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http://dx.doi.org/10.7780/kjrs.2020.36.5.3.3

Cloud Computing-Based Processing of Large Volume UAV Images Acquired in Disaster Sites  

Han, Soohee (Department of Geoinformatics Engineering, Kyungil University)
Publication Information
Korean Journal of Remote Sensing / v.36, no.5_3, 2020 , pp. 1027-1036 More about this Journal
Abstract
In this study, a cloud-based processing method using Agisoft Metashape, a commercial software, and Amazon web service, a cloud computing service, is introduced and evaluated to quickly generate high-precision 3D realistic data from large volume UAV images acquired in disaster sites. Compared with on-premises method using a local computer and cloud services provided by Agisoft and Pix4D, the processes of aerial triangulation, 3D point cloud and DSM generation, mesh and texture generation, ortho-mosaic image production recorded similar time duration. The cloud method required uploading and downloading time for large volume data, but it showed a clear advantage that in situ processing was practically possible. In both the on-premises and cloud methods, there is a difference in processing time depending on the performance of the CPU and GPU, but notso much asin a performance benchmark. However, it wasfound that a laptop computer equipped with a low-performance GPU takes too much time to apply to in situ processing.
Keywords
UAV; Disaster Monitoring; Cloud Computing;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
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