Documentation of Archaeology-Specific Workflow for Airborne LiDAR Data Processing

Abstract

Airborne LiDAR is a widely accepted tool for archaeological prospection. Over the last decade an archaeology-specific data processing workflow has been evolving, ranging from raw data acquisition and processing, point cloud processing and product derivation to archaeological interpretation, dissemination and archiving. Currently, though, there is no agreement on the specific steps or terminology. This workflow is an interpretative knowledge production process that must be documented as such to ensure the intellectual transparency and accountability required for evidence-based archaeological interpretation. However, this is rarely the case, and there are no accepted schemas, let alone standards, to do so. As a result, there is a risk that the data processing steps of the workflow will be accepted as a black box process and its results as “hard data”. The first step in documenting a scientific process is to define it. Therefore, this paper provides a critical review of existing archaeology-specific workflows for airborne LiDAR-derived topographic data processing, resulting in an 18-step workflow with consistent terminology. Its novelty and significance lies in the fact that the existing comprehensive studies are outdated and the newer ones focus on selected aspects of the workflow. Based on the updated workflow, a good practice example for its documentation is presented.

Airborne LiDAR-Derived Digital Elevation Model for Archaeology

“…Due to the availability of data and first-hand experience, all of the datasets are from Europe. For the comparison of the different steps of data processing, these are the same test sites we have already used and outlined in other studies [1,7]. The description of the test sites is therefore only briefly repeated.…”

“…The use of topographic airborne LiDAR data (also known as airborne laser scanning or ALS) has become an essential part of archaeological prospection [1], e.g., [2][3][4]. Archaeologists interpret enhanced visualizations of high-resolution digital elevation models (DEMs) interpolated from classified point clouds [5][6][7]. The results have proven to be very efficient in detecting archaeological features, and have already drastically changed our understanding of archaeological sites, monuments, and landscapes, especially in forested areas, as seen in [8][9][10][11][12][13][14][15][16].…”

“…To provide context, a recent paper summarized the archaeology-specific data processing workflow in 18 steps. These steps range from raw data acquisition and processing, through point cloud processing and product derivation, to archaeological interpretation, dissemination, and archiving [7]. It is important to emphasize that the subject of this paper concerns only a small part of this workflow: interpolation and, to a lesser degree, enhanced visualization (steps 2.4 and 2.5).…”

“…It combines ground data with archaeologically relevant micro-relief features or potential archaeological features: standing walls and stones, roads, channels, and earthworks [4]. Modern buildings are included to provide contextual information during the process of interpretative mapping, and to expedite orientation in the field [7]. Such an "archaeological digital elevation model" [4] has been called a digital feature model (DFM; Figure 1) [33].…”

“…The second goal is to contribute to archaeology-specific LiDAR data processing by providing the pipeline and tools for the automatic precision assessment of DFMs, which we have named the DFM confidence map. The DFM confidence map provides metadata that is a necessary part of the workflow documentation [7], helps in the process of interpretative mapping, and also enables the determination of the appropriate DFM resolution. The latter is a theoretical task, and another area that is neglected in the archaeological literature.…”