Industry Application: LiDAR Best Practices for Cultural Heritage and Archaeology Practitioners
The amount of LiDAR coverage for the Earth's surface has rapidly increased over the past few years, and a number of scientific disciplines are taking advantage of this increased availability of laser-derived data. Cultural heritage and archeology practitioners are no different, and the increased availability of LiDAR data is revolutionizing research in these fields. This trend is becoming common in the industry for a few reasons. First, LiDAR data is cheap or even free in many areas. More importantly, we are seeing an increase in LiDAR incorporated into archeological applications because the detail and resolution of the data allows practitioners to observe features in the landscape that were previously undetectable using conventional survey methods.
Willem Beex is an archeologist from the University of Amsterdam and the founder of BEEX, a company that provides technological solutions for cultural heritage research projects, and he has recognized the influx of LiDAR data usage. Beex indicates that there is a need within the industry to define the best practices for how LiDAR data should be applied by practitioners to their projects. In his recent article titled Lessons from LiDAR data use in the Netherlands, Beex compiled a set of the best practices specifically geared towards guiding these types of professionals in their LiDAR usage and to help them avoid "obvious mistakes when interpreting LiDAR data."
In the article, Beex discusses how professionals should identify various problems that are inherent to LiDAR data in an archaeological context. He provides a "checklist" that scholars can use when applying LiDAR data to their research. The issues that Beex details include how to identify gaps in LiDAR data, how the common gaps are generated, how LiDAR returns are not 100% accurate, how to further validate the classifications, how density of the data affects one's ability to detect features, and how gridding algorithms need to be carefully selected when gridding LiDAR data to create surfaces.
Out of the above list, selecting the correct gridding algorithm is most notable for Golden Software users. In his article, Beex uses Surfer to grid and create 3D surface maps from LiDAR data, and he outlines how using different gridding algorithms will result in very different surfaces. He follows this up by describing how the Kriging method with an elongated search can generate a much different grid than using Kriging with a simple search. The images below are taken from Beex's article and demonstrate the differences.
I found the checklist the most useful aspect of Williem Beex's articl and recommend anyone using LiDAR take these five points into consideration:
- Always check for the presence of gaps in the data.
- Always check the classification of the data.
- Always check the density of the data versus the size of the detected features.
- Always check which algorithms and variables were used.
- Always ground-truth the results in the field.
Read the full article here: Lessons from LiDAR data use in the Netherlands