Automated Feature Extraction (AFE) plays a critical role in image understanding. Often the imagery analysts extract
features better than AFE algorithms do, because analysts use additional information. The extraction and processing of
this information can be more complex than the original AFE task, and that leads to the “complexity trap”. This can
happen when the shadow from the buildings guides the extraction of buildings and roads. This work proposes an AFE
algorithm to extract roads and trails by using the GMTI/GPS tracking information and older inaccurate maps of roads
and trails as AFE guides.