Unmanned Aerial Systems for Building Footprint Extraction in Urban Area

Abstract

The use of Unmanned Aerial Systems (UAS) in remote sensing applications, specifically using the Trimble UX5 HP platform for aerial data collection over Karakol city in Kyrgyzstan. Photogrammetric technique used to identify and match common features in the overlapping aerial images to create a sparse point cloud, which were further processed to create a Digital Surface Model (DSM). A slope-based filtering algorithm was applied to the DSM data for generating a Digital Terrain Model (DTM). The normalized Digital Surface Model (nDSM) was derived from the DSM by subtracting the DTM. Object-based image analysis applied to UAS datasets for the extraction of building footprints in an urban area. The results indicate that extracted building footprints have been generated accurately with an overall completeness of 92.4% and correctness of 95,2%.