Data acquired remotely are affected by several factors such as sensor characteristics, illumination, geometric alignments, and atmospheric conditions. In order to obtain temporally and spatially consistent field results, data must go through a standard preprocessing pipeline. Throughout preprocessing, raw data (that are mainly in the form of Digital Numbers (DN)) need to be converted to meaningful values and attributed to their real-world correspondents such as reflectance or temperature. Radiometric calibration, converting raw data to physical units, and removing noise caused by external effects form the first step of preprocessing. In the stitching step, images of different locations on the ground are laid and stitched together to generate an orthomosaic of the whole study area. Alignment of all the data and staking them so that a specific position contains data from all the sensors, spatially and temporally, creates the georeferencing step.

6.1.1. Radiometric Calibration

6.1.2. Georeferencing

6.1.3. Mosaicing

6.1.4. Point cloud and Digital Surface Models