248
3 These point clouds consist of geo-referenced and dimensioned points, with an average
density of 12 points per m
2 , which thus render the photographed area (or detected, in the
case of LiDAR processing) in digital form and in three dimensions. Available algorithms,
including through open source software, are able to analyze both geographically organized
and dimensioned points, and render an exact 3D urban composition in numerical form.
4 LiDAR (Laser Imaging Detection and Ranging) performs remote sensing to determine the
distance of an object or surface through the emission of high frequency laser pulses by a
flying sensor (plane or drone). The distance of an object is given by the length of time
elapsed between emission and reception. Very high frequency pulses bouncing from objects
or the ground are converted into geo-referenced and dimensioned points, thus giving rise to
a “point cloud” from which the exact reconstruction of an area can be created in the form
of three-dimensional digital models.
Focus B: Using Aerial Photogrammetry for Urban
Sustainability Analysis
Denis Maragno
Department of Design and Planning in Complex Environments,
IUAV University of Venice,
S.Croce, 1957, 30135, Venice, Italy
dmaragno@iuav.it
Keywords Forecasting UHI, Monitoring climate change, Digital surface
model
The ongoing climate change and energy issues are among the most important challenges that city planning, zoning, and architecture are now facing.
Limited resources and the economic crisis aggravate the difficulties of
intervention, forcing one to identify multifunctional interventions for combined solutions to different problems and needs (Musco et al. 2013).
In recent years, there has been considerably growing interest in alternative
and renewable forms of energy supply (Pearce 2002); at the same time, the
difficulties experienced by cities in resisting the effects of climate change are
steering Public Administrations toward formulating integrated policies in
order to decrease CO 2 production and simultaneously increase the land’s
resilience to climate change (Musco 2008).
The ensuing difficulties lead one to analyze urban environments using the
most advanced technology and the best tools available.
We introduce an example of applied methodology, where, using a point
cloud generated by a photogrammetric technique, we will consider what
buildings are most suitable for installing a PV system and which areas are
most affected by solar incidence (Wilson et al. 2000).
Thanks to recent advances in photogrammetry Hardware and Software
(Hirschmüller 2008), by using stereoscopic techniques it is possible to make
3D point clouds
3 and digital models of a terrain comparable in definition to
those produced by active sensors (e.g., LiDAR). But unlike LiDAR data,
4 a
(continued)
F. Musco et al.
3 These point clouds consist of geo-referenced and dimensioned points, with an average
density of 12 points per m
2 , which thus render the photographed area (or detected, in the
case of LiDAR processing) in digital form and in three dimensions. Available algorithms,
including through open source software, are able to analyze both geographically organized
and dimensioned points, and render an exact 3D urban composition in numerical form.
4 LiDAR (Laser Imaging Detection and Ranging) performs remote sensing to determine the
distance of an object or surface through the emission of high frequency laser pulses by a
flying sensor (plane or drone). The distance of an object is given by the length of time
elapsed between emission and reception. Very high frequency pulses bouncing from objects
or the ground are converted into geo-referenced and dimensioned points, thus giving rise to
a “point cloud” from which the exact reconstruction of an area can be created in the form
of three-dimensional digital models.
Focus B: Using Aerial Photogrammetry for Urban
Sustainability Analysis
Denis Maragno
Department of Design and Planning in Complex Environments,
IUAV University of Venice,
S.Croce, 1957, 30135, Venice, Italy
dmaragno@iuav.it
Keywords Forecasting UHI, Monitoring climate change, Digital surface
model
The ongoing climate change and energy issues are among the most important challenges that city planning, zoning, and architecture are now facing.
Limited resources and the economic crisis aggravate the difficulties of
intervention, forcing one to identify multifunctional interventions for combined solutions to different problems and needs (Musco et al. 2013).
In recent years, there has been considerably growing interest in alternative
and renewable forms of energy supply (Pearce 2002); at the same time, the
difficulties experienced by cities in resisting the effects of climate change are
steering Public Administrations toward formulating integrated policies in
order to decrease CO 2 production and simultaneously increase the land’s
resilience to climate change (Musco 2008).
The ensuing difficulties lead one to analyze urban environments using the
most advanced technology and the best tools available.
We introduce an example of applied methodology, where, using a point
cloud generated by a photogrammetric technique, we will consider what
buildings are most suitable for installing a PV system and which areas are
most affected by solar incidence (Wilson et al. 2000).
Thanks to recent advances in photogrammetry Hardware and Software
(Hirschmüller 2008), by using stereoscopic techniques it is possible to make
3D point clouds
3 and digital models of a terrain comparable in definition to
those produced by active sensors (e.g., LiDAR). But unlike LiDAR data,
4 a
(continued)
F. Musco et al.