Measurement Accuracy and Improvement of Thematic Information from Unmanned Aerial System Sensor Products in Cultural Heritage Applications

Author:

Kaimaris Dimitris1ORCID

Affiliation:

1. School of Spatial Planning and Development, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Abstract

In the context of producing a digital surface model (DSM) and an orthophotomosaic of a study area, a modern Unmanned Aerial System (UAS) allows us to reduce the time required both for primary data collection in the field and for data processing in the office. It features sophisticated sensors and systems, is easy to use and its products come with excellent horizontal and vertical accuracy. In this study, the UAS WingtraOne GEN II with RGB sensor (42 Mpixel), multispectral (MS) sensor (1.2 Mpixel) and built-in multi-frequency PPK GNSS antenna (for the high accuracy calculation of the coordinates of the centers of the received images) is used. The first objective is to test and compare the accuracy of the DSMs and orthophotomosaics generated from the UAS RGB sensor images when image processing is performed using only the PPK system measurements (without Ground Control Points (GCPs)), or when processing is performed using only GCPs. For this purpose, 20 GCPs and 20 Check Points (CPs) were measured in the field. The results show that the horizontal accuracy of orthophotomosaics is similar in both processing cases. The vertical accuracy is better in the case of image processing using only the GCPs, but that is subject to change, as the survey was only conducted at one location. The second objective is to perform image fusion using the images of the above two UAS sensors and to control the spectral information transferred from the MS to the fused images. The study was carried out at three archaeological sites (Northern Greece). The combined study of the correlation matrix and the ERGAS index value at each location reveals that the process of improving the spatial resolution of MS orthophotomosaics leads to suitable fused images for classification, and therefore image fusion can be performed by utilizing the images from the two sensors.

Publisher

MDPI AG

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