'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
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
