
Joe Artz
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Papers by Joe Artz
statewide, 1m horizontal resolution Light Detecting
and Ranging (LiDAR) imagery, with both states
making the data available for unrestricted public
download and viewing on the Web. The four
studies summarized in this paper found that
mounds as small as 3 m diameter and 30 cm high
were readily visible in these datasets. The studies
successfully identified 37 percent of 8,726 mounds
previously recorded at a total of 758 sites located
in physiographically-varied regions of each state.
Two studies, including one funded by NCPTT,
developed LiDAR Surveyor, an ArcGIS model
that scans large tracts of land, extracting features
with the characteristic 3D geometry of conical
mounds in LiDAR. The current version scanned
86 km2 in seven physiographically-varied areas
of interest, identifying 1216 total mound marks
(12 km2), flagging 88 percent as false positives,
and identifying potential mounds at twenty-five
of twenty-eight known mound sites within the
study areas. The clustering of detected mounds in
these 25 groups illustrates the model’s utility for
prospection, identifying specific areas within which
to target costly field verification surveys. The other
two studies summarized here achieved mound
detection rates of 36 percent by incorporating
georeferenced maps and digitized survey traverses to
assist in searching LiDAR for 6223 known mounds
in seventeen Minnesota counties; 118 previously
unknown potential mounds at twelve sites. The
studies provided important information about land
use factors contributing to mound destruction and
preservation. The four studies underscore that
archaeologists using LiDAR must be aware of, and
explicitly account for, the limitations of LiDAR
when using it for archaeological prospection and
verification.
statewide, 1m horizontal resolution Light Detecting
and Ranging (LiDAR) imagery, with both states
making the data available for unrestricted public
download and viewing on the Web. The four
studies summarized in this paper found that
mounds as small as 3 m diameter and 30 cm high
were readily visible in these datasets. The studies
successfully identified 37 percent of 8,726 mounds
previously recorded at a total of 758 sites located
in physiographically-varied regions of each state.
Two studies, including one funded by NCPTT,
developed LiDAR Surveyor, an ArcGIS model
that scans large tracts of land, extracting features
with the characteristic 3D geometry of conical
mounds in LiDAR. The current version scanned
86 km2 in seven physiographically-varied areas
of interest, identifying 1216 total mound marks
(12 km2), flagging 88 percent as false positives,
and identifying potential mounds at twenty-five
of twenty-eight known mound sites within the
study areas. The clustering of detected mounds in
these 25 groups illustrates the model’s utility for
prospection, identifying specific areas within which
to target costly field verification surveys. The other
two studies summarized here achieved mound
detection rates of 36 percent by incorporating
georeferenced maps and digitized survey traverses to
assist in searching LiDAR for 6223 known mounds
in seventeen Minnesota counties; 118 previously
unknown potential mounds at twelve sites. The
studies provided important information about land
use factors contributing to mound destruction and
preservation. The four studies underscore that
archaeologists using LiDAR must be aware of, and
explicitly account for, the limitations of LiDAR
when using it for archaeological prospection and
verification.