Back to Search
Start Over
Optimization of UAV-Fixed Wing for Topographic Three Dimensional (3D) Mapping in Mountain Areas.
- Source :
- EAI Computing & Communication in Emerging Regions - CCER; 2024, p1-16, 16p
- Publication Year :
- 2024
-
Abstract
- This study aims to produce a 3D terrain visualization from the Digital Terrain Model from UAV-Fixed Wing data. In this study, data acquisition was performed by utilizing a Fixed Wing UAV equipped with a Sony Alpha 6000 camera. The study area is a predominantly hilly area, with a height approximately up to 327 meters from mean sea level as part of acquisition process, the flight mission planning was rigorously designed by using the Mission Planner software. A total of six flying missions were conducted to collect the necessary aerial photo data. In addition, Aerial photo data is processed by generating photo ortho mosaics through the Structure from the Motion Photogrammetry technique. Ground Control Points (GCP) and Independent Check Points (ICP) are integrated with in the process to enhance data accuracy and precision. ICP has an essential role as a verification tool, ensuring the conformity of the geometric position of the map with the actual coordinates on the earth's surface. The results of this study are Digital Terrain Model (DTM) data which is represented in a three-dimensional topography visualization. Subsequently, Raster data from DTM can be incorporated with BIM-based software, such as Autodesk Infraworks, where it more applicable for advanced planning and design. the results of this study discover that the accuracy of horizontal and vertical positions complies with the established standards as stated by Geospatial Information Agency Regulation Number 6 in 2018, where the 1:10,000 scale map have class 1 horizontal accuracy and class 3 vertical accuracy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25937650
- Database :
- Complementary Index
- Journal :
- EAI Computing & Communication in Emerging Regions - CCER
- Publication Type :
- Academic Journal
- Accession number :
- 183258278