International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
4. CONCLUSIONS
We develop a road extraction method using lidar data and high
resolution optical images. The method tackles the problem of
extracting grid roads in urban areas with dense buildings. Using
lidar data, the difficulty of resolving the occlusion of roads in
optical images is eliminated. It demonstrates the potential and
power of using lidar data to extract information from
complicated image scenes. To obtain more reliable results,
image analysis (to detect contextual objects: grasslands, parking
lots, vehicles etc.) for contextual information extraction is
integrated into the whole procedure. It greatly improves the
final results in correctness and accuracy. The work described in
this paper clearly indicates that involving multiple source of
information will definitely improve the extraction results in the
complicated scene. Future work will include testing the method
using more datasets and developing algorithms of adaptive
threshold determination in the multi-step processing, which will
be a challenging work.
Acknowledgement: The authors are grateful for the support of
a GeolDE project, Canada: ‘Automating 3D Feature Extraction
and Change Detection from High Resolution Satellite Imagery
with Lidar and Maps’
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