Introduction
The town of Pleasant Valley would
like to preserve some of the town`s history as well as prevent the sale of an
already occupied plot via the development of a detailed and accurate map of the
Hadleyville cemetery. This project comes with a few obstacles; all original
records and maps have been lost, the monuments date back to 1865 making them
difficult or impossible to read, and some burial plots are not marked at all. A
simple map could be created to indicate location of marked plots within the
cemetery, however this would not include any attribute information correlating
to the individual plots. A GIS would include such attribute information as well
as the spatial data of the cemetery, this would more comprehensively preserve
information about the cemetery. A UAS capable of stable, high resolution photography
was programmed to take a collection of aerial images of the cemetery in order to
produce an optimal base map. The class used notebooks to
record all observable attribute data pertaining to each individual burial plot and
cellular phones to photograph the same data that was recorded manually to
ensure accuracy. This
method of field data collection can be used to create a base map in a GIS and then
digitize plots with associated attribute data included.
Study Area
Pleasant
Valley`s Hadleyville cemetery is located in west central Wisconsin, in Eau
Claire county. The town of Pleasant Valley is in the southwest corner of the county
(figure 1). Data was collected on a warm, sunny afternoon in early fall.
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| Figure 1 |
Methods
A UAS from the Phantom series was used for the
aerial imagery. According to www.dji.com , the
entire Phantom series contains a gimbal with 3-axis stabilization capabilities
and are all created for high-level aerial photography. The class used notebooks
to record data and cellular phones to photograph the same data that was
recorded manually. The use of notebooks provides a hardcopy backup of the
digitally collected data. The data recorded in notebooks is also data gathered
by the human eye, which provides a different perception of the data as it is
collected and can be used together with photographic images to ensure accurate
interpretation. The use of a survey grade GPS receiver was attempted, however a
complete list of points would have been extremely time consuming and a signal
was not found when under trees. This GPS receiver was selected over a mapping
grade receiver because the mapping grade GPS is generally accurate to within a
meter, many plots are closer together than this. In order to consolidate
all collected data and include all the same attributes for each section of
attributes, an excel spreadsheet was created in a public Google doc. A cemetery
grid pattern with lettered columns and numbered rows was created overtop a base
map to create point IDs for each plot and to ensure accuracy of attribute input
into the excel file from each contributing member. A primary attribute to be
included was the name of the person occupying the plot and initially the presence
of joint tombstones caused the problem of having more than one name attached to
one point ID. This was solved by entering each name as a separate point ID and
the inclusion of a notes field to denote such cases. When the excel file was
complete it was saved as a csv file to be imported into ArcGIS. The GPS
accuracy of the UAS enabled it to obtain a clear, centered image of the entire
cemetery and a moderate pixel resolution allowed for zoom levels close enough
to verify the presence of a difficult to view monument as well as for the
optimal placement of two points on one monument. While digitizing points, the
point ID attribute was also entered and the completed csv formatted table of
attributes was brought into the layer, joined to the table of point IDs
associated to the newly digitized points, and then exported as a new layer to
make the join permanent (figure 2). From this result a layout was created with
symbology representing alphabetical groupings of the last names (figure 3),
which would make the location of a loved one easier for visitors.
Results/ Discussion
The consolidation of data into a communal excel file containing normalized
data fields greatly improved the efficiency of the creation of a GIS. This task would
have otherwise been much more complicating due to the fact that data collection
was completed by numerous groups and in different manners. Had the survey grade
GPS been used to obtain a complete list of coordinates for every plot in the
cemetery instead of manual data collection based off a basic diagram, this
project would have taken much longer still. There is still room for error given
the lack of a GPR system to located unmarked burial plots, however visual
observation provided confirmation that plots lacking a tombstone tended to have
some sort of indication that it was an occupied plot. Data collection could
have been improved if a normalized data list had been created and a basic
diagram had been drawn up before collection began and teams assigned to specific
areas of the diagram for data collection. This would have reduced the initial
confusion between groups and reduced the odds of missing data.
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| Figure 2 |
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| Figure 3 |
Conclusion
Overall the use of digital and observational field data collection
secured a successful final project. Each method of data collection contributed
to the collection all data necessary to meet the goal of this project, to
create a detailed and accurate map of the Hadleyville Cemetery. None of the
data collection formats used could have singularly collected all that was
necessary to create the GIS. There were a few broken monuments piled along the
edge of the cemetery, missing information associated with a few plots, and there
is a slim possibility that time has erased any evidence of an occupied plot. However,
prior to this project the town of Pleasant Valley had no maps or records of the
Hadleyville cemetery and this project has resulted in the identification of 158 occupants within this one and half acre cemetery. The resulting project can be
edited in ArcGIS to digitize in any future additions or update information of existing
data; it can also be used to create a web map online for interactive use by the
public.
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