“A common mistake is to assume, implicitly or explicitly, that Bronze Age and modern coastal morphology are essentially the same.” [1]
Well (pace
Tartaron) we have to start somewhere.
In order to
understand the possible relationship of Bronze Age sites both to the sea and to
nodes of trade a good first step would be to determine the straight line
distance between each BA site and the nearest seacoast. By examining a map on which such
straight-line links are plotted we can begin to understand the relationship of
such sites to the shoreline and the focusing effect that shoreline
irregularities have in mapping inland sites to the sea. First, however, we must have a model of the
seashore of sufficient accuracy to allow us to say with some confidence what
those distances are and we have no choice but to start with the modern
shoreline. A picture should make these
initial themes clear.
Figure 1. Straight lines drawn from BA sites in Arcadia to the nearest seashore. |
In this map I have projected (straight-line) each BA site in Arcadia onto the nearest seacoast. Arcadia is entirely landlocked and its communication with the greater outside world is through neighboring territories; Messenia and the Gulf of Messenia to the S near modern Kalamata, across Triphylia to the W and the Gulf of Kyparissia, and across Achaea to the N (perhaps near ancient Helike). The primary contact between Arcadia and the ocean is through the southern Argolid near the head of the Gulf of Argos. It is this concentration of land-to-sea contacts created by the closest gulfs and inlets that I am speaking of. An accurate representation of site-shoreline direct lines will make this concentration effect clear and it will fulfill another function: that of classification. We would like an easy way of generating lists of onshore sites as distinct from those inland
But how is
this to be done with a database and software?
The first thing that is required is an accurate representation of the
shoreline for the entire Bronze Age world.
In the end I
decided to make my own. To be
sufficiently accurate the nodes should be no more than 20 m apart for the area
being mapped. The region of Locris is a
good example of the technique that I adopted.
Here is an image of the coast of Locris:
Figure 2. The shore of Locris (Euboea at the top). |
First let us
superimpose on this map a representation of the database BA sites in this area:
Figure 3. The north coast of Locris with BA sites as white squares. |
Here the
sites are represented by white squares. The
problem now is to create a straight line from each site to the nearest seashore
irrespective of any land obstacles, mountains, canyons, rivers, etc. The algorithm adopted should be sufficiently
rigorous to be reasonably convincing. To
draw a line to a point withing 30 m of the ‘ideal and perfect’ location should
be rigorous enough. In most cases we can
do better than that. But how should this be done?
The
algorithm I chose was as follows:
a.
Trace
by hand the outline of the several land masses
b.
Each
node in this line had to be 30 m or less from the next node.
c.
Produce
software that would try each (and every) site against all the outline nodes
until it found the smallest distance.
d.
The
output of this software would be a set of sql insert statements for a new
table, coast, that would hold, for each site, the minimum distance to the shore
along with the lat/lon coordinates for the location on the shore closest to the
site.
e.
Modifying
the production software to generate a distance to shoreline report from
the coast table. I described this report in my last blog post.
What did
this process look like. In Google Earth
Professional I generated a ‘path’ structure that would follow the coast. When visible, I followed the wet sand mark
along the coast. It looked like this:
Figure 4. Kamares
Beach on Sifnos. The red dots are interpolated coastal points. |
In this figure we see the
Paralia Kamares on Sifnos (36.990171° N, 24.678167° E). I have interpolated a coastline for this
beach (blue line). My interpolated
points are the red dots. The beach is
525 m long (I used the yellow segmented line to measure it) and the dots divide
the beach into 67 segments. Each node
(dot) therefore is separated from the next by ~7.83 m. The next figure shows a detailed view:
Figure 5. Detail of Kamares Beach. |
In figure 4 the yellow measuring line has been removed and the reader
will get a better idea of the spaces between the nodes (red dots on the blue
coast line).
The site closest to Kamares Beach is C7406, which is a Sanctuary of the
Nymphs on Sifnos. The minimum distance
from this sanctuary to the closest shoreline is ~508.8 m. Given tides, erosion, and other factors the
figure should be accurate to +/- 5 m (503.8 to 513.8 m) at worst.
Figure 6. Detail of closest marker to C7406. |
In this
extreme closeup we see the specific node that marks the closest approach of the
shoreline to C7406. Its next nearest
node on the left is ~15 m. From C7406 to the closest node is an angle of 332.56°. To the next closest point on the left the
azimuth is 330.81°. So, an angular
displacement of something over 1.75° per node and a lateral error distance of
about 15 m. arises from this scheme.
Other sites will provide widely varying parameters of distance and angle
but I present this example of C7406 as a typical case and it is this sort of
accuracy or better which I have striven for in all the coast tracing exercises
I have undertaken.
Which
Approach?
I began this
extended coastal exercise with the assumption that the entire coastline of the
several land masses and islands had to be traced in detail. In Crete I attempted to trace the entire
coastline. The yellow outline in the
next picture represents what I was able to accomplish:
Figure 7. Crete. The yellow outline represents my attempt to trace the coast. |
Even this (not entirely satisfactory) outline required 8000 points placed by hand. It required several days of steady work but, in the end, I decided that this approach has serious drawbacks. First of all the human factor of such eye-straining repetitive work is a drawback. Second, even 8000 points do not result in the accuracy which I desired to achieve. The coastline of Crete is about 985 km (985000 m). Dividing this figure by 8000 gives an average distance between nodes of about 123.1 m. This is about six times worse than the accuracy given for the Sifnos example above. There would need to be at least 48000 nodes in the outline of Crete in order to render both a complete outline of Crete and one which was of sufficient accuracy to use for closest shoreline point determination. I was forced to abandon one criterion or the other and I decided to jettison the idea of creating complete outlines of the landmasses the eastern Mediterranean and just concentrating of those stretches of coastline most likely to be closest to BA sites.
To create an accurate least-distance placing (and with minimal effort) it is necessary to center a circle on each
site and note where that circle touches the coast. Then we draw detailed
coastline nodes only at these specific points.
This approach immediately dispenses with having to outline projecting
capes and peninsulas since these are highly unlikely to be the closest points
to anything. Here is an example.
Figure 8. Eupalion (C562) in Phocis. Corinthian Gulf |
In figure 8 the site of Eupalion/Gouva (C562) is represented by the square rectangle in the center. Centered on that rectangle is a red circle that just touches the shoreline. The coastal outline (blue line) is only elaborated in the vicinity of the red circle. Now it is only necessary to place one or more nodes around the tangent of circle/line segment. This results in considerable time savings and accuracy is enhances. In the neighborhood of the intersection of the red circle and the coast it might pay to lay down points that are much closer together and so ensure greater accuracy.
. Figure 9. Southern Phocis on the Gulf of Corinth |
In figure 9 C562 (Eupalion) is on the left and two more
sites in southern Phocis (C563, C564) are on the right (east). The coast outline only touches the coast at
spots where the closest shoreline has already been determined by circles
centered on the sites themselves. Proceeding in this way means that most
the rugged south coast of Phocis will not require modeling in this
typical example.
In the example of Crete that I mentioned achieving the desired accuracy with the ‘whole coast model’ approach requires about 48000 points in the shore outline. As there are 1500+ sites on Crete the computational cost will be 48000 * 1500 or 72,000,000 separate distance computation routine calls. If we allow only 10 points per site using the previously described circle-focus method then it would require only 15000 outline points and so 1500 * 15000 = 22,500,000 routine calls – a computational savings of about 2/3. This would run is something under 2 minutes on GoDaddy's servers which is where I run this utility-type software.
Another approach is to take advantage of the fact that Crete is divided into subregions in the Mycenaean Atlas database and so it's possible to model just one region at a time. This would considerably reduce and spread out
the workload into manageable chunks.
Figure 10. Gulf of Atalantis. Northern Locris. |
Figure 10 is
an example of the circle-focus method as I applied it to Northern Locris. Here the sites are represented by white
squares. Each is the center of a circle
which extends to the closest coastline.
The blue line is the coast outline.
Notice that it only touches the shoreline where the circles do. Only those segments are carefully
modelled. The rest of the line is ‘armature’. The software algorithm adopted for
calculating the minimal distance traverses this entire blue outline (node to
node) and, for each site, returns that distance along with the lat/lon pair of that specific closest point on the
coast. In figure 11 we see what
that this same region of Locris looks like after processing and with the shortest distance lines properly placed.
Figure 11. North
coast of Locris with lines drawn from sites to nearest seashore. |
I represent
the nearest approach of site to seashore with a blue line that starts at the
site (indicated by a diamond) and ends at the closest seashore point (indicated
by a red circle).
These are
some of the considerations that I had in mind when performing the task of
automating the task of finding the closest seashore to every BA site. The reader
should keep in mind that the ‘shortest distance’ is not from the site,
exactly. It measures the distance from my
site marker to the seashore.
In another
blog post I would like to discuss what algorithm my software used and whether
there are any other useful coastal outline databases available.
Footnotes
[1] Tartaron
[2017] 140.
Bibliography
Tartaron
[2017] : Tartaron, Thomas F., Maritime
Networks in the Mycenaean World.
Cambridge University Press, ISBN:
978-1-108-43136-1. Paperback edition of
2017.