In this paper, the authors describe a Python customized code based on Agisoft MetaShape processing engine that permits the automatic solution of a complete photogrammetric process from acquisition of the image block by Unmanned Aerial Vehicle (UAV) to final results: Dense Digital Surface Model (DDSM), Digital Terrain Model (DTM) and orthophoto. Inspired by the old approach on analytical stereo-plotter, the proposed solution is based on a partition of the aerial block in a series of strips that can be transmitted by drones to the processing units during the flight to obtain a “quasi-real-time” solution in a just few minutes at the end of the flight. The Python code can automatically add images from remote folders creating new Metashape Chunks at the end of each strip; align images of each strip in few seconds using the approximate external parameters of images acquired by drone navigation sensors; recognize coded (and not) markers (GCPs) and make a bundle block solution of each strip; align different chunks in a unique photogrammetric block; solve the final photogrammetric block using camera pose optimization of Metashape with an automatic selection of CPs from the recognized markers; compile and show a report that permits the resulting diagnostic by a skilled user. The proposed solution has been applied to a precision agriculture environment for automatically surveying a vineyard and recognize the rows and the ground areas for automatic path planning purposes.

A Python Customization of Metashape for Quasi Real-Time Photogrammetry in Precision Agriculture Application / Aicardi, Irene; Angeli, Stefano; Milazzo, Rosario; Lingua, Andrea Maria; Angela Musci, Maria (COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE). - In: R3 in Geomatics: Research, Results and ReviewELETTRONICO. - [s.l] : Springer, 2020. - ISBN 978-3-030-62799-7. - pp. 229-243 [10.1007/978-3-030-62800-0_18]

A Python Customization of Metashape for Quasi Real-Time Photogrammetry in Precision Agriculture Application

Rosario Milazzo;Andrea Maria Lingua;
2020

Abstract

In this paper, the authors describe a Python customized code based on Agisoft MetaShape processing engine that permits the automatic solution of a complete photogrammetric process from acquisition of the image block by Unmanned Aerial Vehicle (UAV) to final results: Dense Digital Surface Model (DDSM), Digital Terrain Model (DTM) and orthophoto. Inspired by the old approach on analytical stereo-plotter, the proposed solution is based on a partition of the aerial block in a series of strips that can be transmitted by drones to the processing units during the flight to obtain a “quasi-real-time” solution in a just few minutes at the end of the flight. The Python code can automatically add images from remote folders creating new Metashape Chunks at the end of each strip; align images of each strip in few seconds using the approximate external parameters of images acquired by drone navigation sensors; recognize coded (and not) markers (GCPs) and make a bundle block solution of each strip; align different chunks in a unique photogrammetric block; solve the final photogrammetric block using camera pose optimization of Metashape with an automatic selection of CPs from the recognized markers; compile and show a report that permits the resulting diagnostic by a skilled user. The proposed solution has been applied to a precision agriculture environment for automatically surveying a vineyard and recognize the rows and the ground areas for automatic path planning purposes.
2020
978-3-030-62799-7
978-3-030-62800-0
R3 in Geomatics: Research, Results and Review
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2972396