Intergraph Announces Point Cloud support Coming in ERDAS IMAGINE 2012

The announcement below is the fruit of software development work being done in Atlanta, Georgia USA; Pasadena, California USA; and Singapore as well as the press release written in Atlanta. The Intergraph corporate headquarters are in Huntsville.

Steve du Plessis and I will begin a series webinars on this topic later this month.

The reason we use the term Point Cloud rather than LiDAR, point cloud covers more data sources than LiDAR. LiDAR is but one data source.

The announcement is as follows: 

Intergraph® Highlights Advanced Point Cloud Capabilities at Hexagon 2012

New ERDAS IMAGINE® Features Enable You to Better Understand Your LiDAR Data

HUNTSVILLE, Ala., June 6, 2012 – At the Hexagon 2012 conference, Intergraph® is demonstrating a new technology that enables you to fully leverage the wealth of information in point cloud data. The centerpiece of the new functionality is the augmented viewing capability embedded in ERDAS IMAGINE®, which allows users to simultaneously view LiDAR spatially linked in 2D, 3D and as a user-specified profile that can reveal cross sections of the point cloud.

“Intergraph’s new functionality truly unlocks the potential of LiDAR, taking full advantage of its rich three-dimensional content,” said Steve du Plessis, Global Product Line Executive – Remote Sensing, Intergraph. “You can open up these dense point clouds, see inside them and break them apart to reveal the information they contain to gain a new perspective of the world.”

Within the three new views, ERDAS IMAGINE provides a range of options that make it easy to understand and extract the information contained in the point cloud. Different filtering options allow you to view the points in dozens of permutations. For example, you may only want to see first-return points classified as vegetation. To improve interpretability, flexible colorization settings offer the ability to view by elevation, return, classification, file, intensity or the RGB encoding of each point which provides a lifelike, three-dimensional color view of a point cloud. Additionally, you can view the point cloud draped over your 2D imagery, thereby obtaining a better understanding of the above-ground features portrayed by the points.

The profile view provides unique capabilities for analyzing point clouds. While the standard profile view is defined by a user-specified box drawn over the 2D view of the point cloud, you can also use a polyline vector to obtain a profile view of a longer strip within the cloud. ERDAS IMAGINE can then automatically roam at a user-specified speed along this long profile view. These features are especially useful in the utilities market, where they can be used to inspect power line corridors for encroaching vegetation or other line issues. As problems are visually detected, you can pause, make measurements, record the position and add notes. ERDAS IMAGINE can then export this information to a spreadsheet that can be given to field crews who maintain the corridors.

ERDAS IMAGINE’s new point cloud technology also offers a set of tools to classify, RGB encode, subset and filter your point data. The classification tool will enable you to specify criteria for automated point classification. Users can then leverage the editing tools within the 2D and profile views to refine the results. For example, you can delete, reclassify, bias or set a constant elevation on selected points with the security of multiple-step undo and redo capabilities. In addition to thorough views of the point clouds themselves, ERDAS IMAGINE provides comprehensive views and editing of the associated metadata. You can batch and distribute all these functions for faster processing, which is especially helpful since many users opt to create smaller tiles from large LAS files.

“Intergraph is in a unique position to provide the leading point cloud solution on the market,” continued du Plessis. “As part of Hexagon, our portfolio includes in-house airborne and terrestrial LiDAR hardware technology from our sister division Hexagon Geosystems, powerful GIS analytics from GeoMedia®, the world’s leading remote sensing capabilities in ERDAS IMAGINE and LiDAR data management and serving capabilities in ERDAS APOLLO. In addition, Intergraph’s vertical market approach offers extensive domain expertize in utilities, transportation, government and security. Together, not only will our point cloud technology strengthen any organization’s LiDAR-handling capabilities, but also its user-centric implementation streamlines workflows so users can quickly and easily obtain the most from point clouds and maximize the return on your LiDAR investment.”

To learn more about the Intergraph geospatial product portfolio, please visit http://www.intergraph.com/geospatial/products

ERDAS IMAGINE 2012 is looking really good.

This release is going to be hot. What’s going to be in it?

The upgraded Spatial Modeler is more than an upgrade. This is more than an update of Model Maker that sits on top of the Spatial Modeler Language. All the Modeler Maker capabilities that Esri copied to create Model Builder are there, plus the things customers have demanded.

• Faster file to file processing
• On-the-fly raster processing (lessons learned from ER Mapper) 
• On-the-fly vector processing (lessons learned from GeoMedia) 
• Replacement of Model Maker User Interface 
• Python Scripting 

But this is the beginning. Spatial Modeler is being designed with 64-bit processing as well as sharing tools with GeoMedia in mind. The architecture has been designed in a manner that will allow features and functions to be added in service packs.

The Python Scripting is very powerful. Customers will be able to connect other software applications with Spatial Modeler as part of their data processing work-flows. ERDAS IMAGINE's Spatial Modeler can act as a agnostic geoprocessing hub.

There is more….

• Point Cloud (LAS, MrSID) visualization in 2D and 3D, profiles, measuring, point editing, RGB encoding… I am working with Steve du Plessis to put together a Webinar on point clouds.
• 16-bit ECW, and ECW is faster… not just a little faster, but must faster and scalable.
• Better and faster support for JPEG2000 data. 
• LPS is fully Ribbonized.
• New Segmentation algorithm that customers are saying  is the best they have seen to date. 
• Improved ER Mapper Algorithm capabilities. 
• GeoMedia Vector and GRID capabilities. The GeoMedia Buffer in Spatial Modeler is real time. You can test your buffer processes in a trial and error method in the viewer and then write to file (if you want to). 
• Faster edge detection in MosaicPro.
• New real-time spectral indices tool. 
• Radar analyst work-flow tools in the ribbon, including ship tracking capabilities. 

There are a lot of moving pieces, and there are more items coming that cannot listed at this time. I have to wait a little longer on some.

Last year at Hexagon 2011 I discussed that the wall between raster and vector was coming down. It is more than that, mush more.... raster, vector, point clouds, imagery, photogrammetry, radargrammetry, and more all in one software.

I am again working on a research love of mine, change detection. We have the algorithms and processing performance we need to make high resolution change detection work for the whole geospatial community, not just the expert. This is expected post 2012. Exciting times are here.

Capitalizing on Local Government’s Investment in LiDAR

Jarlath O'Neil-Dunne wrote an article in LiDAR News titled Capitalizing on Local Government’s Investment in LiDAR. Jarlath writes, "In my work using LiDAR data sourced from local government to map land cover in urbanized areas, I find that even in major cities with well-established GIS departments, the point cloud has never been looked at and the term “LiDAR” is typically taken to mean a high-resolution bare earth Digital Elevation Model (DEM)."

I agree with this statement.

Also, the GIS mover and shakers within the State of Georgia are trying to get a elevation project off the ground. Actually, this effort began over a decade ago when I was at the Georgia Tech Center for GIS and a active member of GISCC. (The lesson here, be persistent.)

Because the State of Georgia has 159 counties, it is hard to get the various political powers to agree on spending the money for this project. There has been and will continue to be many surprise floods in Georgia until the state's elevation is mapped correctly. What is sad, nearby states with less financial resources mapped their state's elevation using Lidar many years ago. Thus they are far more prepared for floods than Georgia.

Is political pride getting in the way, or is it lack of education? The Carl Vinson Institute of Government at University of Georgia is trying to overcome the education issue. The Vinson Institute's Office of Information Technology Outreach Services (ITOS) created a Lidar 101 education video to help legislators and other decision makers understand Lidar. It is 13 minutes and 13 seconds long.

Other Lidar post on this blog...

Expanding Lidar Value in Local Governments

I often hear local governments who are flying Lidar to establish the terrain component of their aerial ortho projects. These local governments request a copy of the ‘raw’ Lidar data. What does ‘raw’ mean?

Typically, what the local government really wants is not the ‘raw’ Lidar data, but all Lidar returns further down the processing line. Commercial tools to process ‘raw’ Lidar imagery are not easy to use, nor are they currently cost effective. ERDAS, the inventor of commercial remote sensing, has historically been the company to introduce cost-effective remote sensing tools into the market-place. (I see Lidar as a remote sensing tool that heretofore has been used most successfully by photogrammetrists.)

It is understandable that local governments want more than detailed terrain model from their Lidar collection. Heretofore, Lidar collections have centered on elevation, but there is much more value available in Lidar data than only an elevation model. It is my belief, to use Lidar only as an elevation source, is like using imagery only as a backdrop to a GIS vector dataset; valuable, but very wasteful of the tax payer’s money.

Local governments need more value from their Lidar collections than just elevation, but that value is not easily captured in the ‘raw’ data. What Lidar data do local governments need to request? They need Lidar data that has been bore-sighted. Bore-sighting removes the small imprecision found in the GPS and IMU. These errors can be quite significant errors at a flying height of 5,000 feet (1500m).

After bore-sighting, the data are edited to define ground points and other features. This is a needed step to prepare the point cloud for terrain purposes. Yet, the Editing process can introduce very valuable information. Here is where vendor can classify the points into categories. The philosophy that points should be flagged with a classification, rather than be deleted from the dataset, emerged during the development of the LAS data format standard.

Of the several classification categories that can be defined in a LAS file, the categories local governments may wish to take advantage are: Ground; Low Vegetation; Medium Vegetation; High Vegetation; Building; and Water.

It is my opinion; the local government should obtain the intermediate product at this stage. All returns, bore-sighted and classified, no points added or removed. And, a full QA/QC report. If it were me, I’d ask for the intensity information as well.

The final need, the LAS tiles should each have fully defined horizontal and vertical coordinate systems (as ASPRS suggests). So many times local governments accept LAS tiles that only have the horizontal datum defined. Without knowing the vertical datum, you do not really know the height. Also, putting the vertical datum inside the LAS file rather than on a yellow sticky note on the DVD is far more appropriate. (And what happens when the yellow sticky note looses its sticky?)

Local governments ask, what can I use to work with my Lidar data? I said earlier, “Commercial tools to process ‘raw’ Lidar imagery are not easy to use, nor are they currently cost effective. ERDAS, the inventor of commercial remote sensing, has historically been the company to introduce cost-effective remote sensing tools into the market-place.” Now, ERDAS is presenting tools to convert your Lidar data to raster for further processing.

But why raster?

• Raster conversion of the point cloud can shrink LAS file to a IMG file ¼ the file size of the LAS (you only store x & y values once in the raster UL corner). But that is not the main reason, as I suggest keeping the LAS files in backup for the day when point processing engines are cost effective.
  
• The files being converted into raster allows a visual QA/QC of the data.
  
• Open Lidar collections up to the ERDAS community in a very cost effective manner (no additional costs). Once the data are in raster, the Spatial Modeler, Model Maker, Classification, Expert Classification, and Objective are available to the customer to process the data.