Mapping and 3D modelling using quadrotor drone and GIS software

Background The main obstacle for local and daily or weekly time-series mapping using very high-resolution satellite imagery is the high price and availability of data. These constraints are currently obtaining solutions in line with the development of improved UAV drone technology with a wider range...

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Bibliographic Details
Published in:Journal of big data 2021-03, Vol.8 (1), p.1-12, Article 48
Main Authors: Budiharto, Widodo, Irwansyah, Edy, Suroso, Jarot S., Chowanda, Andry, Ngarianto, Heri, Gunawan, Alexander Agung Santoso
Format: Article
Language:English
Subjects:
3D model
AgiSof
ArcMap
Big Data
Cameras
Communications Engineering
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Database Management
Drone
Drones
Geographic information systems
Image quality
Image resolution
Information Storage and Retrieval
Land cover
Mapping
Mathematical Applications in Computer Science
Networks
Photogrammetry
Satellite imagery
Situation map
Three dimensional models
Unmanned aerial vehicles
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Summary:Background The main obstacle for local and daily or weekly time-series mapping using very high-resolution satellite imagery is the high price and availability of data. These constraints are currently obtaining solutions in line with the development of improved UAV drone technology with a wider range and imaging sensors that can be used. Findings Research conducted using Inspire 2 quadcopter drones with RGB cameras, developing 3D models using photogrammetric and situation mapping uses geographic information systems. The drone used has advantages in a wider range of areas with adequate power support. The drone is also supported by a high-quality camera with dreadlocks for image stability, so it is suitable for use in mapping activities. Conclusions Using Google earth data at two separate locations as a benchmark for the accuracy of measurement of the area at three variations of flying height in taking pictures, the results obtained were 98.53% (98.68%), 95.2% (96.1%), and 94.4% (94.7%) for each altitude of 40, 80, and 100 m. The next research is to assess the results of the area for more objects from the land cover as well as for the more varied polygon area so that the reliability of the method can be used in general
ISSN:2196-1115
2196-1115
DOI:10.1186/s40537-021-00436-8