Abstract High local groundwater flow into rock tunnels through the fracture zones is an important factor influencing excavation time and costs. Therefore, detection of geological features for prediction of high local groundwater flow is essential before excavation of tunnels. Observations during excavation suggest that open fractures in the limestone layers of Li3 unit are the main reason for the high water inflow. The limestone thick layers outcrop in form of cliffs constituting the upper parts of the cuesta. Moreover, Li3 unit as a recharge source of the springs has the highest potential for groundwater inflow throughout the tunnel. To reduce the costs and time of field works, remote sensing investigations can be a good solution. The main aim of this study is to present a methodology for digital processing of ASTER satellite imagery data to detect mall-scale fractures of cuesta-forming limestone layers. Experimental results provided for the Long Zagros tunnel show that, fractures in direction of cliff limestone unites can be detected using colour and textural characteristics of the ASTER image. Results also show that, Li3 unite can be detected on the image based on lack of small scale folding, have a vertical outcrop, interruption in edge direction and without clay cover
