Fusion of SAR/INSAR data and optical imagery for landuse classification

SAR/INSAR data and optical imagery such as high-resolution panchromatic or multispectral data show different information about the imaged objects, and have different advantages and disadvantages when used for object extractio n or landuse classification, Multispectral optical image data is largely de termined by the type of the material an object consists of, Panchromatic da ta which is often available with a higher resolution than multispectral dat a emphasizes geometric detail of the objects, e,g. the complex structure of anthropogenic objects such as road networks. In contrary to this, SAR data contain information about small-scale surface roughness and - to a lower d egree - soil moisture. Height information derived by interferometric proces sing of SAR data contains large-scale surface roughness. Polarimetric SAR d ata show geometric surface and material structure. These different types of information are referring to different object qualities and are, therefore , largely uncorrelated which helps to reduce ambiguities in the results of object extraction. The main advantage oi passive optical imagery with respe ct to SAR data is the lack of the speckle effect leading to images with a f ar better extractability of linear as well as areal objects when systems wi th the same resolution are compared. A major advantage of SAR is its all-we ather capability which allows the acquisition of time series of imagery wit h exact acquisition dales under any climatic condition, In this paper, thes e complementary properties of SAR and optical image data are demonstrated a nd used to improve object extraction and landuse classification results.