Approach and Results
MoorgrünFE Approach
Hyperspectral imagery will be used at the plot level using proximal measurements, UAV data, and satellite hyperspectral imagery (EnMap). In addition to the hyperspectral data, time series from Sentinel-1 and Sentinel-2 will also be used.
Data collected during the planned extensive field work will be used in combination with the available vegetation and soil information.
We will test the efficiency of different algorithms such as Random Forest as well as Deep Neural Networks for regression as well as process based models for the scenario based simulations.
Journal publication
Ghazaryan, G., Krupp, L., Seyfried, S., Landgraf, N., & Nendel, C. (2024). Enhancing peatland monitoring through multisource remote sensing: optical and radar data applications. International Journal of Remote Sensing, 45(18), 6372-6394.
Presentations
2024
Advances in the Assessment of Peatland Areas: Use of Optical and Radar-based Remote Sensing Data to Assess Biodiversity, Moisture Content, and Soil Organic Carbon, Lena Krupp, National Forum for Remote Sensing and Copernicus 2024, 19–21 March 2024.
Advances in the Assessment of Peatland Areas Using Optical and Radar-based Remote Sensing Data, Gohar Ghazaryan, NaturschutzDigital 2024 – Modelling in Nature Conservation, 3–6 June 2024.
Poster
2025
Multi-Source Earth Observation Data for Assessing Hydrological Dynamics in Peatlands, Lena Krupp, ESA Living Planet Symposium 2025, Vienna, Peatland Session, Tuesday.
Multi-source remote sensing for monitoring grassland on peat soils, Lena Krupp, AGIT 2025, Salzburg, 2–3 July 2025.