Name
Title | ||
|---|---|---|
Automatic Training Set Compilation With Multisource Geodata for DTM Generation From the TanDEM-X DSM |
Abstract | ||
|---|---|---|
The TanDEM-X mission (TDM) is a spaceborne radar interferometer which delivers a global digital surface model (DSM) with a spatial resolution of 0.4 arcsec. In this letter, we propose an automatic workflow for digital terrain model (DTM) generation from TDM DSM data through additional consideration of Sentinel-2 imagery and open-source geospatial vector data. The method includes the automatic and robust compilation of training samples by imposing dedicated criteria on the multisource geodata for subsequent learning of a classification model. The model is capable of supporting the accurate distinction of elevated objects (OBJ) and bare earth (BE) measurements in the TDM DSM. Finally, a DTM is interpolated from identified BE measurements. Experimental results obtained from a test site which covers a complex and heterogeneous built environment of Santiago de Chile, Chile, underline the usefulness of the proposed workflow, since it allows for substantially increased accuracies compared to a morphological filter-based method. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LGRS.2019.2921600 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Training,Time division multiplexing,Roads,Data models,Geospatial analysis,Earth,Spatial resolution | Geospatial analysis,Training set,Data mining,Interpolation,Remote sensing,Interferometry,Digital elevation model,Test site,Image resolution,Workflow,Mathematics | Journal |
Volume | Issue | ISSN |
17 | 3 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| christian geiss | 1 | 28 | 5.59 |
| Patrick Aravena Pelizari | 2 | 2 | 1.85 |
| Stefan Bauer | 3 | 0 | 0.34 |
| Andreas Schmitt | 4 | 57 | 7.20 |
| Hannes Taubenböck | 5 | 150 | 28.27 |