Research project PeatSens
Peatland methane emissions measurement approach through remote sensing
Project name Data-based extrapolation model for determining real operating load trains for (residual) service life analysis of railroad INFRA structural systems
Acronym CPC lightweight constructions
Project partner
Grantor BMBFon
Duration 01.02.2024 – 31.01.2027

Research field
 E+E
(E+E > Energy + Environment
I+I > Information + Intelligence
M+M > Matter + Materials)
Project content The PeatSens project is part of the Integrated Greenhouse Gas Monitoring System for Germany (ITMS) and aims to simplify the estimation of methane emissions from rewetted peatlands through the use of remote sensing data. Together with the Landscape Ecology group at the University of Rostock, our department is working on collecting data directly from the peatland sites and estimating relevant ecological parameters using satellites and drones.
Methane emissions are measured directly in the peatland using chambers. The chambers are permanently installed on the ground so that the concentrations of the gases can be measured very accurately. These measurements are time-consuming and labour-intensive but are the most accurate method for researching the factors that determine emissions in rewetted peatlands. Previous research by the Landscape Ecology and Site Evaluation group has already established that the groundwater level and the composition of the vegetation have a decisive influence on the level of methane emissions from the peatland soil.
The project will use remote sensing data to investigate the extent to which methane emissions from peatland soils can be indirectly estimated. Indicators such as soil water content and water levels, vegetation and soil movement will be determined using radar, multi- and hyperspectral satellite data and hyperspectral drone data. These parameters will be validated using in situ measurements in the peatland in parallel with the gas measurements.
Groundwater levels and soil moisture are to be derived from synthetic aperture radar (SAR) data. Radar signals can penetrate the typical peatland vegetation of grasses and mosses and their return radiation can provide information about the moisture of the soil. The phase information of the radar signal is also to be used to derive soil movements. In a near-natural peatland, a seasonal oscillation of the peat body is expected, which swells in the water-rich winter months and shrinks in the hot and dry summer months. If the peatland is heavily drained, no movement or only shrinkage, but stronger emission is expected. Hyperspectral measurements offer the potential to distinguish vegetation classes from each other by means of special spectral signatures. Spectral signatures are like a fingerprint of light reflection. As hyperspectral sensors record the reflections in up to 225 different channels, these data are suitable for differentiating surface cover from one another. The vegetation composition serves as an indicator of the condition of the peatland, which correlates with the emission behaviour. In the next step, these data will be used as new input parameters for a peatland model based on remote sensing data. The methane emissions estimated from this model will be compared with the methane emissions measured using the chambers to improve and evaluate the model.