If you read this blog often, then you have probably already seen some or other article about LIDAR being used in archaeology. This article aims to give you a proper introduction to the technology and its applications in archaeology.
What is LIDAR
LIDAR stands for Light detection and Ranging. It is a method for measuring distance using light. Take the image below as an example:
A sensor is attached to an airplane. Laser light is shot down, bouncing off various types of surfaces. We can measure distance to an object based on how long it takes for the light to bounce back.
The output of this exercise is called a point cloud. You can think of it like a 3D model made out of dots, where each dot represents a point that the light hit. Here is a visualisation of a point cloud representing a mountain. The colours represent the height of the point in relation to the ground:
Properties of the returning light, such as the intensity for example, differ based on the kind of surface that was hit. This kind of information allows us to classify each point in order to identify vegetation, buildings, water, etc.
Once you have a point cloud, you can further process it to output different kinds of artefacts. Out of these, the following have applications in archaeology:
- 3D model: By filling the gaps between the points we can create a 3D model. This can be useful to preserve/document a building in virtual form.
- Digital surface model (DSM): A digital terrain model (DTM) allows us to see what the ground looks like under the vegetation, buildings, etc. A digital surface model (DSM), on the other hand, is a DTM that allows us to keep certain objects identified above the ground. It is often used in archaeology to reveal what buildings look like under thick vegetation, as the laser’s light can go through the holes in between the leaves, hitting whatever may be underneath.
- Raster: You can think of a raster as an image with geographical data. You could, for example, output a raster from a LIDAR point cloud, which outlines the shape and location of some archaeological remains.
- Insights: The outputs of the processed point-cloud do not need to be limited to visual options. LIDAR can be used to gather insights as well, whose output type can vary. In archaeology it can be used to detect changes in a site (e.g. looting), output distance metrics, etc.
Where to find data
Now that you know what you can do with LIDAR, it’s time to talk about how to get the data.
Depending on what you want to do, you may be able to find some data online. These sites provide open data access for research purposes:
- Open topography: The site is mainly focused on the USA with some datasets from other countries. One archaeological dataset found here is the Caracol/Chiquibul Belize Lidar dataset.
- Cyark: The site is focused on the digital preservation of cultural heritage. Some examples of LIDAR point-clouds of archaeological sites available here include Tikal and Ayutthaya.
- Carbon Atlas: This site also provides open access to LIDAR scans for Southern Africa. Note that the scanning was focused on forestry and environmental topics.
- Environment.data.gov.uk: LIDAR survey of the UK.
- USGS: Collection of worldwide data for multi-disciplinary scientific applications.
- NASA: NASA has used satellite LIDAR to map our planet (and others). Note that satellite LIDAR is probably not good enough for your archaeological use case as the resolution will not be good enough to pick up things like buildings. However, I am still adding it here as maybe you get creative and want to try something out 🙂
Chances are that the area that you need has not been surveyed yet, or it is not part of these open data initiatives. In this case, you’d need to do the mapping yourself. Fear not, you have a few options:
- Hire a company: There are companies that you can hire, which have the pilots, airplanes, sensors and experts to do a LIDAR scan for you. If you need to do the scan once (or maybe once a year) this is probably your best option, as it requires no up-skilling into the intricacies of the hardware. One example of such a company can be found here.
- Buy/rent a drone/robot: It may be that you will need to rely on doing LIDAR scans quite often for your use case, and therefore need to be able to do so on demand. You have the option of buying/renting a drone/robot in this case. One thing to note here is that you’d need to up-skill your team, or hire an expert, in order to do the configuration of the hardware. This is because the configuration can differ based on what is being mapped. One example of such a drone can be found here.
- Buy a handheld LIDAR device: It may be that you are not looking for an aerial scan specifically, but rather for a more close range ground-based 3D scan of a site. You can look at handheld or tripod based LIDAR options in this case.
- Build your own scanner: The sensor itself is not expensive, so if you are into building hardware this may be an option for you. Here are some examples of LIDAR sensors that can be bought, an example of a development kit for LIDAR, and another on how to build your own scanner from scratch.
Processing the data
Like with any dataset, the transformations that you will need to do on your point-cloud will differ depending on 2 things:
- What the point-cloud is of: is it a forest, a desert, a city, etc.
- What you plan to do with it: create a 3D model, reveal buildings under vegetation, etc.
While I transformed some of these point-clouds myself I found four transformations that seemed to come up in all my experiments, and which you will most likely need to do. The four were:
- Identifying the ground points: this gives us a baseline in relation to which the location of the other points can be defined.
- Computing the height of the points: Now that we have the ground as a base, the height of each point can be computed in relation to the ground. This allows us to have a common representation of distance between points.
- Classifying the points: Each point represents a surface that was hit by the laser. The properties of the returning light allow us to classify points to be buildings, water, vegetation, etc. The LIDAR tooling available for us already does the classification through existing algorithms, allowing you to focus your work on experimenting with the available parameters to fit your use case. That said, it may be that the algorithms available are not good enough for what you need, leading to you into the deep trenches of LIDAR data to create something custom.
- Cleaning the noise: You can think of noise in point-clouds as isolated points. For example, points representing particles in the air are irrelevant when looking for buildings under vegetation, and are rather sparse. Additionally, if you have 2 points classified as building in a group of 20 vegetation points, for example, these buildings are probably miss-classifications.
Alternatives to LIDAR
As with any tool, depending on what you want to do, there may be an alternative technology that can cover that use case. For LIDAR in archaeology, two alternatives that come to mind are as follows:
- Photogrammetry: If you are creating a 3D model and don’t have overgrowing vegetation to remove from your scan, you can create a 3D model using photogrammetry instead. You can also combine laser scanning with photogrammetric methods to get an even more accurate representation of the site, just like the team at the Zamani Project does.
- Satellite imagery: If you are looking to create some sort of raster output, satellite imagery might already cover your use case and it is a lot more accessible than LIDAR data. If you want to learn more about the use of satellite imagery in archaeology, check out this previous post.
That concludes part 1 of this topic. I decided to play with some tools and see if I could create a Digital Surface Model of the Tikal data that I found on Cyark. I’ll detail the process in the next post.