Supervisors
Background
Temporally high-frequency observations from Copernicus Earth observation (EO) satellites allow detecting and monitoring changes on the Earth’s surface. Changes may include short-term events (e.g. deforestation, flooding) or long-term trends and transitions (e.g. climate-change-induced vegetation changes). Earth observation data cubes are state-of-the-art infrastructure backbones to easier investigate the temporal dimension at scale. It is then possible to detect changes and produce information about types of changes retrospectively using existing time series data in the archives. The “live” monitoring based on continuously updated, new data (e.g. every few days for Sentinel-2 satellite images) in existing approaches are either limited to a specific application in the EO domain (e.g., for deforestation) or developed outside the EO domain and not yet applied and used in combination with EO data / EO data cubes (e.g. Grafana for monitoring IT systems).
Expected from the master thesis is an investigation of existing
classifications of EO image time series changes and approaches to monitoring
(natural) resources using EO data. Further, a generic method should be
developed and (prototypically) implemented as a monitoring and alerting system
based on frequently updated EO data cubes. This master thesis will be embedded
into the overarching goal of building a semantic EO data cube infrastructure,
which is developed at Z_GIS (https://sen2cube.at), and access to these data cubes will be provided.
Example dashboard based on Grafana for monitoring IT resources, including options to configure alerts for increasing, decreasing, or missing values.
Suggested reading
Hermosilla, T., Wulder, M. A., White, J. C., Coops, N. C., & Hobart, G. W. (2018). Disturbance-informed annual land cover classification maps of Canada's forested ecosystems for a 29-year landsat time series. Canadian Journal of Remote Sensing, 44(1), 67-87. https://www.tandfonline.com/doi/full/10.1080/07038992.2018.1437719
Kennedy, R., et al. Bringing an ecological view of change to Landsat‐based remote sensing. Frontiers in Ecology and the Environment 12.6 (2014): 339-346. https://esajournals.onlinelibrary.wiley.com/doi/full/10.1890/130066
Augustin, H., Sudmanns, M., Tiede, D., Lang, S., & Baraldi, A. (2019). Semantic Earth observation data cubes. Data, 4(3), 102. https://www.mdpi.com/2306-5729/4/3/102
Tiede, D., Baraldi, A., Sudmanns, M., Belgiu, M., & Lang, S. (2017). Architecture and prototypical implementation of a semantic querying system for big Earth observation image bases. European journal of remote sensing, 50(1), 452-463. https://www.tandfonline.com/doi/abs/10.1080/22797254.2017.1357432
Related projects
Prerequisites/qualification
Remote sensing
Programming and databases
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