Airborne LiDAR Point Cloud Processing for Archaeology. Pipeline and QGIS Toolbox

Abstract

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.

Application of Airborne LiDAR Data to the Archaeology of Agrarian Land Use: The Case Study of the Early Medieval Microregion of Bled (Slovenia)

“…This paper utilizes an existing corpus of open access archaeological database Zbiva [73,147], open access remote sensing data and environmental data (geological and soil data), as well as open-source software tools (e.g., QGIS, SAGA) to reassess existing knowledge on the early medieval archaeological landscapes, specifically on agricultural land use. While the importance of free and open-source software in science in general, e.g., [148], and in the field of airborne LiDAR data for archaeology in particular, e.g., [149], is well recognised, we believe that the importance of the increasingly abundant and easily accessible free environmental and archaeological data, e.g., [150], is too often overlooked. Hopefully, this article is a step towards recognizing the importance that this data source can have for archaeology.…”

Airborne Lidar Survey, Density-Based Clustering, and Ancient Maya Settlement in the Upper Usumacinta River Region of Mexico and Guatemala

“…The analyses presented here build on a decade of research in the neotropics and elsewhere that have demonstrated the unprecedented ability of lidar to penetrate the often-dense jungle canopy, facilitating the identification of premodern architecture and anthropogenic landscape modifications through the production of 'bare earth' digital elevation models (DEMs) e.g., [7][8][9][10][11]22]; though for alternative terminology see [23,24]. We analyzed airborne lidar data collected in June 2019 by the National Center for Airborne Laser Mapping (NCALM) using their three wavelengths (532, 1064, and 1550 nm) Titan MW LiDAR unit.…”

“…Underbrush and recent regrowth in areas that have been burned for ranching or farming reduces the ability to resolve ground surface and ancient modifications, but more problematic appears to be the broken karst terrain of the Upper Usumacinta zone [27,28]. Changes to the processing of the point cloud and the classification of ground points might improve the resulting DEM [23,24,29,30]; however, the significant variation in terrain challenges any singular processing and classification pipeline applied across the study region. The steep escarpments that top many hills and form the sides of narrow valleys scatter pulses and create shadows, reducing return signals received by the lidar.…”

“…Google Earth also played a critical function in resolving questions concerning whether some features observed in the lidar data were modern or if they predate the cur- Project researchers analyzed the DEM raster models produced by NCALM using ESRI's ArcGIS Pro 2.7 to identify anthropogenic features based on their (typically rectilinear) geometry or previous ground identification. There is no ideal visualization for all areas of the study region [23,24,[30][31][32][33]. Instead, we found moving between an array of visualizations produced with ArcGIS Pro and the Relief Visualization Toolbox (https://iaps.zrc-sazu.si/en/rvt#v (accessed on 1 March 2021))-including RRIM (red relief image map), Archaeological VAT, bonemapping, and variations on these [34][35][36][37]-aided in clarifying the geometry of features.…”

Digital Deforestation: Comparing Automated Approaches to the Production of Digital Terrain Models (DTMs) in Agisoft Metashape

“…This allows for the processing of ALS-derived point clouds to filter out "first returns", representing the canopy, leaving only "last returns", representing the ground surface [8][9][10][11][12]. One end product of such a process is a digital terrain model (DTM; also referred to as a bare-earth digital elevation model), a measure of the elevation of a ground surface that does not include vegetation or structures [13][14][15]. DTMs are critical datasets for archaeologists, useful for identification of sites and features below dense vegetation but also for performing various kinds of landscape modeling and spatial analyses in GIS [13][14][15][16][17].…”