ENRICHMENT OF UAV PHOTOGRAMMETRIC POINT CLOUD TO ENHANCE DSM IN A DENSE URBAN REGION

Abstract

Unmanned Arial Vehicle (UAV) have become very cost effective and time efficient technology for surveying, mapping and various other geospatial applications. UAV serves as a platform but the main dependency also lies on which type of the sensor is integrated on it. Optical photogrammetric surveys are more often conducted for generalized purposes and for its advantages. UAV photogrammetry have become very useful tool in creation of 3D city model or Digital twin model. But creating a Digital Surface Model (DSM) through photogrammetry is not that efficient when it comes to very dense urban regions. In this research, the quality of DSM, Noise in the Photogrammetric point cloud are studied, then an experimental approach is tried to enhance the DSM than that of DSM obtained from photogrammetric processing software. From the results, it is observed that the quality of DSM is enhanced in narrow streets/roads, near trees, regions between trees and buildings, regions near building and road, etc. This approach can be utilized for low-cost UAV photogrammetry for accurate 3D modelling of the narrow streets or roads are of critical importance.