Project summary

The project explores new techniques for monitoring peat bog response to climate change using unmanned aerial systems (UAV, UAS).

The aim of the research is to identify the effects of climate change, forest disturbances, and conservation practices on the environmental properties and hydrological regime of montane peat bogs by using the advanced technologies of UAV imaging, and sensor network monitoring.

The research will be focused on i) changing extent of waterlogged areas; ii) spatiotemporal variability of soil moisture distribution based on multispectral and thermal sensors; and iii) changes in qualitative properties of peatland vegetation.

Spatiotemporal modeling and classifications of changes in the distribution of soil moisture and vegetation properties will be performed using machine learning classification (Support Vector Machine, Random Forest, TensorFlow) and the CAST prediction model in R and using the Google Earth Engine tool.

The study area is located in the headwater part of the Sumava mountains (Czech Republic), where the research will benefit from the long-term research efforts and existing experimental monitoring network and research infrastructure.

This research project fits into the long-term research themes and current activities of the Hydrology research group and the HyDrone team, which provides an opportunity for collaboration with the team.

Relevant publications of the research group

LENDZIOCH, T., LANGHAMMER, J., VLČEK, L., MINAŘÍK, R., 2021. Mapping the Groundwater Level and Soil Moisture of a Montane Peat Bog Using UAV Monitoring and Machine Learning. Remote Sensing. 13(5):907.

MINAŘÍK, R., LANGHAMMER, J., LENDZIOCH, T., 2020. Automatic Tree Crown Extraction from UAS Multispectral Imagery for the Detection of Bark Beetle Disturbance in Mixed Forests. Remote Sensing. 2020, 12, 4081.

MINAŘÍK, R.; LANGHAMMER, J.; HANUŠ, J., 2019. Radiometric and Atmospheric Corrections of Multispectral µMCA Camera for UAV Spectroscopy. Remote Sensing. 2019, 11, 2428.

LENDZIOCH, T., LANGHAMMER, J., JENICEK, M.. 2019. Estimating Snow Depth and Leaf Area Index Based on UAV Digital Photogrammetry. Sensors 2019, 19(5), 1027.

LANGHAMMER, J., VACKOVÁ, T., 2018. Detection and Mapping of the Geomorphic Effects of Flooding Using UAV Photogrammetry. Pure and Applied Geophysics. 175, 9, 3233-3245.

Current research projects of the group

  • 2022-24: Hydrological and hydrochemical response of montane peat bogs to climate change (Czech Science Foundation 22-12837S, PI: Jakub Langhammer)
  • 2020-26: Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia.(TACR SS02030040, PI: Radim Tolasz, CHMI)
  • 2019-21: Spatial and temporal dynamics of hydrometeorological extremes in montane areas. (Czech Science Foundation GAČR 19-05011S, PI: Jakub Langhammer)
  • 2018-20 Monitoring of peat bog habitats using UAV-based multispectral digital photogrammetry (GAUK78318, PI: Theodora Lendzioch)
  • 2019-21: UAS monitoring of river systems response to forest disturbance. (EU COST Action CA16219, LTC 19024, PI: Jakub Langhammer)
  • 2018-19: UAV monitoring of the dynamics of the spread of bark beetle in Prague´s forests. (Prague Environment grants MHMP DOT/54/12/ 013649/2018, PI: Jakub Langhammer)
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