Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters

• DOI: 10.1016/j.jag.2021.102600
• Publication Date: 2021-10-22T15:52:00Z
• Authors: Marco La Salandra; Giorgia Miniello; Stefano Nicotri; Alessandro Italiano; Giacinto Donvito; Giorgio Maggi; Pierfrancesco Del...; Domenico Capolongo
• Keywords: Physical geography; Free open-source software; ReCaS-Bari; 550; Computing clusters; Unmanned aerial vehicle; High-resolution topographic data; Unmanned aerial vehicles; 01 natural sciences; 620; GB3-5030; Photogrammetry, Geoinformation; Environmental sciences; Photogrammetry; GE1-350; Computing cluster; 0105 earth and related environmental sciences

Photogrammetry is one of the most reliable techniques to generate high-resolution topographic data and it is key to territorial mapping and change detection analysis of landforms in hydro-geomorphological high-risk areas. Specifically, the Structure from Motion (SfM) is an emerging topographic survey technique that addresses the problem of determining the 3D position of image descriptors to estimate three-dimensional structures. Thanks to the potential of SfM algorithm and the development of Unmanned Aerial Vehicles (UAVs) that allow the on-demand acquisition of high-resolution aerial images, it is possible to survey extended areas of the Earth surface and monitor active phenomena through multi-temporal surveys. However, the ability to detect remote and wide areas with a very high-resolution is countered by the need to capture large datasets which can limit the photogrammetric process, due to the need for high-performance hardware. This paper presents a photogrammetric workflow based on Free and Open-Source Software (FOSS), which is able to return different outputs and to manage a large amount of data in reasonable time, through the distribution of the most computationally expensive steps on computing clusters hosted by the ReCaS-Bari data center for scientific research. The results are given in terms of performance evaluations based on different computing configurations of the clusters and setups of the steps of the workflow. The HTC cluster test with a parallel SSH approach involved an important reduction of several hours in the processing time of thousands UAV images, especially compared to classic photogrammetric process on a single workstation with commercial software.A parallel test, aimed to validate the performance of a single sever of the new HPC cluster, involved really good results halving the processing time with respect to the HTC cluster test.