We built a SLAM pipeline that is able to utilize visual odometry and key point matching for loop closure to create city scale maps. Our pipeline does not depend no IMU or GPS sensors. We utilize equirectangular images to obtain a full 360 perspective and track key points between video frames that have high amounts of distortion. We are able to reconstruct a sparse point cloud with geometric accuracy sufficient to track movement across multiple city blocks. This is further enhanced with loop closure.