In many sensing applications, typically radio signals are emitted by a radar and from the bounced reflections of the obstacles, inference about the environment is made. Even though radars can be used to sense the landscapes around the user-equipment (UE) such as whether UE is in the forested region, inside buildings, etc., it is not suitable in many wireless applications as many UEs does not have radars in them. Using radar will also increase the cost and power requirements on the UEs in applications requiring sensing of the landscapes. In this paper, we provide a mechanism where basestation (BS) is able to sense the UE's landscape without the use of a radar. We propose an artificial intelligence (AI) based approach with suitable choice of the features derived from the wireless channel to infer the landscape of the UEs. Results for the proposed methods when applied to practical environments such as London city scenario yields a precision score of more than 95 percent.