Recent advances in LIDAR technologies have increased the resolution of airborne instruments to the sub-meter level,
which opens up the possibility of creating detailed maps over a large area. The ability to map complex 3D structure is
especially challenging in urban environments, where both natural and manmade obstructions make comprehensive
mapping difficult. LIDAR remains unsurpassed in its capability to capture fine geometric details in this type of
environment, making it the ideal choice for many purposes. One important application of urban remote sensing is the
creation of line-of-sight maps, or viewsheds, which determine the visibility of areas from a given point within a scene.
Using a voxelized approach to LIDAR processing allows us to retain detail in overlapping structures, and we show how
this provides a better framework for handling line-of-sight calculations than existing approaches. Including additional
information about the instrument position during the data collection allows us to identify any scene areas which are
poorly sampled, and to determine any detrimental effect on line-of-sight maps. An experiment conducted during the
summer of 2011 collected both visible imagery and LIDAR at multiple returns per square meter of the downtown region
of Rochester, NY. We demonstrate our voxelized technique on this large real-world dataset, and derive where errors in
line-of-sight mapping are likely to occur.