Point Clouds at Brisbane City Council
Summary and Background
Peter Murray spoke to our 2018 Technical Forum delegates about Brisbane City
Council (BCC)’s use of Point Clouds in 12d Model software.
Peter works in the
Surveying area of BCC, which is actually run as one large local authority
covering the whole city; it’s unusual in that sense. It’s the largest local
authority in Australia, by both budget and population (it covers a population of
around 1.2 million and an area of 1,367 square kilometres). It works to an
annual budget of around $3.1 billion – to cover traffic management and
infrastructure, public transport, parks and opens spaces, economic development,
and lifestyle and leisure. This leads to a great deal of variety in work – large
projects and many smaller ones as well.
There are nearly 8,000 people working in the organisation. In Planning and
Design, there are nearly 350 people – surveyors, road designers, drainage
designers, bikeway designers, Geotech, pavement designers, landfill management,
GIS, architects, landscape architects, water management, flood modellers, urban
planners, and environmentalists.
The ongoing development of methodologies processes and functionality to make
the use of point clouds derived from various sources in 12d Model for design,
survey and general surface modelling has been important at BCC in recent times.
What is a point cloud?
A point cloud is just a huge collection (thousands-billions) of points –
they’re unrelated despite looking like they’re related. The enormous scale
causes issues – bigger projects lead to more things that can go wrong. Point
clouds have been in use since the mid-1990s…which gives some pause as to whether
they’re still as relevant as they’re sometimes deemed to be.
How to acquire point clouds
A point cloud can be generated by laser scanning (e.g. Terrestrial,
Mobile, Aerial), via photogrammetric techniques (e.g. UAVs), or using SONAR
(e.g. Hydrographic Surveys).
Why use point clouds?
They appear to be very detailed and intuitive – they look almost like
photographs (and it’s possible to measure between the points), which makes
people think they’re loaded with useful information. Point clouds can also be
captured rapidly and at a relatively low cost (particularly using LiDAR – this
can lead to being able to capture, within days, huge amounts of information that
would otherwise take surveyors years to collect). They allow for measuring of
areas with difficult access, allowing for increased safety in areas such as
freeways and dangerous industrial areas (e.g. through use of drones).
And they’re intimately intertwined with BIM, which makes them unavoidable,
especially as they become more and more mainstream and accessible to a wider
Is point cloud data a viable option as a data source in 12d Model, and how could
it be incorporated into existing workflows?
Point clouds can be generated from many sources such as Aerial LiDAR Scanning,
Mobile Laser Scanning, Terrestrial Scanning, Photogrammetry (e.g. UAVs
and Terrestrial), Portable Systems (e.g. ZeBeDee) and Sonar
(Hydrographic Surveys). These different sources have their own characteristics.
Point clouds are alluring because points clouds:
• appear to be very detailed and intuitive
• can be collected rapidly and at relatively low cost
• can collect information about difficult to access features
• record everything in the line of sight of the collector
• are intertwined with BIM
What are the potential downfalls of using point clouds?
In reality, though, there are many issues and problems because points clouds:
• are a relatively new technology
many individual points (millions and billions)
• are comprised of many independent points which are essentially simple xyz
• do not fit well with traditional
survey and design processes .
Highly specialised skills are required to produce a high-quality point cloud.
The size of the datasets required is also prohibitive. It is also an issue that
point clouds don’t fit well with traditional design processes, and are
technology-hungry – a variety of sophisticated equipment is required for their
How to collect the datasets for point clouds
LiDAR – used since about 2010 by BCC for flood plain modelling, concept designs,
investigations, and volumetric resumptions, LiDAR is regularly incorporated into
their workflows and is an accepted data source. Data is generated by a plane
flying over the ground with lasers pointing below and measuring downwards. As
the lasers hit the ground, the beams are reflected back up to the plane so the
plane can take measurements, at a rate of about two million measurements per
Unfortunately, vegetation and water are the ‘natural enemies’ of LiDAR, so it
can’t be used everywhere. Over time, their teams have learnt that not every
point is required, nor is every point reliable…and unfortunately it isn’t always
possible to pick the reliable points with lasers pointing below and measuring
downwards. As the lasers hit the ground, the beams are reflected back up to the
plane so the plane can take
at a rate of about 2 million measurements per second! Unfortunately, vegetation
and water are the ‘natural enemies’ of LiDAR, so it can’t be used everywhere.
Over time, their teams have learnt that not every point is required, nor is
every point reliable…and unfortunately it isn’t always possible to pick the
reliable points by inspection.
LAS files (which have evolved from LiDAR) with categories, which are generated
when reflections bounce off e.g. leaves and trees, leading to greater
ability to filter out extraneous information, determine roof heights,
interpolate floor levels, etc. LAS files are very useful in particular
circumstances, and are included (with accompanying macros) in a number of BCC
The new ‘Point Cloud Surface
Thinning’ option in 12d Model 14 – a very neat function allowing draping of
strings through point clouds. This means points can be concentrated where
changes in grade occur, leading to a reduction in ALS points. The result is
better-looking contours which are closer to the original…at 12% of the size of
the original dataset.
UAV LiDAR using drones – this can be great for working in what would otherwise
be very dangerous areas.
Mobile Laser Scanning – this is more accurate and less expensive than LiDAR, but
also more difficult to control.
UAV Photogrammetric Point Clouds – this method is quick and inexpensive, but
again there are issues with control.
Terrestrial Laser Scanning – BCC had experience with this years ago, for bridge
scans. Using this method, small amounts of important information can safely be
Point cloud functionality in 12d Model
Peter said there is definitely value in point clouds, but they’re not yet civil
design ready, at least not universally. 12d Model manages point clouds well,
though – it will read them in with ease.
12d Model will import common formats of point cloud, convert between formats,
and perform projection transformations. It uses a ‘String_cloud’ element. In 12d
Model 14, these processes have been improved even
further – there is now capability to import multiple files, selected in
Perspective view (which has also been made more responsive and reliable).
Threaded views have also been added.
also outlined some of his favourite point cloud functionality in 12d Model –
including manipulating categories, deleting/undeleting, draping against point
clouds, drawing flags, limiting clouds, pinning clouds, and of course the
aforementioned Point Cloud Thinning.
Point cloud information is being used and shows promise as being a viable option
for BCC. This has been an ongoing journey over several years that started with
Aerial Laser Scanning and has progressed to the extraction of modelled ‘survey’
data from point clouds.
What they’ve learnt at BCC
Overall, point clouds are an efficient and practical way of collecting a
dataset. It is important to remember that not all the points are needed, and
that not all clouds are the same. Also, file extensions are not a reliable
indicator of contents – there are standards in existence, but they are not
always followed. Peter also cautioned against such marketing claims as ‘Scan to
BIM capability’ as they are not always what they seem.
Some of the point cloud outputs include a full point cloud (which is a good
record of what was there), extracted objects, vectors and points, surfaces
(TINs), and viewers. These can be used in such areas as geospatial, forensics,
Where to now for BCC and point clouds?
As they’ve now reached such a level of success with LiDAR point clouds, they’re
now looking at scanning drainage chambers, scanning buildings, and data
extraction and modelling (including vectors, trimeshes, and pipes). Peter showed
examples of terrestrial laser scanning they’ve done (in particular with
manholes). He has been investigating ways to utilise point clouds, including a
macro (within 12d Model) to slice them, meaning he could extract a trimesh out
of a point cloud to reduce it to a manageable number of points. By colouring the
trimesh, surrounding spots have been made visible, and the clouds have become
Download this Case Study as a PDF
valuable in his day-to-day work. By
combining an image and a point cloud on some other projects, further usefulness
has been discovered.
BCC has been
developing a specification for the extraction of trimeshes from point clouds, as
well as mapping files and 12d Field codes. They have utilised DTM auditing
routines for trimeshes. Recently they purchased a BLK 360 scanner, and they are
working on developing in-house skills to take their use of point clouds even
In essence, keeping full point
clouds is a good way of maintaining an accurate record for future reference, and
with some ingenuity, their day-to-day usefulness can be harnessed on some