  Propagation modeling is a crucial tool for successful wireless deployments
and spectrum planning with the demand for high modeling accuracy continuing to
grow. Recognizing that detailed knowledge of the physical environment (terrain
and clutter) is essential, we propose a novel approach that uses environmental
information for predictions. Instead of relying on complex, detail-intensive
models, we explore the use of simplified scalar features involving the total
obstruction depth along the direct path from transmitter to receiver. Obstacle
depth offers a streamlined, yet surprisingly accurate, method for predicting
wireless signal propagation, providing a practical solution for efficient and
effective wireless network planning.
