Automated Author ProfileTack, Frederik
Tack, Frederik
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.3 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The construction of multi-temporal data sets for the modelling and documentation of urban environments has gained a large interest in the last few years. The growing availability of remote sensing data and sophisticated software tools has enabled the construction of Digital Elevation Models (DEMs) with various spatial and temporal resolutions. For this research, multiple scanned airborne images of the inner city of Ghent (Belgium) were processed for the calculation of DEMs using a conventional digital photogrammetric workflow. The aerial images were acquired during four campaigns: 1965, 1977, 1987 and 1990. All resulting image-based DEMs were compared with a DEM acquired with Airborne Laser Scanning (ALS) from 2009. This comparison allowed a model adjustment by minimizing the systematic shift between the data sets. In order to distinct built-up, destroyed or unchanged buildings over time, a threshold of 2.5 m was applied on the resulting vertically shifted points. Finally, a connected component analysis allowed the removal of outliers in the data. The resulting points were evaluated against a 2D digital cadastre map, which enabled a quantitative determination of difference in urban topography. The procedure to detect these changes, as well as the potentials and challenges of this technique, are discussed in this contribution.
Authors
- Stal, Cornelis ;
- De Wulf, Alain ;
- De Maeyer, Philippe ;
- Goossens, Rudi ;
- Nuttens, Timothy ;
- Tack, Frederik ;
- Hendrickx, Marijn