Airborne Electromagnetic and Radiometric Peat Thickness Mapping of a Bog in Northwest Germany (Ahlen-Falkenberger Moor)

Abstract

Knowledge on peat volumes is essential to estimate carbon stocks accurately and to facilitate appropriate peatland management. This study used airborne electromagnetic and radiometric data to estimate the volume of a bog. Airborne methods provide an alternative to ground-based methods, which are labor intensive and unfeasible to capture large-scale (>10 km2) spatial information. An airborne geophysical survey conducted in 2004 covered large parts of the Ahlen-Falkenberger Moor, an Atlantic peat bog (39 km2) close to the German North Sea coast. The lateral extent of the bog was derived from low radiometric and elevated surface data. The vertical extent resulted from smooth resistivity models derived from 1D inversion of airborne electromagnetic data, in combination with a steepest gradient approach, which indicated the base of the less resistive peat. Relative peat thicknesses were also derived from decreasing radiation over peatlands. The scaling factor (µa = 0.28 m−1) required to transform the exposure rates (negative log-values) to thicknesses was calculated using the electromagnetic results as reference. The mean difference of combined airborne results and peat thicknesses of about 100 boreholes is very small (0.0 ± 1.1 m). Although locally some (5%) deviations (>2 m) from the borehole results do occur, the approach presented here enables fast peat volume mapping of large areas without an imperative necessity of borehole data.

Mapping of Peat Thickness Using a Multi-Receiver Electromagnetic Induction Instrument

“…Remote sensing and airborne geophysical techniques represent the most suitable means to investigate peatlands at a large scale (>10 km 2 ). Several recent studies have successfully used airborne electromagnetic (AEM) methods to estimate peatland thickness and extent [14][15][16][17]. Likewise, different proximal or ground-based geophysical sensors have been accurately applied to map peat properties at smaller scales.…”

Mapping the maximum peat thickness of cultivated organic soils in the southwest plain of Montreal

“…Many combinations of covariates are commonly used in regression and classification mapping of peatlands and could be investigated as potential candidates for predicting the thickness of the coprogenous layer. Peat thickness and its extent are often evaluated by combining a digital elevation model (DEM) and its derivatives, airborne gamma radiometric data, electromagnetic data, and satellite data (Gatis et al, 2019;Minasny et al, 2019;Rudiyanto et al, 2018;Siemon et al, 2020). Most of the covariates are the product of remote sensing techniques, while ground penetrating radar, gamma radiometric 5 data and soil electrical resistivity or conductivity can be obtained with proximal sensing techniques (Beucher et al, 2020;Comas et al, 2015;Parry et al, 2014;Rosa et al 2009).…”

1D Stochastic Inversion of Airborne Time-Domain Electromagnetic Data with Realistic Prior and Accounting for the Forward Modeling Error

“…In the last decades, technological advancements made it possible to move from the simple mineral target detection to more detailed groundwater mapping [21,22] and geological modeling applications [23,24].…”