Between the Poles

Oracle Spatial and Graph to support NURBS

At the Oracle Spatial and Graph User Meeting, the folks from Oracle outlined some of the things to expect in the next version of Oracle 12c.  I was very impressed.  All of the below is my interpretation of what will be in Oracle 12c.

Parametric curve support

The really big news for the architecture, engineering and construction community (AEC) who use CAD and BIM applications is that Oracle 12c is expected to support NURBS (non-uniform rational basis spline) a type of parametric curve widely used in the design space.  According the Siva Ravada the support will be very general and will be able to handle different ways of representing NURBS. Up to now the only parametric curve supported by Oracle was circular arcs.

To me it looks like Oracle is taking a major step toward being able to store natively and manipulate (in some cases by stroking) the parametrized curves used by CAD and BIM applications.  There is a lot of CAD and BIM data out there and being able to store it and manipulate it in Oracle Spatial and Graph is going to be a game changer.

Orthorectification

Oracle is providing support for orthorectification embedded directly in the database.  This will have important implications for the industry.   Up to now, you had to pull the image out of where ever it was stored, transfer it over the network to someone's application often from an image processing company to orthorectify it, and then transfer it back to store the image or stream it to the end user.  With 12c you will be able to orthorectify images in the database.  This is in line with Oracle's objective of bringing processing to the data, rather than the data to processing.

Raster algebra

Oracle 12c will also have support for raster algebra, again in the database.  For example, you will be able to average in the database12 months of national temperature data stored in monthly raster files.

GDAL and PDAL support

Oracle supports the open source GDAL raster libraries, the industry standard developed by Frank Warmerdam (now with Google) and used by just about everyone for accessing raster images including ESRI.  PDAL is a similar type of open source library for point clouds developed by Howard Butler and Michael Gerlek.

3D

Oracle supports three types of 3D data.  3D vectors, point clouds and terrain (surfaces).  Oracle 12c will provide full support for 3D geodetic data, lon lat and elevation in meters or feet.

Performance

Oracle has developed a new engine for handling massive point clouds.  Dan Geringer showed impressive results for a 2.8 billion point point cloud (286 gigabyte file). 

Processing vector geospatial data is reported to be 50 to 100 times faster in 12c than in 11g. 

Raster operations have been parallelized which can dramatically reduce the time it takes for these operations.

Engineered Database

Since acquiring Sun, Oracle has become a hardware and software company and is offering integrated hardware and software solutions that offer extremely good performance characteristics.  For example, processing LiDAR data benefits from hardware acceleration on engineered machines such as Exadata boxes.

Bundled data

Oracle is planning to bundle vector data from Nokia (Navteq), TomTom and others.

Oracle Spatial and Graph

The name of the product is changing to Oracle Spatial and Graph partly because it has had graph capabilities (network and RDF semantic) already for several years.  But probably more importantly because the demand for graph capabilities is accelerating, especially RDF semantic graphs for linked data, text mining, and for social media analytics, according to Xavier Lopez.  Even Oracle's NOSQL database (aka BerkeleyDB) is apparently getting graph capabilities.

SPAR 2013: Integrated geospatial, LiDAR and design datasets for large infrastructure construction projects

Kevin Gilson, of the Project Visualization group at Parsons Brinckerhoff (PB), gave an overview of how PB manages 3D+ datasets in support of design and construction for large infrastructure projects such as the San Francisco-Oakland Bay Bridge, the I-95 New Haven Harbour Crossing /Q-Bridge reconstrcution, and the Alaskan Way viaduct project.  He showed how the project visualization team leverages geospatial data, LiDAR data, design data and construction planning data together in large integrated datasets that concurrently support visualization, stakeholder communication, design, construction planning and site logistics.

PB has more than 30 staff dedicated to project visualization.  That included folks who do 3D modeling, design visualization, web design, and programming.  3D technologies include building information modeling (BIM), 3D design, virtual desgin and construction (VDC) and laser scanning (LiDAR).

3D modeling for design and construction

Some of the reasons that designers and construction firms are adopting 3D technology are the serious limitations of 2D sheet sets, still legally required fro s-builting but very unreliable, the design efficiencies of 3D parametric models, and the limitations of siloed project data.  PB has adopted the concept of project information models or PIMs, that integrate information about all aspects of the design and build process and that potentially can flow data through for operations and maintenance.

3D modeling and model-based design are used by PB for design validation, clash detection, and parameteric modeling, civil integration management, 4D modeling (time+3D), 5D (cost+time+3D), and design visualization.  Model-based design involves integrating CAD, GIS, survey, analytics, BIM and associated databases, and 3D visualization typically in a vitual gaming environment.

Construction firms in particular see tremendous advantages in 4D models that integrate design and gespatial data and allow the construction team to virtually build the project so that they can check staging and construction sequencing and site logistics virtually.  5D and higher dimensions allow them to add additional metrics including cost, resources, materials, and equipment.

The benefits that PB realize by this integrated approach based on 3D+ dataest include finding and fixing conflicts between different design groups (HVAC, plumbing, electrical, structural, and so on) during the design phase rather than during construction when clashes are much more expensive to fix.  Another benefit is being able to quantify things using analytics, so  that decisions are data-driven rather than subjective.

A major benefit is less re-work is required reducing the risk of cost and schedule overruns.  A big advantage is improved communication and coordination between all project stakeholders, and especially with non-technical decision makers.  Being able to see photorealistic visualizations of what the project is going to look like makes a huge difference in communicating with politicians and the public.  PB uses gaming technology making it possible to experience a project before a shovel has gone into the ground.  For example, on highway projects, PB's visualization makes it possible to drive the highway and even the detours required during construction in a virtual environment so that the public can experience the changes and be prepared for them before they actually happen.

Another important benefit that Kevin sees from a project approach that includes visualization is that "sexy deliverables" get peoples attention, within the project team as well as with external stakeholders.  Several other speakers at SPAR 2013 also emphasized the importance of the "sexiness" factor.

Laser scanning in construction

Kevin described a number of applications of laser scanning (LiDAR) as part of the 3D constrcution process.  A major application of LiDAR is contruction monitoring, capturing construction progress as well as being able to automate the process of checking for divergence from design when contractors for a variety of reasons don't build what is designed. 

Another important Laser scanning application is accurate and reliable as-builts.  At SPAR 2013, speaker after speaker in different sectors of the construction industry reiterated that current 2D as-builts, still legally required, are unreliable and rarely looked at by anyone post-construction.  Marco Vidali Castillo at ICA which is responsible for the Autopista Urbana Sur project in Mexico City  gave an example of how trying to use 2D as-builts can lead to problems necessitating major re-engineering.  LiDAR scans of a completed project can provide the reliability that 2D as-built sheet sets lack.  On the Autopista Urbana Sur project Marco says that ICA intends to deliver LiDAR scans as well as the legally required 2D as-built sheet sets.

3D modeling and sustainability

There are also benefits from the perspective of sustainability to PBs project approach. Collaboration typically has relied on the exchange of paper documents which on a large project can involve many thousands of paper documents.  Collaborating in a virtual environment can dramatically reduce paper flow while improving the quality of communication.  It can also improve traffic flow and resource management during construction, thereby reducing emissions. A life-cycle approach to data management during design and construction, with data being reused for operations and maintenenace can reduce rework resulting in significant efficiencies.  

Selecting software tools

The PB project visualization team takes a best of breed approach in selecting software for 3D modeling and visualization. An important criterion in selecting tools is interoperability between the different technologies.  Currently the software stack that PB relies on includes

Geospatial

• ESRI
• Global Mapper
• Infraworks (Autodesk Infrastructure Modeler)

CADD

• Microstation InRoads
• AutoCAD/Civil 3D
• Solidworks

Visualization

• 3ds Max
• Sketchup
• Realtime - UDK, Unity

Collaboration/4D

• Navisworks

SPAR 2013: Integrated geospatially-enabled asset management at the Utah Department of Transportation

The Utah Department of Transportation (UDOT) is responsible for about $30 billion in assets including pavement, bridges, signs, culverts and signals.  At SPAR 2013  Stan Burns, Asset Management Director at UDOT gave an overview of a very ambitious program involving inventorying all assets and developing an integrated gespatially-enabled asset management  system. 

UDOT has about 6000 centre-line miles (10 000 km) of highways and has just completed an inventory of the entire system.  The inventory generatd a total of 30 terabytes of data, 6 terabytes of imagery and 24 terabytes of point cloud data captured by LiDAR.

UDOT is in the process of developing applications that are designed to provide a common interface for the dozen or so UDOT groups that provide a variety of services.  One of the most important features of the architecture of the integrated asset management solution that UDOT is developing is that location represents a fundamental way of indexing and integrating disparate data sources.  For example, it makes it possible to see critical maintenenance issues in different layers such as culverts, pavement, and bridges on a common landbase map, so that repairs can be coordinated for all of these assets at the same time. 

A critically important objective is no data duplication by implementing a data management stategy based on data stewardship,  In essence every piece of data has a single owner, which could be a group or department.

Interoperability is a critical issue because UDOT has many different software systems from different vendors including Oracle, Bentley, ESRI, Deighton, Mandli, Virtual Geomatics and others.

But perhaps the most important aspect of this project is the sharing of a common dataset among all the departments of the UDOT.  As Gene Roe of LiDAR News said in another session, sharing of data among different departments of DOTs is not the current situation in many DOTs.

This type of asset management represents a cultural shift for DOTs, because it makes it possible to maintain assets proactively, develop strategic directions, and create wisdom from the huge volume of asset and other data such as historical weather conditions.  For example, it makes it possible to predict future bridge and pavement conditions, so that funding requirements can be projected into the future.

SPAR 2013: Digital highways require integrated engineering and geospatial data

At SPAR 2013 I had the opportunity to hear very forward looking presentations by Ron Singh, Chief of Surveys/Geometronics Manager at the Oregon Department of Transportation.  What Ron sees in the future and what motivates a lot of what Don sees needs to change in the highway construction process is autonomous vehicles, which will provide a major motivation for what Ron refers to as digital highways.

Automation over the last 25 years

If you look at the last 25 years there has been quite a lot of automation in the form of survey automation such as electronic data collection, GPS, and basic 3D laser scanning;  design automation such as computer aided design and drafting, and a bit of construction automation.  The primary focus has been on speeding up the project development process, but the end goal remains  2D paper construction documents.  Some people have been using what is called 2..5 D, a 3D roadbed prism with 2D objects on it.  In Ron's view the current way of designing and building highways has reached the end of it's lifetime and a complete transformation to a new paradigm is required.  The way Ron refers to this is standing the current process on its head and I blogged about it yesterday.  Fundamentally it involves intelligent 3D models replacing the current as-builts and a process that speeds up project development because it leverages existing engineering data rather that requiring a complete resurvey at the beginning of every project..

A new paradigm for intelligent highways

The objective is intelligent highways that will support autonomous and partially autonomous vehicles.  The new paradigm needs to be data-centric and real-time.  It will involve automated construction.   From a data management perspective it will require highway infrastructure lifecycle management, which will involve a very different approach to the survey/design/construct/maintain process that is currently used for highway projects in North America.

First of all, it will involve geospatially enabled 3D digital data. A key requirement is a low distortion geospatial coordinate system that will provide the foundation for geolocatiig all infrastructure including utilities.  It will require interoperability using industry standards for data exchange. Most importantly it will support a construction process that uses post-construction surveys to replace as-built plans with a full 3D engineered model that supports GIS/engineering data integration. 

It will require geospatially-enabled enterprise data management including version control and the ability to search for things geospatially.  It will provide tools for geospatially enabled asset management.  It will provide a framework for developing and maintaining engineering and geospatial data including 3D engineered models as well as scanned data for existiing structures for the entire life cycle of a highway.

Autodesk University 2011

If you are interested in new technological approaches for the challenges facing the utility, municipal government, and other industries, such as smart design, integrated substation design, records management, reducing truck rolls with high resolution imagery, convergence, digital cities, sustainability, open municipal geospatial data, and you would like to share ideas and experiences with other folks in the industry, then you might think about coming to Autodesk University in Las Vegas, November 29 to Dec 1.  

You can access last year's classes at the AU web site.

Point Cloud Shape Extraction for AutoCAD Available Worldwide

I blogged earlier about the Point Cloud Shape Extraction for AutoCAD Plug-in, which is an intelligent point cloud shape extraction solution which allows you to import, load, and extract shape and geometry information from point cloud data in AutoCAD. 

It is now available worldwide for download at the Autodesk Labs site.  If you want to experiment with Shape Extraction for AutoCAD, the Labs site includes some sample point cloud data.

Point Cloud Shape Extraction for AutoCAD

Utilities are increasingly using laser scanning, terrestrial and LiDAR, to scan transmission lines for vegetation management, substations to create 3D models as a starting point for rehabilitation design, and other objects.

There is a new Point Cloud Shape Extraction Plug-in available on the Autodesk Labs site. Shape Extraction is a plug-in for AutoCAD that allows you to extract shape and geometry information from point cloud data in AutoCAD 2011 and AutoCAD 2011-based products.

To do this first import unorganized point cloud data into AutoCAD.  You then have three options for extracting shapes.

• Primitive Shape Extraction - extract primitive shapes such as spherical, cylindrical, conical and toric surfaces or solids.
• Plane Extraction - extract a single plane or automatically extract all planes
• Point Cloud Sectioning - specify a sectioning plane and then fit poly-lines or b-splines to the points on the sectioning plane

More information is available on the Labs blog. There are some examples on Shaan Hurley's site and on Kean Walmsley's blog.  Videos are also available.

AutoCAD Map 3D 2011 Release

AutoCAD Map 3D 2011 has been released worldwide.  Some of the important new capabilities include

Point Clouds

• Import LiDAR data in LAS and ASCII file formats
• Stylize point data
• Filter point data
• Snap to points within the point cloud using standard AutoCAD functions
• Export surfaces as digital elevation models (DEMs)
• Export point cloud layers to LAS, ASCII, and SDF file formats

3D Surfaces

• Generate 3D raster surfaces from point clouds, survey and FDO data sources

New FDO Providers

• ESRI ArcSDE v 9.3.1
• Microsoft SQL Server 2008 service pack 1
• PostGIS 1.3
• SQLite

Workflow Tools

• Connect to any vector data source
• Execute AutoCAD commands

Multi-coordinate system tracking

• Track in multiple coordinate systems through a single interface

Grids and graticules

• Add dynamic grids and graticules to any map