Journal
REMOTE SENSING
Volume 13, Issue 16, Pages -Publisher
MDPI
DOI: 10.3390/rs13163225
Keywords
airborne LiDAR; airborne laser scanning; ALS; archaeology; point cloud processing; toolbox; open source; QGIS
Categories
Funding
- Austrian Science Fund (FWF) [I 3992]
- Slovenian Research Agency (ARRS) [N6-0132, P6-0064]
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This research aims to create a processing pipeline for archaeology-specific point cloud processing, optimizing the classification and interpolation of LiDAR data, reducing manual workload, and improving the overall efficiency of data processing in the field of archaeology.
The use of topographic airborne LiDAR data has become an essential part of archaeological prospection. However, as a step towards theoretically aware, impactful, and reproducible research, a more rigorous and transparent method of data processing is required. To this end, we set out to create a processing pipeline for archaeology-specific point cloud processing and derivation of products that are optimized for general-purpose data. The proposed pipeline improves on ground and building point cloud classification. The main area of innovation in the proposed pipeline is raster grid interpolation. We have improved the state-of-the-art by introducing a hybrid interpolation technique that combines inverse distance weighting with a triangulated irregular network with linear interpolation. State-of-the-art solutions for enhanced visualizations are included and essential metadata and paradata are also generated. In addition, we have introduced a QGIS plug-in that implements the pipeline as a one-step process. It reduces the manual workload by 75 to 90 percent and requires no special skills other than a general familiarity with the QGIS environment. It is intended that the pipeline and tool will contribute to the white-boxing of archaeology-specific airborne LiDAR data processing. In discussion, the role of data processing in the knowledge production process is explored.
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