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PhD Project:

Monitoring biodiversity of agroforestry systems, using multisensor Earth-Observation data and deep learning

The main objective of the PhD-project is the development of suitable methods for monitoring and assessing biodiversity in agroforestry systems (AFS), e.g., by mapping woody landscape elements and their interaction with neighboring cropland. The project aims on the synergies of various satellite data (e.g. multispectral and SAR with different spatial resolutions) and a potential integration of UAV data. The methods will base on state-of-the-art developments in the field of data analysis and can foster the general use of advanced methods for large remote sensing data sets. These findings can support monitoring compliances, e.g., in context of the EU common agricultural policy, adapting agriculture to climate change and programs regarding the conservation of biodiversity, and the UN Sustainable Development Goals. Furthermore, the results serve as a basis for further investigations on the effect of AFS on yields, carbon storage, and resilience of climate change adopted cropping systems at the landscape scale.

Project team: Moritz Lucas (Ph.D. Student), Prof. Dr. Björn Waske (UOS), Dr.-Ing. Ralf Pecenka (ATB)

GIL Tagung 2024

Find the digital version of the conference poster here: GIL 2024 POSTER

Publications

M. Lucas, A. Dasgupta and B. Waske, "Analyzing Gradual Vegetation Changes in the Athabasca Oil Sands Region Using Landsat Data," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 1365-1377, 2023, doi: 10.1109/JSTARS.2023.3234090