by Walter G. Kropatsch
Abstract:
General principles for integrating data from different sources are derived from the experience of registration of SAR images with DEM data. The integration in our case consists of establishing geometrical relations between the data sets that allow to accumulate information from both data sets for any given object point (e.g. elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor charateristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.
Reference:
Integration of SAR and DEM Data - Geometrical Considerations (Walter G. Kropatsch), Technical report, PRIP, TU Wien, 1992.
Bibtex Entry:
@TechReport{TR003,
author = "Walter G. Kropatsch",
institution = "PRIP, TU Wien",
number = "PRIP-TR-003",
title = "Integration of {SAR} and {DEM} Data - {G}eometrical
{C}onsiderations",
year = "1992",
url = "https://www.prip.tuwien.ac.at/pripfiles/trs/tr3.pdf",
abstract = "General principles for integrating data from
different sources are derived from the experience of
registration of SAR images with DEM data. The
integration in our case consists of establishing
geometrical relations between the data sets that
allow to accumulate information from both data sets
for any given object point (e.g. elevation, slope,
backscatter of ground cover, etc.). Since the
geometries of the two data are completely different
they cannot be compared on a pixel by pixel
basis. The presented approach detects instances of
higher level features in both data sets
independently and performs the matching at the high
level. Besides the efficiency of this general
strategy it further allows the integration of
additional knowledge sources: world knowledge and
sensor charateristics are also useful sources of
information. The SAR features layover and shadow can
be detected easily in SAR images. An analytical
method to find such regions also in a DEM needs in
addition the parameters of the flight path of the
SAR sensor and the range projection model. The
generation of the SAR layover and shadow maps is
summarized and new extensions to this method are
proposed.",
}