| dc.description.abstract | Photogrammetry is a technology with a wide range of applications
nowadays. Compared with traditional technology, photogrammetry has the
advantages of high mobility, low cost, and safety. With the advancement of
technology, thermal image monitoring has also started to be applied to the
prevention of slope disasters. Unlike optical images, thermal images do not
provide detailed geometric information about the object, but they can
provide temperature information instead for regional tracking by the
monitor. Recent studies have shown that thermal images can be used to
analyze potentially unstable areas hidden behind the slope surface by
temperature difference. Therefore, if the geometric information of the slope
can be retained through optical image analysis and supplemented with
temperature information to track the hidden unstable areas in the slope, it
can provide more comprehensive monitoring data.
The main objective of this study is to use computer vision technology
to fuse optical and thermal images for analysis and develop a field
instrument based on the method. In addition to maintaining the original
slope displacement analysis, the thermal image can also be used to analyze
the temperature difference and potentially unstable areas behind the slope
for future planning and tracking.
In this study, after the development of the field instrument, the scale
model test will be used to evaluate the instrument. The slope behind the
Central University is then applied as a field example. By setting up a
monitoring system on site, the slope displacement analysis is performed
from the multi-phase images, and the monitoring process of the overall
system is realized through the three-dimensional information model of
post-processing. According to the experimental results, the accuracy can
reach within 3 cm. The results can provide more effective decision data for
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slope disaster warning, prevention, and post-disaster planning. | en_US |