Mountain Green Cover Index in Sen2Cube.at

 Suggested by: Dirk Tiede, Martin Sudmanns

Background

Mountains are one of the most affected regions by climate change, directly affecting the mountain’s ecosystem roles and health. The mountain community understands the direct correlation between the vegetation (“green”) coverage of the mountain area and the ecosystem health and status; Therefore, the Mountain Green Cover Index (MGCI) was developed to measure changes in green vegetation in mountain areas to provides an indicator of their environment. This index contributes to the target 15.4 of the sustainable development goals (SDG) 15: “By 2030, ensure the conservation of mountain ecosystems, including their biodiversity, to enhance their capacity to provide benefits that are essential for sustainable development”.

The Sen2Cube.at system (www.sen2cube.at) is an application-agnostic semantic EO data cube that contains Sentinel-2 images and derived information layers since the satellite’s launch in 2015. An EO data cube organizes Earth observations in a spatio-temporal data model that allows simplified access to the data based on (geographic) coordinate values instead of files and directories, thus enabling big EO data analytics. The definition of a semantic EO data cube is “A semantic EO data cube or a semantics-enabled EO data cube is a data cube, where for each observation at least one nominal (i.e., categorical) interpretation is available and can be queried in the same instance.“ The Sen2Cube.at system contains a semantic EO data cube for Austria and is developed by Z_GIS.

The master thesis will investigate the feasibility of calculating the remote-sensing-based Mountain Green Cover Index (MGCI) using the Sen2Cube.at system and upscale it spatially for Austria and temporally for several years. Thus, the output should be Austria-wide information layers of the MGCI of several years.

Suggested reading

Mountain Green Cover Index (SDG Indicator 15.4.2) – Metadata and methodological information: http://www.fao.org/fileadmin/templates/mountain_partnership/MGCI_for_validation/Methodological_notes/Methodological_note___metadata_-__Mountain_Green_Cover_Index.pdf

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

Start

Anytime

Prerequisites/qualification

Remote Sensing

Programming and databases

Interest in the topic, mountains, and rejecting flat-earth theories +

Interest to work in a cross-domain setting (remote sensing, SDG, visualization, GIS)