SAR is a remote sensing technique capable to deliver actual data at any time and under bad weather conditions. Before
launch of TerraSAR-X, RADARSAT-2, or COSMO-SkyMed, the rather coarse resolution of operational SAR satellite
systems allowed an analysis of spaceborne SAR data in case of disaster management only for medium scale products.
The new generation of spaceborne SAR satellites permits a more detailed analysis at the object level even for urban
areas, which was before restricted to airborne SAR sensors. Change detection in SAR images is an important field of
research. In general, the appearance of objects in SAR images strongly depends on the viewing angle and look direction.
This makes a comparison of images on a pixel level difficult. The changeover from pixel- to object level leads to the
possibility, to look for object-features that are more stable concerning different imaging constellations. Bridges are keyelements
of man made infrastructure. In this paper the appearance of bridges in SAR data is analyzed and features are
derived that are exploitable for change detection. Here the focus is on analysis at the object level to derive features that
are either stable concerning the imaging constellations or that can be predicted based on a given imaging constellation.
Thereby, the usage of different sensors will be possible to achieve the goal of real time information. The investigations
are supported by simulations, which allow the creation of SAR images for different imaging constellations, bridge
materials, and even for situations with destroyed bridges.
Ship traffic monitoring may be performed using satellite SAR data. The advantage with the SAR sensor is the all
weather and day/night imaging capability. However, the SAR backscatter contrast between a vessel and the
surrounding sea state may be small in high wind conditions and at small incidence angles. The present and future
SAR satellites will have the capability of imaging the earth surface with several incidence angles, and with dual-polarimetry
(HH/HV, VV/VH or HH/VV). The SAR ship/clutter contrast may threrefore be increased by applying
different polarisation combinations, or using higher incidence angles.
We have shown that geocoded ENVISAT ASAR images in the coastal region of Norway can be used to gain
experience in the combined use of satellite SAR and an automatic identification system (AIS) for ship traffic
monitoring.
There are plans for placing AIS systems onboard satellites. It will then be possible to fuse the information from
satellite SAR with those from satellite (or ground-based coastal) AIS and thereby identify all the detected ships
within a SAR image. This data fusion will enable us to develop further knowledge about SAR backscatter properties
from vessel types that may not be detected so well using the SAR data only. On the other side, it will be possible to
pin-point those ship candidates that do not carry an AIS system, and thereby take appropriate security or rescue
actions.
Operational SAR satellite systems such as ENVISAT-ASAR and RADARSAT-1 deliver image data of a rather coarse
resolution, which allows the recognition or feature extraction only for large man-made objects. State of the art airborne
SAR sensors on the other hand provide spatial resolution in the order well below a half meter. In such data many features
of urban objects can be identified and used for recognition. Core elements of man-made infrastructure are bridges. In
case of bridges over water, the oblique side looking imaging geometry of SAR sensors may lead to special signature in a
SAR image depending on the aspect. In this paper, the appearance of bridges over water in SAR data is discussed.
Geometric constraints concerning the changing of this signature are investigated using simulation techniques based on an
adapted ray tracing. Furthermore, an approach is presented to detect bridges over water and to derive object features
from spaceborne and airborne SAR images in the context of disaster management. RADARSAT-1 data with a spatial
resolution of about 9 m as well as high-resolution airborne SAR data of geometric sampling distance better than 40 cm
are investigated.
Strong point backscatter can be observed in ERS-1 satellite SAR images taken over urban areas. Several of these point backscatter come from metal surfaces and roofs. An experiment using a continuous wave (cw) radar has been carried out in order to model the radar backscatter from tarred board roofs and corrugated iron surfaces. Test objects are illuminated by the cw-radar using the ERS-1 SAR frequency, but with several polarizations and incidence angles. Specular reflection and Bragg resonance effects are studied in particular. Radar simulations are used to confirm the experimental results. The final results show that both metal and tarred board roofs can give strong radar backscatter. Both first and second order Bragg resonance peaks occurred at the theoretical incidence angles when illuminating corrugated iron plates with the radar. Comparisons are also made to real data by investigating point target backscatter seen in a multitemporal ERS-1 SAR image data set. Further investigations could be carried out when RADARSAT images acquired at different incidence angles are available.
Tromso Satellite Station (TSS) is the Norwegian national receiving station for ERS-1 SAR data. The TSS Fast Delivery (FD) SAR processor was upgraded during spring 1994 so that the whole processing chain will now be performed in power rather than in voltage. This new FD SAR product from TSS needs absolute calibration, and a calibration constant is therefore estimated. First, a TSS Power-processed ERS-1 SAR image was used. This image covers the ESA transponders in Flevoland. The integration method was used to estimate the backscattered power from the 3 transponders. The Earth ellipsoid, local incidence angle, antenna pattern, range-spread loss, pixel size and RCS were also taken into account in the calculation. The result was a calibration constant of 53.51 dB. An other method is to compare the backscatter from an ESA processed PRI product and a TSS Power-processed FD product acquired at the same place and time. Areas were extracted from two such SAR images, and the pixel values averaged in power. The known calibration constant for the PRI product was used in the comparison of the image products. The calibration constant for the TSS FD product was then found to be 54.20 dB. This is close to the result from using the ESA transponders.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.