MMS or mobile mapping systems is an integrated system consisting of various sensors such as Cameras, LIDAR, IMU and GPS modules fitted on the top of a mobile platform (usually a car) and is used to get accurate situational awareness of the environment around the vehicle. It acquires 3D information of road surfaces, signage, guard rails, lettering on road surfaces, manholes, and buildings surrounding the road while the vehicle is travelling. It also makes 3D GIS (Geographic Information Science) map data and subsequently makes vehicle motion model simulation so as to achieve safe driving and generation of maps for development purposes. But in the case of a UAV, the process of getting the sensor information becomes complex as pitch, roll and yaw motion of the drone are involved (unlike a car). So, in order to accurately understand, interpret and visualise the data, we perform calibration (Bore sight, Level arm and Time delay) of all the sensors present on board. This helps to reduce the biases present in the data to a minimum and helps to get accurate information about the environment. In this paper, we have presented Level arm calibration and a novel technique for Bore sight calibration of sensors on-board a UAV. We have also shown the difference in estimated and ground truth trajectory which arises due to improper calibration. © 2020 IEEE.