Over the past
several weeks, I have worked on a project which involved a study on detecting
Scythian burial mounds, in the general area of Tuekta, Russia. The ultimate
goal of the study was to generate a raster file, containing a random
distribution of points which would express the possibility of presence of a
Scythian burial mound, based on previously known information.
The metrics
considered for a possible presence of a burial mound in the immediate area of
the points were: slope, aspect and elevation. All of these layers were created,
and generated in ArcMap based on DEMs downloaded from the web. The study itself
was confined to a general greater, area of Tuekta, Russia, and the random
points of the predictive model were merged with previously marked locations of
known burial mounds, in order to have the spatial data of the known locations
influence the appearance of similarly-set points.
The results
of the study are represented based on an OLS model, which was created after the
merging of the point files. With zero being an average value, the coloring of
the points will tell us not only how compatible (or incompatible) the location
of the given point is with a possible burial mound, but also express the degree
of confidence in the result based on the data provided. The spatial
autocorrolation test that was ran on the data showed the z-score (indication of
the normal distribution of data) of 14.36 and the p-value (the likelihood that
the data is not randomly distributed) at 0.0.
There are
factors in the predictive model, which were not considered for this study but
may be of importance to its overall accuracy. These factors may include the
proximity to water, the landscaping of the landmass, proximity to other sites,
and maybe even the overall space around the point. (The known burial mound
locations all occur close to one another, in a very large cluster.) The model
does however provide locations of potential locations based on the exact
coordinates of each point. Each positive hit could benefit from a field survey,
with all other factors neutral.
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