverage, multiple spectra information and nearly constant observation (Bell et al, 2001;Bierwirth and Brodie, 2008;Douaoui et al, 2006;Farifteh et al, 2007;Metternicht and Zinck, 2003;Mulder et al, 2011;Taghizadeh-Mehrjardi et al, 2014). This is especially true since higher resolution imageries become readily available.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and evaluating spatial variability of soil salinity in dry and wet seasons in the Werigan–Kuqa Oasis, China, using remote sensing and electromagnetic induction instruments

Ding

2014

Geoderma

152

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Section: Introductionmentioning

confidence: 99%

Monitoring and evaluating spatial variability of soil salinity in dry and wet seasons in the Werigan–Kuqa Oasis, China, using remote sensing and electromagnetic induction instruments

Ding

2014

Geoderma

152

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“…Th and U) compared with EC a . This is consistent with Bierwirth & Brodie (), who reported counting errors and noise associated with γ ‐ray collection around 10% for a single measurement. With regard to the EC a measurements, possible errors include differences in soil moisture and temperature (Sudduth et al ., ); the instrument may have been affected by close proximity to either a head or tail ditch which may have recently been wet owing to an irrigation event and which is not representative of soil moisture in dryland areas.…”

Section: Resultsmentioning

confidence: 99%

An error budget for digital soil mapping of cation exchange capacity using proximally sensed electromagnetic induction and remotely sensed γ‐ray spectrometer data

Huang

Bishop

Triantafilis

2017

Soil Use and Management

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The cation exchange capacity (CEC) of soil is widely used for agricultural assessment as a measure of fertility and an indicator of structural stability; however, its measurement is time‐consuming. Although geostatistical methods have been used, a large number of samples must be collected. Using pedometric methods and incorporating easy‐to‐measure ancillary data into models have improved the efficiency of spatial prediction of soil CEC. However, mapping uncertainty has not been evaluated. In this study, we use an error budget procedure to quantify the relative contributions that model, input and covariate error make to prediction error of a digital map of CEC using gamma‐ray (γ‐ray) spectrometry and apparent electrical conductivity (ECa) data. The error budget uses empirical best linear unbiased prediction (E‐BLUP) and conditional simulation to produce numerous realizations of the data and their underlying errors. Linear mixed models (LMMs) estimated by residual maximum likelihood (REML) are used to create the prediction models. The combined error of model [5.07 cmol(+)/kg] and input error [12.88 cmol(+)/kg] is ~12.93 cmol(+)/kg, which is twice as large as the standard deviation of CEC [6.8 cmol(+)/kg]. The individual covariate errors caused by the γ‐ray [9.64 cmol(+)/kg] and EM error [8.55 cmol(+)/kg] were large. Preprocessing techniques to improve the quality of the γ‐ray data could be considered, whereas the EM error could be reduced by the use of a smaller sampling interval in particular near the edges of the study area and at pedoderm boundaries.

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“…Radiometric data were collected at a flight altitude of 60 m using a multichannel Exploranium GR 820 spectrometer (16.8 liter down, 4.2 liter up) which measures the energy range of the following five channels: Total Count (0.42-3 Mev), Potassium (1.373-1.574 Mev), Thorium (2.414-2.816), Uranium (1.660-1.860 Mev) and Cosmic Background (3.00-6.00 Mev). Thanks to a gamma spectrometer, it is possible to estimate the energy of gamma photons emitted on the Earth's surface and their activity [14].…”

Section: Gamma Spectrometrymentioning

confidence: 99%

Geostatistical Study of Airborne Geophysical Data of the Tiouit Mining Area (Eastern Anti-Atlas, Morocco)

Miftah

Azzab

Attou

et al. 2021

Proceedings of the 2nd International Electronic Conference on Mineral Science

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The main objective of the present work is to use principal component analysis (PCA) on the various airborne geophysical data, including gamma-ray spectrometry (concentrations of radioactive elements 40 K and 232 Th), magnetism (magnetization contrast due to magnetic susceptibility), and electromagnetism (apparent electrical resistivity) to describe the physicochemical behavior of the mining zones in operation as well as to prospect other zones favorable for exploration. This data's geostatistical study highlights the adequate principal component (PC) to visualize these geophysical variables. We chose PC4 to visualize the zones favorable for mining concentration because it describes the same physical and chemical characteristics represented by the Tiouit alteration zone. The collection and X-ray fluorescence analysis of 32 samples in the field yielded high grades of Arsenic (24 g/t), Copper (5.87%), Iron (19.30 %), Lead (5.70%), and Zinc (8.85%).

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Gamma-ray remote sensing of aeolian salt sources in the Murray–Darling Basin, Australia

Cited by 16 publications

References 20 publications

Monitoring and evaluating spatial variability of soil salinity in dry and wet seasons in the Werigan–Kuqa Oasis, China, using remote sensing and electromagnetic induction instruments

Monitoring and evaluating spatial variability of soil salinity in dry and wet seasons in the Werigan–Kuqa Oasis, China, using remote sensing and electromagnetic induction instruments

An error budget for digital soil mapping of cation exchange capacity using proximally sensed electromagnetic induction and remotely sensed γ‐ray spectrometer data

Geostatistical Study of Airborne Geophysical Data of the Tiouit Mining Area (Eastern Anti-Atlas, Morocco)

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