Top 5 Features of Global Mapper’s Lidar Module Version 22

Written by: Cíntia Miranda and David McKittrick

The Lidar Module®, an optional add-on to Global Mapper®, provides advanced point cloud processing tools, including Pixels to Points®, for photogrammetric point cloud creation using overlapping drone-captured images, automatic and manual point cloud classification, as well as feature extraction, hydro-flattening, and more.

The latest version of the Lidar Module includes several new tools, as well as improvements to many of the existing features and functions. This blog highlights the top five new features of version 22:

 

  • A new Terrain Paint tool 

 

Terrain Painting is a set of terrain editing tools that provide the ability to modify the elevation values of a gridded elevation dataset interactively. Using simple drawing tools, this innovative addition to the Lidar Module can be used to fill gaps in the terrain, raise or lower the existing elevation inside a defined area, or set a specific elevation height. Dynamically editing a terrain layer in this way is useful for site planning, modeling, and cleaning up or improving sensor derived elevation data. This tool works with all types of gridded elevation datasets, including DSMs and DTMs, bathymetric datasets, lidar derived terrain data, and more.

The ‘Fill Gaps’ operation is used to fill in missing areas of terrain.

The ‘Smooth Terrain – Average’ operation is used to create a cleaner terrain surface.

In this example, the ‘Set Terrain Height’ tool is used to create the simulated path of a road. The feathering effect creates a sloped transition into the surrounding terrain.

 

  • A new algorithm that improves building classification 

 

The Lidar Module includes a variety of automatic feature identification and point reclassification tools. The underlying algorithms analyze the point cloud’s geometric structure in a local context to look for patterns that match a prescribed format. The specific options include reclassification of points representing high vegetation or trees, powerlines, power poles, and buildings. For the version 22 release, the algorithm for identifying buildings in a point cloud has been updated to provide a more accurate reflection of human-made structures when working with point cloud data from any source.

The orange points have been automatically classified as building points.

 

  • Improved building extraction with better 3D shape simplification 

After a point cloud has been appropriately classified, individual vector features can be created, reflecting the object’s three-dimensional characteristics. For example, 3D line features can be automatically generated by connecting the dots for those points that were identified as powerline points. Perhaps one of the more useful applications for this feature extraction tool is for creating 3D polygons representing buildings. In version 22, several new settings and options have been added, and the vectorization algorithm has been significantly improved to provide more accurate building outlines. Individual surface planes are now created, allowing the building’s specific structure to be more precisely represented, and the simplification process has been updated, resulting in cleaner roof planes and sidewalls.

Complex building features extracted from a point cloud as 3D polygons.

 

  • A new option to generate a process summary report when using the Pixels to Points process 

 

The Pixels to Points tool is arguably one of the most powerful components of the Lidar Module. Using simple drone-collected images, this tool photogrammetrically analyzes and identifies recurring patterns of pixels in multiple images to create a 3D reconstruction of the environment. Version 22 of the Lidar Module includes several improvements to this function, most notably a new ‘Post Processing Report’ that concisely summarizes the pertinent information from the data generation process. This report includes a summary of input data, processing time, output data, quality assessment, as well as a visual representation of the individual output layers. The report is in HTML format and will automatically open in your default web browser from where it can be saved as a PDF file.

A section of the report generated after the Pixels to Points process has been completed.

 

  • Two new lidar draw modes

 

3D lidar or other point cloud data can be rendered to reflect various point attributes, such as elevation, return intensity, and point classification. This latest release introduces two new lidar draw modes:

Color by Source Layer — With this option, a unique color is applied to each loaded point cloud layer as a simple way to distinguish separate point cloud layers in the workspace clearly. A specific color can be selected for a layer in the Lidar Display for that layer.

Color by Scan Angle – In this mode, lidar points are colorized using the scan angle attribute, with values potentially ranging from -90 to 90 degrees. The actual color of the points is determined by the Shader Option chosen in the workspace.

If you’re not familiar with Global Mapper and the Lidar Module, request a two-week free trial today. If you would like to speak with a representative about how the software can address your unique geospatial challenges, request a demo!

Top 5 New Features of Global Mapper v.22

Top 5 New Features of Global Mapper v.22

Global Mapper v.22 is here!  As with all previous releases, version 22 introduces an extensive array of new and updated functionality in virtually all software areas. What hasn’t changed is the price. For under $550 for a single user license, Global Mapper is still unquestionably the best value in GIS software. As a first look at some of its most significant new capabilities, this blog highlights the top five new features of Global Mapper v.22:

1.New Eye Dome Lighting settings in the 3D viewer to help improve the visual display of vector and lidar data: 

While it’s probably not accurate to say that point cloud data appears flat in the 3D Viewer, it is sometimes difficult to discern texture or depth when viewed obliquely, especially when the view is static. The solution to this challenge is the new Eye Dome Lighting feature. This new display option in the 3D Viewer enhances depth perception by darkening the rendering of some points to produce an enhanced perspective of texture.

The best way to see this new tool’s effect on displaying a point cloud in the 3D View is to look at some lidar data before and after the  Eye Dome Lighting feature has been enabled:

2.A new tool for simplifying loaded meshes or TINs

The mesh simplification tool combines the triangle faces of mesh features if they do not significantly contribute to the scene’s shape to simplify and reduce its size. This tool reduces the number of faces, or vertices, in a mesh by collapsing the edges and placing replacement vertices based on the specified method. This process attempts to preserve as much of the mesh’s shape and boundaries as possible while significantly reducing the size and memory requirements for working with the mesh, or TIN,  within Global Mapper or other 3D tools. 

Unsimplified mesh

Simplified Mesh

3.A new Spatial Operations tool for calculating the intersection of layers of the area feature

The new spatial operations tool performs vector overlay procedures on area features to find the intersection of two area layers. By combining this tool with selection by location, or attribute, or repeating with various layers, you can perform a detailed analysis to identify where multiple features coexist. For example, intersection operations are often used in suitability analysis to find the locations that meet two or more criteria.

4.A new Analysis menu option to find the overlap (both percentage and graphical) between two or more lidar, raster/image, and or terrain layers

The new Find Overlap Between Lidar/Raster/Terrain Layers tool can be accessed from the Analysis menu. This tool generates a report showing the overlap percentage between layers. It optionally creates a new raster layer showing overlapping areas – a straightforward and yet useful process! 

5.A new consolidated Digitizer Menu, providing convenient access to all drawing and digitizing tools

It is a testament to the strength of Global Mapper’s vector creation and editing capabilities that the Digitizer has finally been assigned its dedicated menu. Longtime users of the software will have witnessed the continual expansion and reorganization of the Digitizer’s right-click menu and may, on occasion, have struggled to find a particular tool. Thankfully those days are gone.

The Digitizer menu offers a one-stop location for accessing all of the tools needed for working with vector data. Organized into a series of logical sub-menus, this extensive collection of tools includes everything from a simple point, line, and area feature creation to advanced 3D mesh editing functions. If you work with vector data, and virtually all Global Mapper users do, this new menu will streamline your workflow.

There’s much more to Global Mapper!

Global Mapper includes many more data editing, rendering, and analysis tools, and supports over 300 formats of geospatial data, making it the most versatile and interoperable application on the market.  If you’re not familiar with Global Mapper, request a two-week free trial today. If you would like to speak with a representative about how the software can address your unique geospatial challenges, request a demo!

Global Mapper — the all-in-one and affordable GIS software. Contact us today to learn more.

Global Mapper Maintenance and Support

By Rachael Landry

Longtime users know that every purchase or upgrade of Global Mapper includes a year of technical and licensing support. This support, along with our Knowledge Base, videos, webinars, and self-guided training, allows users to explore and experience all Global Mapper has to offer. Our year-long Maintenance and Support Plan (M&S Plan) begins on the date payment is received, and it includes access to all version releases of the software within that 12-month period, allowing customers to utilize the most current version of Global Mapper.

The “Support” Part – The Blue Marble Tech Team is here for you

In addition to providing users access to the most current version of Global Mapper, the M&S Plan also includes the unparalleled technical and licensing support that Blue Marble is known for. Our technical team is ready to answer any questions you might have, from format support to complex workflow scenarios in a timely manner. However, it is important to highlight that technical support is not a substitute for training. Blue Marble offers many training solutions both in person and virtually, including a Global Mapper Certificate program. 

Maintenance and Support Renewals and License Structure

The M&S Plan provides customers with the option to renew their support every year. Purchasing an M&S Plan is not obligatory, as Global Mappers license structure is perpetual, meaning that not renewing it will not affect your license. However, if your M&S Plan has expired, Blue Marble’s technical and licensing support teams may be unable to assist you if you require assistance.

Blue Marble strongly encourages you to stay up-to-date with your M&S Plan, so that you have access to the best software we have to offer. Staying current with your plan guarantees the highest level of software support and service, and that you are receiving the latest software fixes and enhancements.

In the coming weeks, Global Mapper 22 will be released. Make sure that you are eligible to use all the great features and enhancements the new release has to offer by contacting orders@bluemarblegeo.com.

Terrain Layer Support in Global Mapper Mobile v2.1

Written by Jeff Hatzel

One of the many new features in Global Mapper Mobile v2.1 is support for terrain layers, which introduces a variety of new functions and settings within the app. These new tools add to an already robust feature set that help to extend  the reach of your GIS. While much of this functionality is available in the free version of the app, some more advanced options are part of the optional Pro Module. 

Features available in the base version of the app:

Prior to the release of Global Mapper Mobile v2.1, a terrain layer exported from the desktop version Global Mapper was handled as a simple raster layer, without any elevation information.  The new functionality recognizes terrain layers and their respective elevation information and metadata.

All terrain layers will be rendered using the Atlas Shader, one of the default shaders in the desktop version of the application. Users can also control whether hill shading is enabled via a new setting found in the Configuration settings in the mobile app. 

Terrain data is displayed using the Atlas shader, with shading enabled by default (left). A setting found in Configuration allows users to disable hill shading if necessary (right).

Navigating to the Control Center within Global Mapper Mobile will feel familiar to users who work with the desktop software. The layer’s elevation range, units, and other related information are now available when viewing the metadata for a terrain layer. This provides a useful reference for users when in the field, providing situational awareness in relation to their data and surroundings.

Terrain layer metadata now shows relevant elevation information associated with the layer, including elevation range, units, and other pertinent information

The addition of terrain layer support to Global Mapper Mobile v2.1 also helps to expand location information by providing elevation information at a specific location. Enabling either Crosshair or GPS and Crosshair location mode will report the elevation values of the terrain at the crosshair location. This displays specific elevation information for a given location from a source other than the device’s location services.

The elevation value of a given location can be viewed when using a crosshair-based location option. As you pan and zoom on the map, the elevation value will update based on the loaded terrain layer.

Advanced options in the Pro Module:

Navigating to the new Shader Options section within Configuration provides Global Mapper Mobile Pro users more options to customize the terrain data. The Shader Name option allows access to any of the terrain shaders that are built into the desktop version of the software.

Users who need to simulate water level on their terrain data will find the Display Water Level settings beneficial to their workflows. Whether modeling water level rise or trying to understand what changes in water level will look like on the landscape, users can control when this is enabled, and at what elevation water is displayed.

Terrain layer support is just one of the many new features in Global Mapper v2.1. If you’re interested in exploring the app further, visit Global Mapper Mobile v2.1 for details. The app is also a free download from the Apple App Store and Google Play Store.

Lidar Quality Control in Global Mapper

Written by: Mackenzie Mills

As more and more individuals independently collect 3D data using  drones equipped with Lidar sensors, it is important to discuss the accuracy of the data. Analysis performed using point cloud data is only as accurate as the source data. When working with 3D data you must worry about not only accuracy in the x and y directions, but the elevation, or z, component. This z value usually contains the most variation or error. While GPS receivers provide accurate horizontal information, they can struggle with vertical accuracy. RTK or PPK systems can help improve location information, but can be prohibitively expensive to include in a drone set up. An alternative would be to survey ground control points for use in post processing to help improve the accuracy of your point cloud.

To check for vertical error and correct it, those surveyed ground control points can be used with Global Mapper’s Lidar QC tool.

This Lidar QC tool, included in the Lidar Module of Global Mapper, compares control points with nearby points in the point cloud layer to measure the elevation difference between the two. Before the point cloud is adjusted, the tool provides a report showing the compared points and elevation difference between the point cloud and control points. After reviewing these metrics, you can then choose to apply the adjustment to the point cloud layer.

The adjustment of the point cloud is determined by interpolating a best fit surface for the area of the point cloud based on the elevation differences calculated and reported by the Lidar QC tool. This method allows the point cloud to be adjusted accurately even if there are differing degrees of vertical error in different areas of the cloud.

To look closer at the process and options available in the Lidar QC tool, we will work through an example.

To begin, ensure a point cloud layer and a layer of 3D ground control points have been loaded into a Global Mapper workspace.

Opening the Lidar QC tool from the Lidar Toolbar, select the point cloud layer and control point layer to use. You do have the option to use only selected 3D points as control points instead of using a whole layer of point features.

The maximum distance parameter in the Lidar QC setup determines how far from each control point Lidar returns will be considered and compared to the control point elevations.

The maximum point cloud returns to consider determines how many Lidar points will be compared to each control point. After the maximum number of point cloud points is reached for each control point, the program stops the comparisons even if all the returns within the maximum distance have not been considered.

Clicking the OK button will generate the Feature Measurement Information seen below. To generate the feature measure values for each control point, the Lidar QC tool uses inverse distance weighting (IDW) to determine the point cloud elevation at the coordinate location of each control point. The reported statistics show the point cloud elevation (LIDAR_ELEV), control point elevation (ELEVATION), and the elevation difference (ELEV_DIFF) for each control point.

This is where you could stop if your elevation differences are within your accepted error margin. Additionally, the feature measure metrics reported by the Lidar QC tool are added as attributes to the control point vector features in Global Mapper so you can look up and reference these values later.

If the elevation difference exceeds your accepted error, you can choose to Fit Lidar to Control Points from the Feature Measurement Information dialog. This will use an interpolated best fit surface determined by comparing the point cloud to the control points to vertically adjust your point cloud layer(s) to better fit the control points. As you can see in the path profile below, the adjusted point cloud is several meters above the original

Although we have been discussing this tool in the context of Lidar data, you can use it with any point cloud, such as those constructed from drone images. By ensuring the accuracy of your point cloud, you will have a more accurate terrain grid, contour lines, and other analyses derived from the quality-controlled point cloud layer.

Working with Bathymetric Data

By: Katrina Schweikert

Global Mapper is well known for its file format support and terrain analysis capabilities. Perhaps what is less well known is the way the various data analysis tools in Global Mapper can be used to generate and analyze bathymetric data. 

Bathymetry is the study of topographic landforms below the water, such as on the ocean floor, the bottom of a lake, or even the bed of a river. Given that over 70% of the earth’s surface is covered with water, this branch of 3D analysis is extremely important in understanding the characteristics of the planet. What follows is an exploration of some of Global Mapper’s analysis and visualization techniques that are relevant to the bathymetric analysis. 

Great Barrier Reef Depth model obtained from Geoscience Australia

Bathymetric Data Support

Global Mapper provides support for over 300 file formats, and many of those include formats for bathymetric data, marine navigation, and remote sensing of subsurface data. Here are some examples: 

  • Marine Navigation and Nautical Charts (S-57 and S-63 with s-52 symbols, NOS/GEO, NV Verlag, PCX,  and others)
  • Sonar, Sidescan sonar and Bathymetric Sounding data (Lowrance Sonar, XTF, HTF, and others) 
  • Gridded Bathymetric Data (BAG, DBDBV, Hypack, IBCOA, GRD98, NITF, various other terrain formats such as netCDF, GeoTiff, ASCII grid)

Bathymetry in a DTM

Gridded bathymetric data provides various visualization and analysis options when loaded into Global Mapper.   The preformatted elevation shaders or a custom shader can be used to find the best color scheme to show depths of submarine landforms. Terrain Shaders can also reveal the slope steepness and slope direction of underwater topography. 

Displayed in the 3D viewer, gridded bathymetric data comes to life with draped imagery and charts, water level visualizations, and any other reference vector data. Quickly and easily generate elevation profiles, or a series of sequential cross-profiles using the Path Profile tool and Perpendicular Profiles setting. 

3D view of bathymetric data with path profile cutaway showing a shipwreck site in the Gulf of Mexico

Combining data from different surveys and fusing data from multiple sensors is as easy as loading in the datasets and ordering the layers. The analysis and visualization tools can automatically merge the various inputs to take data from the topmost layer or choose to view and compare the data from multiple surfaces simultaneously. There are also options for cropping, aligning, feathering, and comparing to create a more seamless integration between disparate datasets. 

Analyzing Bathymetry as a 3D Point Cloud

Global Mapper provides tools for converting existing sensor data such as sonar or soundings to a 3D point cloud; or for sampling existing gridded data to create an array of 3D points at the pixel centers. This enables the automated classification algorithms of the Lidar Module, which can be used to identify the seafloor and identify or remove other subsurface structures or topography. This powerful tool has been used for shipwreck detection and modeling, as well as identification of other subsurface features. 

Subsurface Contouring

Global Mapper includes an easy-to-use tool for generating precise depth contours and shorelines from gridded bathymetric data. The resulting line features can be edited and stylized in a variety of ways and combined with other datasets to create custom bathymetric charts. Alternatively, the areas enclosed by contours lines can be filled to create polygons that show the water extent at different depths or sea levels. 

Contour lines colored by elevation combined with other basemap data to create a custom chart

Measurement and Volume Calculation

Global Mapper provides various tools for calculating two- and three-dimensional measurements. In the 2D map view, the Path Profile window, and the 3D Viewer linear distances and areas are measured using a simple drawing function. Volume can be calculated from bathymetric data by either defining a height or by calculating numerous volumes across a range of water heights. Volume can also be measured by defining a plane or comparing the bathymetric data to a surface grid. This provides various options for water volume calculation. 

Flood Modeling

By combining bathymetric data with terrain data and using tools such as the watershed analysis and water level rise tool it is possible to discover flood extents, flow accumulation, and perform other hydrographic analysis. 

Employing the various terrain editing and terrain creation functions, Global Mapper can be used to create hydro-enforced DEMs or other modified surface models. These can be analyzed within Global Mapper or exported to various formats to support analysis in other applications. 

Temperature and other Measurements

The bathymetric analysis may also involve other gridded datasets such as surface temperature, salinity, gravimetric data, and various other measured values. These datasets can also be visualized, rendered in 3D, and contoured to provide additional insight into the dynamics of lakes, oceans, and other water bodies. 

The latest version of the Global Mapper and Lidar Module include several enhancements, many of which apply to bathymetric data analysis. If this blog piqued your interest and you’d like to find out if Global Mapper is the right application for you, download a 14-day free trial and request a demo today!

How Pixels to Points Works

By: Katrina Schweikert

The Pixels to Points tool in Global Mapper’s Lidar Module uses a process of Automated Aerial Triangulation to reconstruct the 3D scene present in overlapping images. This computationally intensive process may seem like magic, but it relies on basic concepts of vision and photogrammetry. Photogrammetry is the science of taking real-world measurements from photographs. Let’s pull back the curtain to reveal how this process works. 

What is Aerial Triangulation?

Based on photogrammetry techniques, the location, size, and shape of objects can be derived from photographs taken from different angles. By combining views from multiple images, the location of distinct parts of the image are triangulated in 3D space. This is similar to how depth perception works with two eyes; since the object in front of you is viewed from two slightly different angles, the brain can perceive how far away the object is.

Diagram of depth perception

In traditional photogrammetry with stereo-image pairs, the two angles of the image allow the photogrammetrist to measure objects in the image and determine their real world size. With automated techniques using many overlapping images, the entire 3-dimensional nature of the scene being photographed can be reconstructed. 

Photogrammetry measurement diagram

What are the steps in Automated Aerial Triangulation?

Automated Aerial Triangulation involves a number of steps to get from the original images to 3D point clouds, terrain models, textured 3D models, and orthoimages. The first step is to detect distinct features in each image, and then match those features across the adjacent images. The challenge is to automatically detect distinct features that may be at different scales and rotations in each of the images. 

Features detected in two images, with lines showing the matches found

After the features are tracked through the images, the initial reconstruction begins with a process called Structure from Motion (SfM). In the context of mapping technology, the structure of the 3D scene is revealed based on the motion of the camera. This process calculates the precise orientation of the cameras relative to each other and to the scene, and builds the basic surface structure of the scene. This is the point where the selected Analysis Method is applied. The Incremental Analysis Method starts with a set of the best matching photos, and incrementally adds the features from subsequent images into the scene to build the 3D reconstruction. This works well for drone-collected images collected over a large area in a grid pattern. The reconstruction will typically start somewhere near the center of the scene, and work outwards. The Global Method, by contrast, takes information from all of the images together and builds the scene all at once. This makes for a faster process, but it also requires a higher degree of overlap between adjacent images. This is recommended if the images are collected focusing on an object of interest, such as a building, especially when all of the images focus on that central area or object. The result of the Structure from Motion analysis is a sparse point cloud that builds the basic structure of the scene, and a set of precisely oriented cameras that show where and in what direction the images were taken relative to each other

Example of sparse point cloud with camera frustums

The final step of the Automated Aerial Triangulation process involves filling in additional details from each image that was calibrated as part of the scene. This process is called Multi-view Stereo. It involves calculating the depth of each part of the image (i.e. how far away it is from the camera), and then fusing those depth maps to keep the points that appear in multiple images. 

Depth map and confidence map based on overlap with other images

This process generates the final dense 3D point cloud. Based on the options selected, there may be further processing to convert the point cloud into a refined mesh surface (3D Model) that is photo-textured by projecting the images onto it. This option also produces the highest quality orthoimage, removing relief distortions based on the 3D mesh surface. 

What factors impact Automated Aerial Triangulation?

Lens Distortion

An important initial step in the Pixels to Points process is removing the lens distortion in the image. While the photograph may appear as a flat image capture of the target area to the untrained eye, most photographs contain some distortion, particularly towards the edge of the image, where you can see the effect of the curvature of the camera lens. Pixels to Points will remove distortion in the image based on the Camera Type setting. Most standard cameras need correction for the basic radial lens distortion in order to create an accurate 3D scene. The default camera type setting, ‘Pinhole Radial 3’, corrects for the radial lens distortion (using 3 factors). In some cases it might be beneficial to use the ‘Pinhole Brown 2’ camera model, which accounts for both radial distortion and tangential distortion, where the lens and sensor are not perfectly parallel. 

Image with distortion and processed undistorted imag

Some cameras have the ability to perform a calibration, which automatically removes distortion in the image. If the Pixels to Points tool detects from the image metadata that the images have been calibrated, it will switch to the ‘Pinhole’ camera model. If you know your images have already had the distortion removed either by the camera, or some other software, choose the ‘Pinhole’ camera model, which will not apply any additional distortion removal. The final two Camera Type options account for the more extreme distortion of Fisheye or Spherical lenses. Select these options if appropriate for your camera. 

Focal Length and Sensor Width

An important part of transferring the information in the image into a real world scale is knowing some basic camera and image information. The focal length and sensor width values allow for a basic calculation of how large objects are in the image, and thus how far away they are from the camera. What is calculated using these values is a ratio between a known real world size (the sensor width) and the pixel equivalent of that size in the image. This is a starting point for reconstructing the 3D scene. Focal Length information is typically stored in the image metadata. Global Mapper includes a database of sensor widths based on the camera model, however, you may be prompted for this value if your camera is not in the database. You can obtain this information from the device manufacturer. 

Image Position

The basic position of each camera is typically stored in the image metadata (EXIF tags). With a standard camera this location is derived from GPS, from which average horizontal accuracy is within a few meters. There are a few ways to improve the accuracy of the resulting data based on the desired accuracy, and decisions about cost vs. time spent. 

Height Correction

The GPS sensors contained in most cameras may have sufficient horizontal accuracy for some applications. However, the corresponding height values are usually less accurate and are based on an ellipsoidal height model. A basic height correction can be performed using the options for Relative Altitude. This will anchor the output heights based on the ground height where the drone took off (the height of the ground in the first image). You can enter a specific value, or Global Mapper can automatically derive the value from loaded terrain data or online references (USGS NED or SRTM). 

Ground Control Points

One way to correct the position of the output data is through the use of Ground Control Points. This is a set of surveyed points with known X,Y,Z locations that should be evenly distributed throughout the scene. The measured ground control point locations need to be visually identifiable throughout the corresponding images, so it’s common to use a set of crosshairs or targets placed on the ground throughout the collection area before the images are captured.

 

Ground Control Points can be loaded into the Pixels to Points tool and the corresponding locations identified in multiple input images. This will align the scene based on the control points taking precedence over the camera positions. This procedure is a more time-intensive option, but is streamlined through a process whereby the images containing each point are highlighted, It is also possible to use Ground Control Points after the output files have been generated. Global Mapper provides various tools for this, including 3D rectification and the Lidar QC tool, which can also provide accuracy assessment information. 

RTK and PPK Positioning

Hardware manufacturers provide options for improving the accuracy of the positional information by communicating with a reference base station in addition to satellites, and by performing additional corrections based on available information at the time of the image collection. This includes both Real-Time Kinematic and Post-Processing Kinematic options. With some systems, higher accuracy positioning information is written into image metadata, which can be used directly in the Pixels to Points tool. Other systems may save the higher accuracy positions in a text file, in which case you will want to load your images into the Pixels to Points tool and use the option to Load Image Positions from External File

 

Understanding the variables and data requirements for the Pixels to Points tool and other SfM processes will help you to collect images better suited for processing. In turn, this will create higher quality results for further geospatial analysis.

The latest version of the Global Mapper Lidar Module includes several enhancements, many of which apply to the Pixels to Points tool for generating point clouds and 3D meshes from drone-captured images. If this blog piqued your interest and you’d like to find out if the Lidar Module of Global Mapper is the right application for you, download a 14-day free trial and request a demo today!

Classifying Lidar with the push of a (few) button(s)!

By Rachael Landry

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:

*An unclassified point cloud is displayed as gray.

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. 

*A point cloud with classified ground points.

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. 

*Point cloud with ground buildings and vegetation classified.

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! 

To learn more about the Lidar Module’s automatic classification tools please check out the Global Mapper Knowledge Base and if you have any further questions about the auto-classify tools please contact geohelp@bluemarblegeo.com.

Getting to Know the Global Mapper Toolbars

Written by: Cíntia Miranda, Director of Marketing

Global Mapper is a robust and yet easy-to-use GIS application that offers access to an unparalleled variety of spatial datasets, a complete suite of vector and raster processing tools, and an extensive collection of analysis tools, especially for working with Lidar or terrain data. If you’re new to Global Mapper, getting to know the toolbar is one of your first steps in familiarizing yourself with the application.  This blog provides a brief review of the buttons to help you understand the basic function of each.  More in-depth information is available in the Knowledge Base

The toolbars in Global Mapper provide quick and easy access to the most commonly used tools. To hide or display the toolbars, click the View menu and, from the Toolbars submenu, check or uncheck the appropriate checkboxes as needed.

The drop-down menu on the right side of each toolbar provides access to Customization of the toolbars, including adding new buttons and showing text labels.

Note that some toolbar buttons will not be available in certain situations. For example, most of the Digitizer (Edit) buttons will be disabled until one or more vector features are selected on the map.

Here’s what each toolbar button can do for you:

File

Open Data Files  Save Workspace  

Connect to Online Data  Map Layout Editor  

 Overlay Control CenterConfigure

 Overview Map

Navigation

Zoom (Alt+Z)Pan (Alt+G)

Zoom InZoom Out

Restore Last View (Ctrl+Backspace)Full View

Selection

Digitizer Tool (Alt+D)Select by Drawing Polygon

Clear Current SelectionSelect Labels

Tools

Measure Tool (Alt+M)Feature Info Tool (Alt+P)

Search Vector Data

Analysis

Create Elevation GridCreate Contours

Calculate Cut and Fill Volume (Ctrl+Alt+M)Path Profile (Alt+L)

Create View Shed (Alt+V)Create Water Shed

Combine/ Compare Terrain LayersCombine/ Compare Terrain Layers

Create 3D Fly-through

Viewer

Add 2D Map ViewsRotate Map

Image SwipeShow 3D View

Link 2D and 3D Views (Ctrl+Shift+3)Display Water Level

Increase Water LevelDecrease Water Level

Enable/ Disable Hill ShadingDynamic Hill Shading

Shader Drop-down Menu

GeoCalc

Enable GeoCalc Projection ModeAuto-select GeoCalc Transform

Launch Geographic Calculator

Favorites

Favorites Drop-down

Run Selected Command (Ctrl+Enter)

Digitizer (Create)

Create Point/ Text FeatureCreate Line Feature (Vertex Mode)

Create Line Feature (Trace Mode) (Shift+T)Create Area Feature

Create Rectangle/ Square Area FeatureCreate Circle/ Ellipse Area Feature

Digitizer (Advanced)

Create Distance/ Bearing/ COGO LineCreate Range Rings / Ellipses

Create Regular Grid of FeaturesCreate Strike-and-Dip Point

Cut Selected Area(s) From Another AreaRight Angle Draw Mode (R)

Ortho Draw Mode

Digitizer (Edit)

Move Selected Feature(s) (Ctrl+Shift+M)Rotate Scale Feature(s)

Display Area/ Line Vertices (Shift+V)Move Selected Vertices

Insert VertexCombine Line Features

Split Line At Selected VertexCreate Points From Line/ Area Vertices

Create Areas From LinesCreate Lines From Areas

Combine Selected AreasCrop To Selected Areas

Create Buffer Around Selected Features

GPS

Start Tracking GPS (Ctrl+T)Stop Tracking GPS

Keep GPS\ Video Vessel on screenOrient View to GPS \Video Heading

Mark Waypoint (Ctrl+M)Mark Waypoint from Averaged Position

Mark Waypoint at OffsetDisplay GPS Info

Animate

StartStop

SlowerFaster

AddRemove

Get the most of Global Mapper by learning how it can improve productivity, encourage efficiency, and save time and money in your GIS operations.  The following resources will help you become familiar and more proficient with the software.

1) The Global Mapper Getting Started Guide provides a concise overview of the software.

2) The Global Mapper Knowledge Base has more in-depth information about Global Mapper’s features and functions.

3) The FAQ page offers answers to commonly asked questions.

4) The self-guided training provides a series of free hands-on exercises, including written instructions and sample data files. Take a moment to download these instructional materials to learn how to use some of Global Mapper’s basic tools. 

5) The GeoTalks Express webinars are a series of free online presentations conducted every two weeks covering a wide variety of topics and themes. Sign-up to one or multiple webinars! 

6) Global Mapper online training classes provide the most effective way to get the most out of the software. Scheduled public classes provide a thorough introduction to the full breadth of the application’s features and functions, while a custom class will allow your organization to adapt the course content to meet your specific needs. For more information, email training@bluemarblegeo.co

Global Mapper’s intuitive user interface and logical layout help smooth the learning curve and ensures that users will be up-and-running in no time. Take advantage of the aforementioned resources and if you need any further assistance with the application, contact geohelp@bluemarblegeo.com.