BEST PRACTICE FOR MAPPING PRODUCTION FROM UAV IMAGERY
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Abstract
This research defines the best practice of processing and measuring the quality of mapping data production from UAV. In this research, aerial images from the popular DJI M300, equipped with the 45megapixel ZENMUSE P1 camera, were acquired over Chulalongkorn UAV Test Field. The test field covers 1.4 square kilometers and has 14 permanent signalized ground control points. Two software suites for UAV processing: PIX4Dmapper and Agisoft Metashape are used as processing and production platforms. By practicing and researching for years, we propose “the best practice for processing and measuring quality”. A scheme of in-situ quality control for aerial triangulation with camera interior and lens distortion parameters (f, ,R1,R2,R3,T1,T2) is called “QC-1 & QC-2”, which tangibly proposed here. The assured result of the aerial triangulation will help produce reliable and precise downstream data mapping. The UAV mapping scheme processed by using Bundle Block Adjustment (BBA) with optimal number of GCPs. In the last part of research, suggestions for data production by reducing GSD of the initial products are described. The pragmatic productions will provide convenience, speedy, and efficient workflow for downstream processes in a typical engineering project.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The published articles are copyright of the Engineering Journal of Research and Development, The Engineering Institute of Thailand Under H.M. The King's Patronage (EIT).
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