If you are working with any type of point cloud data, the Global Mapper Lidar Module is a powerful, must-have add-on to the desktop application. One of the standout features of the Module is its ability to automatically identify and apply the appropriate ASPRS classification to each point with a few clicks. This blog will walk through the steps required to automatically classify a point cloud.
Global Mapper’s Lidar auto-classification tools provide the means to identify ground, buildings, utility lines and poles, vegetation, and noise points within an unclassified point cloud. Each of the classification processes requires the presence of ground points in the point cloud so this is a good place to start. If necessary, noise classification can be used to automatically identify any points that are beyond the expected elevation range when compared to those in close proximity. This cleanup tool is used to remove obvious anomalies in the data. At this stage, buildings and trees can be classified and if the point cloud is of sufficient density, there are even tools to classify above-ground utility lines and poles.
When you begin the auto-classification process and load your point cloud into the software, it is important to know that Global Mapper has the ability to display points in several different ways including by RGB value (if present), intensity, and classification. For this process, we will color the Lidar by classification. If your point cloud has never been classified, it will look similar to this:
After the data is loaded, you are ready to classify ground points. To do this, locate the Auto-Classify Ground Points button in the toolbar. This tool brings up the Automatic Classification of Ground Points settings window. These values will need to be adjusted based on the local terrain, the range of elevation values in the data set, user-defined preferences for filtering points prior to auto-classification, or known features in the landscape. This will help to optimize the output. When you have applied the necessary settings, click the OK button to initiate the process.
If necessary, your next step will be to click the Auto-Classify Noise Points button. Identifying previously unclassified noise points will clean up the point cloud and improve further classification results.
At this stage, the non-ground points or points representing buildings and vegetation, are ready to be identified and classified. In the Lidar module, buildings and vegetation are classified using the same algorithm, and the dialog box can be accessed using the Auto-classify Buildings and Vegetation button. The parameters required in the classification process describe the expected structure of buildings and trees within the point cloud. These values can be adjusted to account for the characteristics of your specific point cloud.
The Auto-Classify Powerline and Pole points button can automatically detect above-ground cables, and/or pole-like objects, such as utility poles, in high-density Lidar data with at least 20 points /m2. This density is typical of terrestrial Lidar and mobile Lidar point clouds. While synthetic Lidar (photogenerated Lidar) may also have this density, it does not typically have the reconstruction detail to precisely identify power lines or pole-like objects. Similar to the other classification tools, this process looks for structures resembling powerlines or poles based on user settings.
After you have classified your point cloud, you can begin analyzing the data further. This may involve creating a terrain model or extracting vector features from the classified point cloud.
Keep an eye out for our upcoming blog, focused on the lidar QC process!
The What’s New list in Global Mapper 20 reflects the increasing importance of 3D data visualization and processing, with numerous new tools for working with point clouds, 3D meshes, 3D vector features, and terrain models. In the latest Global Mapper webinar, we showcase some of the highlights of this release.
Among the specific topics covered in the webinar are:
If you are like most people, it’s unlikely that you take the time to read the plethora of dialog boxes that appear when installing software but if you did, you might actually learn some interesting details about the application. In the case of Global Mapper, one of the windows that beckons for your attention is the “What’s New…” list. While we understand the eagerness of most users to repeatedly click the Next button and finish the installation process so they can “play” with their new toy, it might be worth pausing on this one for just a moment.
Blue Marble’s development process requires each new tool, functional upgrade, bug fix, and performance improvement to be meticulously documented and archived. What you are presented within the “What’s New …” list is an abbreviated version of this archive. In a sense, the list offers a summary report of what the development staff has been working on over the preceding weeks and months. It can make for some interesting reading.
For the soon-to-be-released Global Mapper version 20, there are more than 200 individual changes that have been noted. Given the dynamic nature of the development process, this number will likely increase by the actual date of release.
For those of you who do not have the time or the wherewithal to peruse the entire list, what follows, in no particular order, is a summary of five of the most significant new features that you will find in Global Mapper 20.
1) Improvements to the Map Layout function
One of the surprising findings from last year’s Global Mapper user survey was the importance of map printing. For years, the prevailing opinion has been that printed maps would eventually bite the proverbial dust, but this has not been the case. Global Mapper’s Map Layout functionality was completely redesigned a couple of years ago and it has been undergoing continual improvements ever since. For this release we have introduced a new tool for creating a map book or atlas from selected features; a new option to filter the legend by layer; and a custom macro function that allows you to create title blocks with name, company, etc. Suffice to say, if your workflow requires the printing of maps, Global Mapper 20 has all the tools you need.
2) Support for Windows Tablets with improved touchscreen functionality
While Global Mapper has always been supported on Windows-based touchscreen devices, certain actions and UI procedures have been difficult. In version 20, there have been significant improvements that allow a wider range of actions to be controlled with your fingers. Pinching to zoom the map is now supported as well as swiping with two fingers to pan the map in both the 2D and 3D views. Previous enhancements to support touchscreen interaction include, touching the screen to activate contextual menus and tapping on the screen with any of the digitizing tools enabled to place points or vertices.
3) Ability to create a point cloud or flattened orthoimage from a 3D mesh or model
Creating a point cloud, similar in structure to LiDAR data, from an existing 3D model or mesh may seem like an inverted procedure. It is the reverse of what would be considered a normal workflow. It does, however, open up a number of interesting 3D analysis workflows, in which the source data is an existing 3D mesh. For instance, the point cloud created from the model can be readily classified, edited, and filtered using Global Mapper’s LiDAR processing tools, and points representing ground can be used to create a DTM. Version 20 of Global Mapper not only offers this new point cloud creation tool but it also offers the option to create a flattened orthoimage derived from the colors in the mesh.
4) Speed improvements when loading large vector files
Citing any type of performance improvement as a new version highlight is often perceived as subjective and difficult to quantify or validate. In the case of Global Mapper 20, the improved speed when working with larger vector files is tangible. During our internal testing, the load time for a specific large shapefile was measured at just over four minutes in version 19 of Global Mapper. In version 20, on the same multi-core machine, the load time was shaved to 2.5 seconds. That’s almost 100 times faster. Improvements have also been made to the rendering of large vector files in the 3D View.
5) Eyedropper tool for accurate color selection
Perhaps not a major functional upgrade, however, when considered in the context of one of the author’s favorite Global Mapper tools, it is a godsend. The tool in question is a feature informally referred to as “Raster Vectorization” or, to give its proper name, “Create Area Features from Equal Values”. The premise is simple: By identifying a specific color in an image, you can create polygons that enclose the extent of the pixels of that color or you can expand the tolerance to accommodate similar colors. Previously, fine-tuning the color selection involved manually entering the required RGB values. In version 20, there now is a color picker option, with which you simply click the section of the raster image that you want to extract. This color picker is also available when choosing a transparent color for a raster layer.
And a couple of bonus highlights for LiDAR Module users:
Tool for creating a 3D model or mesh from selected LiDAR points
The underlying technology that enables the creation of an orthoimage was incorporated into Global Mapper within the Pixels to Points tool, introduced in the LiDAR Module in version 19. As a byproduct of the photogrammetric 3D point cloud generation process, there is also an option to generate a flattened raster representation of the area in question. Previously, the only way to create either of these data outputs was from drone images. With version 20 of the LiDAR Module, there is now an option to create a mesh or orthoimage from selected points in an existing LiDAR file or point cloud.
Option to spatially thin a point cloud
The LiDAR Module offers an extensive array of point cloud filtering and editing tools. Among the options are: deleting selected points, geographically cropping a point cloud, removal of noise points, manual or automatic reclassification of points, and horizontal or vertical shifting of the point cloud layer. Added to this list in version 20 is a new function to spatially thin a LiDAR layer. This tool allows the user to specify a target resolution for the point cloud which eliminates redundancy, reduces file size, and improves performance.
Version 20 Coming in Mid September
Global Mapper 20 is scheduled for release in the second half of September 2018. Check your inbox or visit bluemarblegeo.com to find out when it is available for download. As always, you can activate a free two-week trial and if you have time, check out the full What’s New list to see what improvements have been made to your favorite Global Mapper tools.
Product News, User Stories, Events, and a Chance to Win a Copy of Global Mapper Every Month
For many, summer is a time for relaxing, for taking your foot off the gas, for being lazy. Not at Blue Marble. We are busy preparing for the next major release of Global Mapper in just over a month, planning our hectic autumn travel schedule, and making the final preparations for our 25th anniversary user conference here in Maine. In this edition of Blue Marble Monthly we formally invite you to join us at BMUC. We also hear from Sam Knight about becoming a licensed drone pilot; we discuss the differences between LiDAR and PhoDAR; and we challenge your geographic prowess in the Where in the World Geo-Challenge.
We hereby cordially invite you to Blue Marble’s home state for our User Conference (BMUC), as we continue to celebrate our 25th birthday. Not only will you have a chance to meet other users and learn about the latest software developments, but you’ll also hear from some interesting presenters including Ron Chapple who will be speaking about his work in the Pulitzer Prize-winning project, “The Wall”.
Ready for the kids to go back to school? Sorry, we can’t help you with that, but we recently sent our own Sam Knight back to school to learn what it takes to become a licensed drone operator. As we continue to develop tools for the UAV industry, it is essential that we have the first-hand knowledge of what is required. For Sam, this was a journey into unknown territory.
Blue Marble’s development process has always relied on direct input from users and now you have a chance to be part of that process. Sign up as a beta tester today and we’ll let you know when a beta version of either Global Mapper or Geographic Calculator is available for you to put through its paces.
The Pixels to Points tool has caused quite a stir in the UAV industry. Creating a high-density 3D point cloud from a drone would have been unheard of just a few years ago. While the data may look and feel like traditional LiDAR, there are significant differences between the two formats. In a recent blog post, we outlined some pros and cons of each.
In the latest Global Mapper case study, we hear from Michael Frings, General Manager of MFBI Technologies about how the LiDAR Module’s point cloud processing tools played a critical role in planning autobahn truck stops in Germany.
“The fact that the LiDAR Module is so powerful, giving us the ability to handle large point clouds, was the killer argument for us to go with Global Mapper.” – Michael Frings
Simply stated, Global Mapper gives you more functionality for less money. Need proof? Take a look at this short video highlighting some of the terrain processing tools that are available out of the box in Global Mapper. No extensions required.
The geographic sleuths were once again hard at work in July. Most of you were able to identify all five locations in the Where in the World Geo-Challenge. The randomly selected winner of a copy of Global Mapper is Roy Mayo, a land surveyor from Mackay, Mackay, and Peters. If you are one of the handful whose response to the capital city question was, “Haven’t a clue” or words to that effect, check out the correct answers here then click the link below to see if you can do any better in August’s challenge.
The Blue Marble training team will be hitting the road again in October with the next three-day Global Mapper class scheduled for Houston. Typically our Houston classes fill up fast so be sure to sign up as soon as possible to reserve your spot.
“Without a doubt, one of the most informative and enjoyable technical training classes I have ever taken.” – Recent Global Mapper trainee
When we have a new product release like the version 19 of the LiDAR Module that comes with the Pixels to Points™ tool, it’s always exciting to see that feature in action for the first time outside of the Blue Marble office. Our South and Central American reseller Laurent Martin from EngeSat was quick to try the new Pixels to Points tool for himself using drone data collected by his peer Fabricio Pondian.
The new Pixels to Points tool uses the principles of photogrammetry, generating high-density point clouds from overlapping images. It’s a functionality that makes the LiDAR Module a must-have addition to the already powerful Global Mapper, especially for UAV experts.
Below, screenshots captured by Laurent illustrate the simple step-by-step process of creating a point cloud using the Pixels to Points tool and some basic point cloud editing using other LiDAR Module tools.
1. Loading drone images into the LiDAR Module
2. Calculating the point cloud from loaded images
3. Viewing the generated point cloud
4. Classifying the point cloud
5. Creating an elevation grid and contours from the point cloud
A quick and easy process
In just a few steps, Laurent was able to create a high-density point cloud from 192 images, reclassify the points, and create a Digital Terrain Model. It’s a prime example of how easy version 19 of the LiDAR Module and the new Pixels to Points tool are to use. Check out EngeSat’s full article on the release of LiDAR Module.
In my first couple of weeks as graphic designer at Blue Marble Geographics in 2016, I heard my coworkers use an unfamiliar term in our marketing meetings. They said things like: “do we have bee-muck speakers yet?”; or “when is the bee-muck e-mail going out?”; or “the bee-muck numbers are looking good so far.”
What the heck is a “bee-muck”?!
I figured it was one of dozens of conferences that Blue Marble attends each year, like AUVSI or InterGeo, and not a term used to describe mud on a yellow and black insect pollinator. “Bee-muck” is actually how the Blue Marble team pronounces the acronym BMUC for Blue Marble User Conference, and BMUC is not just another event the company attends. It’s a series of conferences organized by Blue Marble in cities around North America (and sometimes the world) to show appreciation for the users of Blue Marble software. The one-day conferences offer users a chance to chat face-to-face with Blue Marble team members, to hear success stories from GIS peers, and to share a meal with everyone. I admit, I was skeptical when I heard the “share a meal” part. But when Blue Marble hosted a BMUC in Maine, I had the opportunity to take part in the rich experience the conferences actually have to offer.
Product News that Fosters a Collaborative Culture
At every BMUC, Blue Marble software specialists give talks on the latest product news. During the presentations at the Maine conference, I noticed one phrase that prefaced most of the announcements about new software developments — “We received requests for this feature.”
Global Mapper and Geographic Calculator have evolved into the cutting edge software they are today because of user feedback. Whether a user emails, calls, sends a Facebook message, or speaks to a staff member at a BMUC or other conference, the team at Blue Marble hears and considers what that user has to say. A couple of examples of user-requested features that were highlighted at the Maine BMUC were Global Mapper’s advanced attribute editor, which allows for streamlined editing of data assigned to map features; and the real-time hillshading feature, which allows for dynamic positioning of a light source by clicking and dragging a sun icon.
When asked about what new features of Global Mapper v19 came from user requests, Product Manager Sam Knight began listing them off:
The new attribute editor function
Playing multiple videos attached to a feature
The dynamic hillshading control
All the new raster band math formulae, which include Normalized Difference Snow Index (NDSI) and Advanced Vegetation Index (AVI)
Drag and drop docking for the 3D viewer and path profile
Exporting/importing flythrough paths
After giving this handful of examples, he stopped himself and said, “Actually, literally every significant new feature is a user request.”
The point I’m trying to make is that the product news shared at BMUCs not only keeps users in the loop, but it also fosters the collaborative culture that makes Blue Marble software great. It lets users know that they have a hand in improving these already powerful tools.
Peer-to-Peer Learning in the GIS Community
There are at least two guest speakers at every BMUC, who share their real-life experiences using Blue Marble products. These professionals come from a variety of GIS backgrounds — from oil and gas to filmmaking; from city planning to conservation. While members of the Blue Marble team bring their software expertise to the BMUC agenda, the stories from others in the GIS community add valuable outside perspectives.
At the Maine BMUC, attendees heard from GIS Specialist Thea Youngs, who uses Global Mapper for Portland city projects. She explained how the software fits in her workflow, and how fast it is to view and select an area of interest from a large point cloud. “Global Mapper helps with making LiDAR data play better with drafting software.” She also commended Global Mapper for its extensive list of supported file formats, since her work sometimes deals with older and less common formats.
Attendees also heard from GIS Specialist Alex Gray of GEI Consultants Inc., whose presentation focused on a hydrology analysis for which he created digital terrain models from a combination of LiDAR and sonar data in Global Mapper.
While both speakers use Global Mapper and the LiDAR Module for their powerful point cloud processing functionality, both work with very different workflows and could provide unique ideas on how to use the software. The presentations, as well as the variety of occupations in the BMUC audience, exemplified how versatile Global Mapper is and how BMUCs are a great place to share tips on how to use the software.
Let’s Call it Lunch, not “Networking”
It’s probably safe to say that the word “lunch” elicits a positive reaction from more people than the word “networking”. I mean, who can’t bond over a good sandwich?
During lunch at the Maine BMUC, attendees had the opportunity to share their own stories, ask more questions, discuss projects with their peers, and to make connections in their local GIS community. I was able to hear from attendees about what developments they’d like to see from Blue Marble in the near future, like the ability to create point clouds from drone imagery, which is actually something that Blue Marble is currently testing.
Other than providing lunch, Blue Marble also offers opportunities to win prizes such as T-shirts and a license of the latest version of Global Mapper. At the Maine BMUC, this opportunity came in the form of a “Name That Country” game, in which attendees had to identify countries from a series of slides.
An Affordable and Rich GIS Experience
After the conference, two thoughts struck me as I drank a beer with my co-workers and BMUC attendees who were able to join us for happy hour. My first thought: How cool is it that this small company can serve customers all over the world and still have intimate events like BMUCs? Second: BMUCs truly embody the user-focused mission of Blue Marble.
They are an affordable opportunity (only $25 to register) to gain insights from company experts and other GIS professionals; to meet new people in the GIS community; to win a copy of the latest version of Global Mapper; to have an opinion about a Blue Marble software and to have it heard; and did I mention lunch?
As I write this entry, the Blue Marble team is planning its BMUC 2018 schedule. Drop us a line at email@example.com if you’d like to see this experience come to your neck of the woods, and keep an eye on the BMUC page to find out where we will be next.
There’s an abundance of knowledge to be shared in the GIS and Blue Marble community, and BMUC is a tap on the barrel. Cheers!
Chelsea Ellis is Graphics and Content Coordinator at Blue Marble Geographics. Her responsibilities range from creating the new button graphics for the redesigned interface of Global Mapper 18 to editing promotional videos; from designing print marketing material to scheduling social media posts. Prior to joining the Blue Marble team, Ellis worked in graphic design at Maine newspapers, and as a freelance photographer.
The availability of LiDAR data is expanding at a rate that is out-pacing the requisite knowledge and skills needed to effectively utilize the data. Sounds like a cart-before-the-horse analogy, to coin an idiom from a bygone era.
This conundrum first came to our attention a couple of years ago when, during a roundtable discussion at a GIS forum in one of our neighboring New England states, a local government official excitedly announced that her town had just received LiDAR (or leader, to use her exact pronunciation) from the state. She went on to confide that she wasn’t entirely sure what LiDAR was but evidently that did not dampen her excitement. Remarkably, several other forum delegates jumped on the bandwagon, to use another obsolete transportation-based analogy, and shared their enthusiasm at having received data for their town while eagerly awaiting instructions from the same state agency on what to do next.
In the months that followed, it became clear that LiDAR illiteracy is not unique to small-town New England. Many GIS agencies and departments in other states, provinces, and regions throughout the world, recognizing the increased accessibility of point cloud collection technology, have proactively embarked on massive data collection projects. As a means to justify the expense of these projects, the agencies will often provide the fruits of their endeavor to eager and yet uninformed constituents and office bearers.
The aforementioned municipal officials were certainly justified in their excitement; LiDAR data is contributing to a fundamental change in how we perceive our world. Traditional mapping practices have considered the planet from an inherently unrealistic, top-down perspective. With the emergence of 3D data formats, we are now able to develop a more realistic view allowing us to interact with our data in an immersive environment and providing the impetus for the development of new cartographic and analysis techniques.
What is LiDAR?
Let’s make one thing clear, in most circumstances, LiDAR data is not a product but a raw material. It is not an end in and of itself but rather a means to an end. A commodity, if you will. Before exploring some examples of the products that can be created from LiDAR, let’s put the brakes on (yes I know, another transportation metaphor) and consider the basic structure and characteristics of LiDAR data.
Natively, LiDAR (an acronym of Light Detection And Ranging) is a vector data format, or more specifically, it is a 3D point vector format. Each LiDAR file or dataset usually contains millions, or sometimes even billions of closely spaced, randomly distributed points, with the closeness of the spacing dependent on how the data was acquired. Most publicly available LiDAR data has been collected on an airborne platform using laser transmission and receiving technology in tandem with precise position and navigation systems. Each point is attributed with an X, Y, and Z value derived from the calculated time difference between the transmission and reception of a reflected laser pulse. An aircraft flying lower and slower will create a point cloud with more closely spaced points than one flying faster at a higher altitude. Depending on how the data was collected and/or processed, additional attributes might include, a color value, reflection intensity, and the number of returns per pulse, all of which can be visualized and analyzed.
What Can You Do With LiDAR Data?
Fully utilizing LiDAR usually involves some sort of transformation process. This transformation might involve the creation of a 3D raster surface, often referred to as a Digital Elevation Model (DEM), or it might entail the automatic creation or extraction of 3D vector objects derived from the geometric patterns in an array of points. Both of these procedures will be described in more detail later. It is also possible to derive meaningful information by simply changing how the point cloud is represented. The point display can show the distribution of the different surface-type classifications; the elevation of each point above ground; variations in the density of the points; and many other characteristics.
Editing and Filtering LiDAR Data
Almost without exception, LiDAR data files will include many more points than are needed for a particular project or task. In Global Mapper, there are numerous filtering options for removing points that are outside of the geographic extent of a project area; that are considered erroneous or noise points; or that are attributed with a surface-type classification that is not required. Before embarking on any point cloud filtering procedure, it is a good idea to scrutinize the metadata for the layer. This statistical summary will provide the necessary information about the characteristics of the point cloud to allow more informed decision-making in the filtering process.
Improving the Quality of LiDAR Data
As well as removing unrequired points, Global Mapper includes several built-in procedures for recovering points that would otherwise be discarded. The most common and most powerful application of this automatic classification process is the detection and subsequent reclassification of ground points among those that are unclassified. This procedure increases the relative percentage of points that can ultimately be employed in the creation of a DEM resulting in a higher-resolution terrain model.
Other automatic classification procedures include the detection and reclassification of buildings, trees, and utility cables, which is the first step in the feature extraction process.
Creating a Digital Elevation Model
In order to perform virtually all 3D analysis procedures, a LiDAR point cloud will need to be gridded. In this context, gridding describes the process whereby the value associated with each point in an array (typically an elevation value) is used as the basis for generating a solid 3D model. This model can either represent bare earth (a Digital Terrain Model) or an above-ground surface such as a forest canopy (a Digital Surface Model). The distinction between the two is derived from the filtering and selection of the points that are used to generate the surface.
For most LiDAR users, the primary objective is the generation of a DTM, which is the platform for a wide variety of terrain analysis workflows. Without straying too far off the prescribed path (yet another transportation reference), Global Mapper offers an extensive collection of terrain analysis tools, including volume calculation; cut and fill optimization; contour generation; watershed delineation; and line of sight analysis.
The increased availability of higher density point cloud data has paved the way (OK, I’ll stop now) for a new LiDAR processing discipline. The analysis of patterns in the geometric structure of adjacent points can result in the delineation of building models, represented as three-dimensional polygons; power lines or above-ground utility cables, represented as three-dimensional lines; or tree points, derived from the collective structure of points classified as high vegetation. Global Mapper’s vector extraction tools also include a custom extraction option where 3D lines and polygons can be generated by following a series of profile views that are perpendicular to a predefined path. This tool can be used to create a precise three-dimensional model of any elongated structure, such as a curb along the edge of a street.
The impetus behind this article was to address some typical applications for LiDAR data without delving too deeply into the technical considerations or step-by-step instructions. That said, if you are sufficiently intrigued and are ready to move to the next level, you will need software in order to utilize your LiDAR data. Global Mapper has supported the import and display of LiDAR data since before the format became widely available and each subsequent release has introduced new functionality for effectively managing and processing the data.
Several years ago, Blue Marble introduced an optional module for Global Mapper to address the demand for ever more powerful LiDAR processing tools. If you are interested in the aforementioned automatic reclassification and extraction tools, you should certainly give the LiDAR Module a try.
If you are new to Global Mapper, both the base software and the LiDAR Module can be evaluated free of charge for two weeks.
Webinar Series: LiDAR Processing in Global Mapper
We are releasing a series of short webcasts exploring the use of LiDAR data in Global Mapper and the accompanying LiDAR Module. Beginning with an introduction to the structure and characteristics of LiDAR data, each video will be approximately 20-minutes in length and will cover a specific theme or topic. To receive notification of the availability of these and other Blue Marble video presentations, be sure to subscribe to our YouTube channel or follow us on Twitter.
This is the first video of the LiDAR Processing in Global Mapper series:
David McKittrick is a Senior Application Specialist at Blue Marble Geographics in Hallowell, Maine. A graduate of the University of Ulster in Northern Ireland, McKittrick has spent over 25 years in the field of GIS and mapping, focusing on the application and implementation spatial technology. McKittrick has designed and delivered hundreds of GIS training classes, seminars, and presentations and has authored dozens of articles and papers for a variety industry and trade publications.