Abstract
Abstract. Understanding and protecting cultural heritage involves the detection and long-term documentation of archaeological remains alongside the spatio-temporal analysis of their landscape evolution. Archive aerial photography can illuminate traces of ancient features which typically appear with different brightness values from their surrounding environment, but are not always well defined. This research investigates the implementation of the Structure-from-Motion - Multi-View Stereo image matching approach with an image enhancement algorithm to derive three epochs of orthomosaics and digital surface models from visible and near infrared historic aerial photography. The enhancement algorithm uses decorrelation stretching to improve the contrast of the orthomosaics so as archaeological features are better detected. Results include 2D / 3D locations of detected archaeological traces stored into a geodatabase for further archaeological interpretation and correlation with benchmark observations. The study also discusses the merits and difficulties of the process involved. This research is based on a European-wide project, entitled “Cultural Heritage Through Time”, and the case study research was carried out as a component of the project in the UK.
Highlights
1.1 BackgroundDetection, interpretation, documentation and monitoring of archaeological features are fundamental for understanding the historic environment, as well as maintaining and protecting cultural heritage
This paper has investigated the detection and documentation of 2D/3D archaeological features from archival aerial datasets in both visible and NIR wavelengths
Tests have demonstrated that SfM-Multi-View Stereo (MVS), in conjunction with an image enhancement, pipeline can potentially reveal cultural heritage lost assets
Summary
1.1 BackgroundDetection, interpretation, documentation and monitoring of archaeological features are fundamental for understanding the historic environment, as well as maintaining and protecting cultural heritage. Archaeological features commonly survive as subsurface remains (e.g. ancient roads, ditches, ruined buildings) which can be evidenced as crop/soil marks and/or earthworks on historical photographs (Evans and Jones, 1977). Such features can be vulnerable to landscape dynamics due to natural and cultural processes such as weather and climate change, pollution, agriculture, urbanization and other human activities ranging from tourism to war. A wide range of geoinformatics technologies, including photogrammetry, remote sensing, laser scanning, Global Navigation Satellite Systems (GNSS), topographic surveys etc., are well established techniques for archaeological documentation and monitoring (Xiao et al, 2018). Recent studies have investigated the derivation of vegetation indices from multispectral imagery (Agapiou et al, 2017) and surface morphological attributes from laser scanned digital surface models (DSMs) (Toumazet et al, 2017) to automatically detect and record archaeological structures
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