Got a Drone? Now What? — Using Global Mapper with Your UAV

Let’s start with a question. How many of you currently own a Segway? Unless you moonlight as a mall cop or run an urban tour company, you probably decided not to jump on that gyroscopically-controlled bandwagon. If the hype that surrounded the release of this ‘revolutionary technology’ was to be believed, we would long since have abandoned our cars, redesigned our cities, and be living much more fulfilling lives. Alas, the reality has fallen a little short.

The emergence and proliferation of Unmanned Aerial Vehicles (UAVs) or Drones, on the other hand, while not accompanied by a cacophony of hyped-up fanfare, promises to have a much more profound impact on our lives. If current speculation is to be believed, within a few short years, the skies overhead will be swarming with delivery drones, traffic monitoring drones, and even people-moving drones.

For those of us in the mapping industry, this eye-in-the-sky technology effectively addresses one of the perennial challenges that we face: where do we get data, and more specifically, where do we get current data? Traditionally, we have depended on often inadequate and outdated public geospatial data archives or expensive commercial sources. With the advent of readily accessible UAV technology, on-demand data is within anyone’s reach.

The rapid growth of UAV ownership has resulted in an interesting dilemma for some would-be pilots. Having purchased the hardware and collected some data, many are often unclear as to what exactly they can do with it? Over the last couple of years, I have attended several UAV-focused tradeshows and a question that I am often asked is, ‘What can I do with Global Mapper?’ The answer: many things.

Initial Flight Planning

Among the freely available online data services in Global Mapper are high-resolution aerial imagery, Digital Elevation Models (DEMs), aviation charts, and topographic maps.

Before hitting the launch button, it is a good idea to virtually reconnoiter the project area. What possible obstructions are in the vicinity, what are the terrain characteristics, are there any nearby buildings or other facilities that might have overflight restrictions, what is the coverage area? These questions and more can be answered by loading the relevant data into Global Mapper and conducting some rudimentary pre-flight analysis. Among the freely available online data services are high-resolution aerial imagery, Digital Elevation Models (DEMs), aviation charts, and topographic maps. Global Mapper’s drawing tools can be used to delineate the extent of the project site to determine coverage area and to draft an initial flight plan to optimize the data capture process. All of this data can be transferred to an iOS or Android device running Global Mapper Mobile to allow field checking of the flight plan parameters.

Geotagged Image Viewing

Images can be loaded into Global Mapper as picture points creating a geographic photo album. Derived from the coordinate values embedded in the image files, the location at which each photo was taken is represented by a camera icon in the map view.

One of the most basic functions of a UAV is taking photographs and as we will discuss below, with sufficient overlap, these images can be processed into a 3D representation of the local area. Before proceeding with this more advanced functionality, the images themselves can be loaded into Global Mapper as picture points creating a geographic photo album. Derived from the coordinate values embedded in the image files, the location at which each photo was taken is represented by a camera icon in the map view. Using Global Mapper’s Feature Info tool, each photo is displayed using the computer’s default image viewer. Viewed in the 3D Viewer, the camera icons will appear above the terrain or ground providing a precise representation of the drone’s altitude when each image was captured.

3D Reconstruction

The functionality of the Pixels-to-Points tool transforms simple drone-collected image files into a dataset that can be used for countless 3D analysis procedures.

Incorporated into the optional LiDAR Module, beginning with the version 19 release of Global Mapper, the Pixels-to-Points tool is used to analyze an array of overlapping images to create a 3D representation of the environment. This powerful component identifies recurring patterns of pixels within multiple photographs and employs the basic principles of photogrammetry to determine the three-dimensional structure of the corresponding surfaces. While the underlying technology is extremely complex, as is typical in Global Mapper, the user’s experience is very straightforward. Simply load the images, apply the necessary settings for the camera system, add ground control points if available, click the Run button, and wait while it creates a high-density point cloud and, if required, a 3D model or mesh. The functionality of the Pixels-to-Points tool transforms simple drone-collected image files into a dataset that can be used for countless 3D analysis procedures.

Orthoimage Creation

A byproduct of the aforementioned point cloud generation process is the option to create an orthoimage. Defined as a raster layer in which each pixel’s coordinates are geographically correct, the orthoimage is generated by gridding the RGB values in the point cloud. Given its inherent accuracy, this 2D imagery layer can be used for precise measurements or as a base layer for digitizing or drawing operations.

DTM creation and Terrain Analysis

Global Mapper can generate a Digital Terrain Model (DTM) from point cloud data.

As mentioned previously, the Pixels-to-Points-generated point cloud represents the raw material for numerous analysis procedures in Global Mapper. As with any unprocessed dataset, some QA, cleanup, and processing will be required before embarking on any meaningful workflow. Fortunately, the software offers a plethora of editing and filtering options, including noise point removal, spatial cropping, ground point identification, and automatic reclassification. After isolating the points representing bare earth, the gridding tool is employed to create a Digital Terrain Model (DTM), a 3D raster layer that depicts the ground surface. In turn, this terrain layer can be used to create custom contour lines, to calculate volume, to delineate a watershed, to conduct line-of-site analysis, and, if overlaid on a previously created DTM, to identify and measure change over time.

Video Playback

Aside from capturing still images, most UAVs are equipped with the necessary hardware to record video. Beyond simple recreational use, this functionality is useful for building or asset inspection, strategic reconnaissance, forestry inspection, and in countless other situations where a remote perspective is needed. Global Mapper includes an embedded video player that will play this recording while displaying the corresponding position of the UAV in the map window. The determination of position is derived from the per-vertex time stamp recorded in the track file recorded during the flight. After loading this file as a line feature, and associating it with the corresponding video file, the playback is initiated from the Digitizer’s right-click menu.

LiDAR Processing

The Global Mapper LiDAR Module offers a set of tools for identifying, reclassifying, and extracting these features as vector objects.

Not too long ago, it was generally accepted that, due of the size and weight of the required equipment, LiDAR collection could only be carried out using a manned aircraft. This simple fact contributed to the high cost and logistical challenges of the LiDAR collection process. Today, miniaturization of the LiDAR apparatus has reached the point where it is within the payload capacity of many larger drones. Given the limited range of the aircraft, drone-collected LiDAR is only viable for small, localized projects however it does allow frequent re-flying of a project site and is thus ideally suited for change detection. Global Mapper, along with the accompanying LiDAR Module, offers a wide range of tools for processing LiDAR data. As previously mentioned, points can be filtered and edited before creating a surface model for terrain analysis. Compared to photogrammetrically created point cloud data, LiDAR provides a more complete three-dimensional representation of non-ground features such as buildings, powerlines, and trees. The LiDAR Module offers a set of tools for identifying, reclassifying, and extracting these features as vector objects.

Fundamentally, UAVs and maps have much in common. Both are intended to provide a remote, detached perspective of an area of interest and allow us to see spatial distribution and patterns in our data that would not otherwise be detectable. It is understandable, therefore, that one of the primary functions of a drone is to provide data that can be used for creating maps and other spatial datasets. Global Mapper is ideally suited for this type of workflow and it provides an extensive list of tools that can be used by drone operators.


A thirty-year veteran in the field of GIS and mapping, and a lifelong geographer, David McKittrick is currently Outreach and Training Manager at Blue Marble Geographics. A graduate of the University of Ulster in Northern Ireland, McKittrick’s experience encompasses many aspects of the geospatial industry, including cartographic production, data management, marketing and sales, as well as software training and implementation services. McKittrick has designed and delivered hundreds of GIS training classes, seminars, and presentations and has authored dozens of articles and papers for numerous business and trade publications.

 

A Brief History of Global Mapper Part III

This screenshot of Multiview in Global Mapper 19.1 is a prime example of how far the software has come since its days as dlgv32.

The final chapter in the saga of this venerable software’s two-decade long adventure, picks up where we left off in the second installment. The year was 2011 and if you recall, our hero — the dashing and indefatigable Global Mapper — had seemingly been kidnapped by the ruthless and malevolent Blue Marble Geographics. At least that was the impression of many of the software’s most loyal disciples at the time.

“Global Mapper has been swallowed by some faceless, uncaring corporate behemoth. Gone are the days of the freewheeling, interactive development philosophy of the early years.” Or so they feared. In reality, nothing could have been further from the truth.

Global Mapper Becomes a Team Effort

While many of our detractors at the time assumed that Blue Mable looked loftily down on its customers from its executive offices atop some gleaming glass and steel skyscraper, the reality was that the company’s entire staff could have fit comfortably into one of the aforementioned building’s elevators. Spurred by the addition of Global Mapper to the company’s software offerings, Blue Marble would eventually see an expansion of its workforce but at the time it numbered no more than 20.

Sam Knight
A hand full of the Blue Marble crew at a company outing in summer 2017.

For you as a Global Mapper user, the most significant consequence of this transitional period and the years that followed was a rapid acceleration in the software’s development. Reaping the benefits of a supporting cast, Mike Childs was able to singularly apply his talents to the development of Global Mapper. Routine and mundane tasks, such as selling the fruits of his labor to customers, were left to a group of dedicated specialists. If the truth be told, one of the most difficult aspects of this transition was convincing Mike that he no longer needed to respond to each and every inquiry.

Needless to say, relinquishing control over something that you have caringly nurtured for many years is not always easy, but Global Mapper was becoming a team effort with each developer significantly contributing to the software’s functionality. If it were possible to quantify and graph Global Mapper’s evolution, 2011 was the year that the slope of the line began to steepen and the release of version 14 the following year proved this and served to silence the cynics.

Global Mapper Development from 2012 to Present

The bulleted list of new functionality, updated tools, performance improvements, and various bug fixes for version 14 alone was 10 pages long, a trend that has continued with successive releases. Condensing this into a manageable size for this Brief History does a disservice to the software. If you have a couple of hours to spare and you want the unabridged version, read the What’s New section in the software’s Help files. I guarantee you will be introduced to features and functions that you did not even know were included.

Chelsea E | Projections

In late 2016, Global Mapper would undergo what was arguably the most significant update in its release history, at least from a superficial perspective. Out went the old “disco” logo, and its idiosyncratic interface design and in came a fresh new look with updated graphics, a more intuitive layout, and a bold new logo. What didn’t change was the powerful capability of the software and the continued improvements that were being made to its functionality.

Chelsea E | Projections

While it’s fun and sometime enlightening to look over your shoulder and marvel at how far you have come, Blue Marble’s philosophy is very much focused on looking forward. Plans are already in the pipeline for Global Mapper version 20 and beyond. Thanks to the continued support of our growing customer base and their eagerness to participate in the collaborative development process that is unique to this remarkable application, we have a long list of new functionality that will be added over the coming years. Global Mapper is a project that will never be complete.


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.

Got LiDAR? Now What?

LiDAR Extraction in Global Mapper
Using Global Mapper‘s Path Profile tool to precisely digitize the edge of a curb from terrestrial LiDAR data.

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.

The basics of collecting LiDAR data from an airborne platform.Illustration by Chelsea Ellis

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.

LiDAR data and DEM

Feature Extraction

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.

Next Steps

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.