Initially it was hoped that using dedicated software would enable the modelling of specific urban archaeological deposits to create of a borough wide database of deposit information based on archaeological excavation and borehole data. It was soon realised that only two sources of information were recorded in a uniform fashion that enabled inter-site comparison: Depth of “natural” (undisturbed surface or “drift” geology) and depth to water table. More detailed archaeological deposit data has only been possible on a small quantity of sites. These can be expressed as heights in metres above Ordnance Datum (OD) or as heights relative to existing surface. Within these types there are two dataset variations, the much smaller sample, taken from sites where all data was available in OD, and a much larger coverage where depths are derived from ground surface taken from LIDAR data.
With these data, 2D surface maps of the historic core, and certain other areas of the borough are possible. These interpolated maps can show depth of made ground and natural subsoil and water table depth. This information has informed on the growth of the town, and areas where waterlogged (and thus preserved) archaeological material may remain. Similarly, colour graded point maps can also show site specific information in a quickly accessible to development management officers,
The grid references for the larger sample of data points “depth from surface” were taken with an 8 figure NGR. this has introduced a small quantity of spatial error. The points are to the south west by a maximum of 10m, though usually less than this. Points where an HBSMR deposit model exists are accurate adding strong vertical (as not extracted from LIDAR) and horizontal resolution, but reduced point number affecting interpolated raster layers.
Hannah Cutler, 2017
Map showing data points colour coded by the depth of archaeological depoists (and “made ground”), this can be interpolated to provide projected depths, but must be viewed with caution due to the high variability within short distances and areas with fewer data points, (Image: SCCAS)
When interpolated depth of “natural” data is compared with interpolated water table data we can suggest the locations of water-logged deposits. Areas in blue are where the interpolated water table is higher than the natural surface geology, (Image: SCCAS). This must be viewed with caution in the central and northern parts of the town due to low numbers of data points.
Stratigraphy of the town defences, (Image: SCCAS)