Mapping upland peat depth using airborne radiometric and lidar survey data

Gatis, Naomi; Luscombe, David J.; Carless, Donna; Parry, Lauren; Fyfe, Ralph; Harrod, T. R.; Brazier, Richard E.; Anderson, Karen

doi:10.1016/j.geoderma.2018.07.041

Cited by 34 publications

(42 citation statements)

References 39 publications

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“…The site lies at 515 m above sea level and is classified as National Vegetation Classification class M17 Scirpus cespitosus-Eriophorum vaginatum blanket mire (Rodwell 1991). Peat at the study site is estimated to be between 3.6 and 4.0 m thick (Gatis et al 2019) above the average for Dartmoor (0.81 m) (Parry et al 2012). The study site is within an extensive area of erosional peat pans and vegetated haggs ( Fig.…”

Section: Study Sitementioning

confidence: 96%

“…The deep peats of Dartmoor store an estimated 13.1 Mt of carbon (Gatis et al 2019) but are vulnerable to climate change as they lie at the southern limit of the UK blanket bog climatic envelope (Clark et al 2010). This makes them invaluable as indicators of the potential effects of climate change on other, more northerly, maritime peatlands.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the impact of peat erosion on growing season CO2 fluxes by comparing erosional peat pans and surrounding vegetated haggs

Gatis

Benaud

Ashe

et al. 2019

Wetlands Ecol Manage

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Peatlands are recognised as an important but vulnerable ecological resource. Understanding the effects of existing damage, in this case erosion, enables more informed land management decisions to be made. Over the growing seasons of 2013 and 2014 photosynthesis and ecosystem respiration were measured using closed chamber techniques within vegetated haggs and erosional peat pans in Dartmoor National Park, southwest England. Below-ground total and heterotrophic respiration were measured and autotrophic respiration estimated from the vegetated haggs. The mean water table was significantly higher in the peat pans than in the vegetated haggs; because of this, and the switching from submerged to dry peat, there were differences in vegetation composition, photosynthesis and ecosystem respiration. In the peat pans photosynthetic CO 2 uptake and ecosystem respiration were greater than in the vegetated haggs and strongly dependent on the depth to water table (r 2 [ 0.78, p \ 0.001). Whilst in the vegetated haggs, photosynthesis and ecosystem respiration had the strongest relationships with normalised difference vegetation index (NDVI) (r 2 = 0.82, p \ 0.001) and soil temperature at 15 cm depth (r 2 = 0.77, p = 0.001). Autotrophic and total below-ground respiration in the vegetated haggs varied with soil temperature; heterotrophic respiration increased as water tables fell. An empirically derived net ecosystem model estimated that over the two growing seasons both the vegetated haggs (29 and 20 gC m -2 ; 95% confidence intervals of -570 to 762 and -873 to 1105 gC m -2 ) and the peat pans Wetlands Ecol Manage (2019) 27:187-205 https://doi.org/10.1007/s11273-019-09652-9( 0123456789().,-volV) ( 01234567 89().,-volV) (7 and 8 gC m -2 ; 95% confidence intervals of -147 to 465 and -136 to 436 gC m -2 ) were most likely net CO 2 sources. This study suggests that not only the visibly degraded bare peat pans but also the surrounding vegetated haggs are losing carbon to the atmosphere, particularly during warmer and drier conditions, highlighting a need for ecohydrological restoration.

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Section: Study Sitementioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Assessing the impact of peat erosion on growing season CO2 fluxes by comparing erosional peat pans and surrounding vegetated haggs

Gatis

Benaud

Ashe

et al. 2019

Wetlands Ecol Manage

View full text Add to dashboard Cite

show abstract

“…The peat depth model is essential for determining the conservation areas [11,51], and for defining the suitable type and location of canal blockings [52]. The peat depth model is also needed as a basis of evaluation of the carbon stock and the condition the soil organic carbon (SOC) (see e.g., [23,26,53,54]) and is required in the evaluation of peatland ecosystem [55,56], and peatland burn [57,58].…”

Section: Discussionmentioning

confidence: 99%

“…These covariates are organism activities, topographic conditions, spatially relative positions [18,20], land cover, and geological aspects [25]. Topographic covariates consist of slope, aspect, curvature, flow accumulation, wetness index, stream power index, landform classification, vegetation index, and soil map [26][27][28]. Peatland visual conditions also have a specific correlation to the existing peat depth, i.e., length and slope condition, land cover, vegetation, and the groundwater surface [14,29,30].…”

Section: Introductionmentioning

confidence: 99%

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

2020

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High-accuracy peat maps are essential for peatland restoration management, but costly, labor-intensive, and require an extensive amount of peat drilling data. This study offers a new method to create an accurate peat depth map while reducing field drilling data up to 75%. Ordinary least square (OLS) adjustments were used to estimate the elevation of the mineral soil surface based on the surrounding soil parameters. Orthophoto and Digital Terrain Models (DTMs) from LiDAR data of Tebing Tinggi Island, Riau, were used to determine morphology, topography, and spatial position parameters to define the DTM and its coefficients. Peat depth prediction models involving 100%, 50%, and 25% of the field points were developed using the OLS computations, and compared against the field survey data. Raster operations in a GIS were used in processing the DTM, to produce peat depth estimations. The results show that the soil map produced from OLS provided peat depth estimations with no significant difference from the field depth data at a mean absolute error of ±1 meter. The use of LiDAR data and the OLS method provides a cost-effective methodology for estimating peat depth and mapping for the purpose of supporting peat restoration.

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“…T CO 2 -C-equivalents) of the total national greenhouse budget of 2006 came from peatlands and horticultural peat extraction and use [1]. Knowledge on peat volumes of peatlands (both peat bogs and fens) is essential to estimate carbon stocks accurately and to facilitate appropriate peatland management [2], as well as to support nature conservation policies.…”

Section: Introductionmentioning

confidence: 99%

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

2020

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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.

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Mapping upland peat depth using airborne radiometric and lidar survey data

Cited by 34 publications

References 39 publications

Assessing the impact of peat erosion on growing season CO2 fluxes by comparing erosional peat pans and surrounding vegetated haggs

Assessing the impact of peat erosion on growing season CO2 fluxes by comparing erosional peat pans and surrounding vegetated haggs

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

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

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