As you probably know, the availability of lidar data (lidar stands for Light Detection and Ranging) has taken the archaeology world by storm over the last decade or so. The collection of airborne lidar data involves sending out laser pulses from a plane, which are reflected back from the point at which they hit the ground (or any intervening objects). Given that the speed of the light is known, the distance each pulse has travelled can be calculated from the time it takes to return; in conjunction with very precise GPS positional data for the plane, the result is an accurate 3D location of each point in space, and therefore an accurate model of the land surface. This can then be viewed in a GIS, where it makes a superb tool for detecting subtle earthworks, such as coaxial boundaries, against background clutter.
Unfortunately, there is not 100% lidar coverage of the Dales yet. The lidar I am using has come from the UK Environment Agency, who collect data as part of flood monitoring and environmental asset planning programmes and therefore target specific, required areas. The image below shows the 1m resolution (there is a point value for every square metre) lidar data available for the Yorkshire Dales National Park. It is very clear from this map that most of the data collection has focussed on the river valleys, with coverage often not (or only just) reaching the top of the valley sides. Which makes it difficult to rely on when prospecting for coaxials, which often, frustratingly, survive just above this level!
In places, however, coaxial field boundaries do show up clearly in the lidar data, running across the contour as in figure 2, and I have been mapping them from the lidar in conjunction with aerial photographs and maps, in order to characterise the individual systems. Lidar data can be viewed in various ways: figure 2 contains a simple 2D hillshade plot that ‘makes sense’ to the human eye, but various parameters can be exaggerated, or the point values used to analyse assorted elements of the terrain. The data can also be viewed in ‘3D’ (as in figure 3), which helps to visualise and understand relationships between the archaeology and the landscape. Usefully, it is also possible to drape other data sets over this digital elevation model – such as the aerial photography in figure 4.
One of the bonuses of lidar data is the facility to alter the direction from which the (artificial) light source is shining on the landscape – depending on the orientation of individual features or their position in the topography, they may not be easily visible when illuminated from any given direction (as is the case in an aerial photograph, for example). Figure 5 shows the same medieval lynchets in Wharfedale illuminated from 3 different directions, and the difference this has on the visibility of the archaeology is very clear. The same goes for the height of the light source above the ground (think of the difference between viewing earthworks at midday and in late afternoon!). Obviously, while particular light directions and heights reveal more detail in landscapes, the flip side of this is that others cause detail to be obscured and it requires a little trial and error to work out which are the most advantageous light source positions.
One way to get around going through 8 or 16 different images by hand for each area, is to use a combination of the images, which essentially includes the ‘best bits’ of each one. For my first foray into the world of computer coding – aided and abetted by my infinitely more code-minded colleagues – I am in the process of writing a piece of code that does this, by applying principal component analysis. You can see the difference between the images below…it’s often only subtle, but in places it may make interpretation just that bit more accurate.
You can find out more about lidar here: http://content.historicengland.org.uk/images-books/publications/light-fantastic/light-fantastic.pdf/