AEL have developed expertise in the processing and interpretation of polarimetric SAR and radar interferometry. Polarimetric SAR measures 4 channels of data, represented every possible combination of transmitted and received wave polarisation. In this way they gather information about the shape and material composition of the scatterer. This information is vital in Radar Sciences for the extraction of physical and structural parameters in remote sensing.
AEL have developed a set of techniques based on invariant features of the scattering matrix.As such these features do not rely on any particular choice of antenna polarisation. One of the key concepts involved in such processing is the ENTROPY of the SAR Image. This is a formal measure of the randomness of the scattering features in the scene. When the entropy is 0 we have scattering from a smooth surface or a single object while when the entropy is close to 1 we have volume scattering from vegetation.
Shown below is an example of a processed entropy image of San Francisco Bay area (raw data courtesy of NASA/JPL). We can clearly see features such as the ocean (in blue) the parklands (in red) and the urban areas (in yellow). We can use this information to provide automatic classification of radar scenes.
AEL are involved with the German Establishment, DLR and with NASA-JPL in the development of new sensors for Earth Observation Sciences. These sensors combine polarisation with interferometry to provide highly accurate maps of vegetated land surfaces.
Recently AEL have been involved in the processing of coherent polarimetric interferometric data.This data provides the flexibility to generate interferograms using arbitrary wave polarisation. AEL, in collaboration with DLR were the first to show that the quality of the interferogram can be optimised by employing a matrix filtering technique. This process has been applied to Space Shuttle Image Radar data collected for the Lake Baikal area in Siberia to generate for the first time high resolution maps of forested terrain from a single frequency space borne sensor.
Lake Baikal is the deepest freshwater lake in the world and the third largest lake in Asia. A large variety of plant and animal life is found in its clear waters. Many rivers, as well as more than 300 mountain streams, feed into the lake.
The figure below shows an example of the type of processing that can be performed. This is a 3-D map of a forest region to the south of Lake Baikal. The image was generated from 1 day repeat passdata from a single frequency sensor (L-Band) on board the Space Shuttle. The mean height of the forest shown is around 20m.
