Drone Flight Tips When Using Global Mapper’s Pixels to Points Tool

Written by: Mackenzie Mills,  Application Specialist

As drones gain popularity and more people begin collecting their own data for analysis, tools like Pixels to Points in Global Mapper become more important in workflows. The Pixels to Points tool is the structure from motion (SfM) process to create three-dimensional data and image outputs from sets of drone-collected images. In many situations, this is a great and cost-effective alternative to collecting lidar (light detection and ranging) data.

The SfM process used in the Pixels to Points tool identifies features in multiple images by matching pixel patterns in the images. Features identified in multiple images are then triangulated and constructed in 3D space to generate three-dimensional outputs, including a point cloud.

Whether you are experienced with drone data collection or are new to this method, it is worth learning or reviewing some tips for quality data collection. The most important requirements for drone-collected images that you intend to process with Pixels to Points (structure from motion) are overlap and clarity.

The overlap between collected images is very important as it allows the tool to identify features in multiple images in order to triangulate them in space and construct the output layers for the area. With sets of images that contain little to no overlap, the Pixels to Points tool cannot identify features from multiple views in order to triangulate and construct the outputs. This will result in an error, or outputs that contain missing data. We recommend a minimum of 60% overlap between adjacent images, but you should always plan for more.

Drone images of a baseball field.
Drone images of a baseball field being aligned.

The images you intend to use need to have clear and identifiable features so that the Pixels to Points tool can identify them based on clear pixel patterns. This means two things, (1) the images need to be in focus, and (2) the images need to have identifiable features. Images that are blurry due to the camera shaking or vibrating, or out of focus will yield incomplete or no results from the structure from motion process. This is because the noise(or movement that makes the images blurred) inhibits the program’s ability to identify features. Areas with no identifiable features will similarly result in errors. Common scenes that encounter this issue are areas of snow cover, all white with no features, or bodies of water with no lasting features that can be identified.

Comparison of a focused and a blurred image due to noise.
Comparison of a focused and a blurred image due to noise.

Depending on the goals of your project, you may want to use different methods for collecting images. Some basic variables that go into how you plan your drone flight are pattern, height, and angle.

Drone flight patterns.
Drone flight patterns.

For two-dimensional mapping to generate an elevation model of a ground area and not surface features, capturing nadir images (looking straight down) from as high up as possible is best. For this data collection, you can use a simple mow the lawn pattern moving back and forth over the area of interest.

For 3D modeling of high relief terrain, buildings, and structures, you’ll want to capture oblique images in order to capture the sides of features. Here you would fly at a lower height, 150 to 200 feet, with a front-facing camera and collect data in a checkerboard pattern, going back and forth over the study area, then back and forth again crossing over the previous flight lines. This will help to capture the sides of terrain features from various angles for a better three-dimensional reconstruction.

For structural modeling of a specific building or stockpile feature, you’ll want to capture oblique images as you fly at a lower height in a circle around the object of interest. This will capture images covering the sides of the feature to create a detailed model.

Types of angles of drone images.
Types of angles of drone images.

Flight planning is an important part of data collection when working with drone collected data. 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 work.

How to Compare Point Clouds Using Global Mapper v21.1

Written by: Mackenzie Mills,  Application Specialist

In many areas of GIS,  change detection can be a powerful analysis tool. Comparing datasets through time can add another dimension to your work as you can visualize and measure how a study area changes. This type of analysis is becoming particularly important as drone mapping and collection of first-hand data are more common. Change detection analysis can also be very useful when looking for natural change in an area, like the impact of a natural disaster or new vegetation growth year to year; or a man-made change, like the progress of construction in an area or deforestation; or change made to the data by previous edits.

In the release of Global Mapper version 21.1, the Compare Clouds tool was introduced to detect change points between overlapping lidar or point cloud layers. Previously in Global Mapper, change detection was only available using the Combine/Compare Terrain Grid tool, which creates a new elevation layer based on the difference in the per-pixel Z-values of the overlapping layers using the subtraction setting.  The output of the new Compare Clouds tool is a layer containing the points that have changed between the input point clouds. 

To use the Compare Cloud tool, start by loading the point clouds you would like to compare into Global Mapper. Select the Compare Could tool from the Lidar Tools toolbar. 

Compare Lidar Point Clouds
Compare Lidar Point Clouds

In the Point Cloud(s) to Compare Against box, select the starting or original point cloud. This is typically the first or earlier pass over an area. The cloud(s) selected in the Point Cloud(s) to Find Changes In box will be compared to the “Point Cloud(s) to Compare Against when the tool is run.

This new tool works to compare point clouds by having the user input a distance to use for comparison. This Minimum Distance Between Point Clouds value allows for a looser or tighter comparison of the clouds. This setting is important when comparing point clouds because they are made up of individual points and not interpolated like a terrain grid. It is unlikely that the point clouds you are looking to compare will contain points in the exact locations, so a threshold (specified in point spacings, meters, or feet) is required for comparison. Any points from the Find Changes In point cloud that do not have a corresponding point in the Compare Against cloud will be considered changes in the area.

When the process runs, those points in the second layer that have been found to have shifted beyond the designated threshold when compared to the original layer will be marked as having changed. After running this process, you will find a new layer added to the workspace containing only the points that have changed.

Points detected to be changed using the Compare Cloud tool in Global Mapper
Points detected to be changed using the Compare Cloud tool in Global Mapper

In the image above, you see an area of rocks where some have been removed between point cloud one and point cloud two, after running the Compare Cloud tool we see the selected (red) areas are the points detected to be changed.

After identifying change in an area using the Compare Clouds tool, you may wish to classify the points detected as changed or delete them to reconcile multiple datasets. Alternatively, you may want to generate gridded layers to show the changed areas and layer these changed grids over the original or use the Compare Against layer.

This powerful new tool speeds up the process of change detection on 3D data by directly comparing two point clouds to find points with significant change. This change detection functionality can be applied in a wide variety of industries including agriculture, forestry, and engineering. Take a look at the latest release of Global Mapper and the Lidar Module to bring this streamlined workflow into your own data analysis.

How to use Global Mapper’s Raster Reclassify tool

Written by Jeff Hatzel, Senior Application Specialist

With the release of Global Mapper v21.1 comes the addition of an exciting new tool, Raster Reclassify. The development of this tool, like so many in Global Mapper®, was heavily driven by requests from our users. The initial release of this tool allows users to modify the pixel values of a palette image. A common use case for this might be to adjust the classes with a landcover file to create a new layer with a simplified set of classes. Let’s look at a more advanced workflow: using Raster Reclassify to adjust the values of an image created from classified lidar.

Hint: If you’d like to learn about this tool in detail, review the Raster Reclassify Knowledge Base page!

Using Lidar Classification Codes to Make a Raster Layer:

If you’re familiar with the Create Elevation Grid tool in Global Mapper, you know that this tool allows you to create a terrain layer based on the elevations within the source point cloud. You may also know that when working with lidar data, this tool allows you to create a grid-based on a variety of lidar attributes and properties, for example, classifications.

Classified lidar data
Classified lidar data (left) was gridded based on its classification code to make an output raster (right).

This resulting file represents multiple lidar classes from the source point cloud. The classes follow the same color scheme used to display lidar by classification. However, it’s possible we may only have an interest in a specific set of classes or an individual class, buildings for example. We’ll address that with Raster Reclassify.

Hint: Take a look at the different Grid Type options in the Create Elevation Grid tool.

Raster Reclassify to Highlight Classes of Interest:

The Raster Reclassify tool (part of the Analysis Menu) allows you to adjust the values of the source layer. In this situation, we want to focus on buildings. We’re going to merge all non-building classes: ground, low, medium, and high vegetation, bridges, powerlines, and water. Buildings will be retained as a unique class.

Raster Reclassify
Raster Reclassify allows you to load the source palette from a reference file. You can choose which classes you want to reclassify, adjusting their description, color, etc.

This tool creates a new output layer within the current Global Mapper workspace. As you can see below, that layer will now only show the newly created classes you outline in the Raster Classification Rules section of the Raster Reclassify tool.

Source file comparison
The source file (left) compared to the reclassified layer (right). The reclassified layer now only shows two classes, based on the rules set in the Raster Reclassify tool.

Hint: Want to display different layers side-by-side in the same workspace as we’ve done in some of the above images? Check out Multiple 2D Map Views!

What’s Next?

Products created by Raster Reclassify can be used in a variety of applications. Some may be final deliverables for reclassified landcover datasets, used to make or adjust clutter grid files, or any other number of possibilities.

How will you use the Raster Reclassify tool?

Keep an eye out in the future for new functionality in this tool, including the ability to reclassify terrain data and non-palette imagery!

How to move your Single User Global Mapper® license in a few easy steps

The day has come, you received a computer upgrade at work or you finally splurged on a new laptop. The excitement and joy of finally having a faster computer with better graphics and a new operating system can quickly be diminished by the laborious task of transferring files and software to the new machine. This blog aims to alleviate some of that headache by walking you through Global Mapper’s single-user license transfer workflow. 

The first thing to do is to check the version number of your installation of Global Mapper. If you have version 20 or 21 you will be able to download the installation files directly from the Blue Marble website to your new machine. If you have version 19 or older you will need to move the installation files manually to the new computer. You’ll also want to ensure your Maintenance and Support (M&S) is still active. If you have questions or concerns about moving your license or the status of your M&S, please contact authorize@bluemarblegeo.com before moving your license.

Once you have checked your version of Global Mapper, navigate to the Help menu at the top of the screen, click “License Manager”, and the window below will open:

Blue Marble License Manager
Blue Marble License Manager

Select “Release” next to the license you would like to remove. A prompt will appear to confirm that you want to move forward. Click the “Yes” button. After the removal process is complete, you should receive a message containing the removal code for your license. This code will also be copied to your computer’s clipboard. To complete the removal, send the removal code to authorize@bluemarblegeo.com for confirmation that your license is no longer active. After the Blue Marble licensing team verifies this information, you will be able to move your license to the new machine.

It is possible that you may not receive a prompt upon removal, but do not worry, you can access it from the C: drive. On most computers, the file can be found in the following folder location: C:\ProgramData\GlobalMapper\GlobalMapper[your version number]. The ProgramData folder is hidden by default in Windows. If you can’t navigate to that directory,  you can view hidden files and folders with the instructions below.

Navigate to the search bar next to the Windows “Start” button and type “hidden files”. This will bring you to the “For Developers” prompt.

For developers window prompt
For developers window prompt

Under the heading “File Explorer”, click the “Show settings” next to “Change settings” to show hidden and system”. The Folder Options window will open, review the options and select “Show hidden files, folders, and drives”, then click the OK button. Please note these instructions are for Windows 10, for instructions on how to access “Hidden Files” in other versions of Windows please visit the Microsoft support page.

Windows File Explorer OptionsCintia Miranda | Projections
Windows File Explorer Options

Once this step is completed, you will be able to locate the Program Data folder on your C: drive. Please attach a copy of your GlobalMapper.lic_removed file in an email to authorize@bluemarblegeo.com.

Global Mapper license location on C Drive
Global Mapper license location on C Drive

The Licensing Team will then verify your license removal and you will be able to move your license to the new machine. Before beginning the licensing process, please remove your computer from all external hardware, including docking stations. Finally, follow the detailed steps to set up and obtain the license in Part I of Global Mapper’s Knowledge Base.

Remember, if you have any questions or run into any problems moving your license, our Licensing Team is available Monday – Friday 8 am – 5 pm Eastern Standard time. They can be reached by phone at 207-622-4622 ex 1146 and by email at authorize@bluemarblegeo.com

Chelsea E | Projections
Rachael Landry is a Blue Marble Geographics Marketing Assistant and an unofficial licensing guru.

Get access to Blackbeard online oil and gas data from Global Mapper 21.1

On February 19, 2020, Blue Marble Geographics® released version 21.1 of Global Mapper®. The release included many new software features, including subscription-based access to Blackbeard Data — an online data service for accessing pipeline, well, and lease information.

Blackbeard Data is primarily known for providing information to assist institutional professionals and independent investors in the acquisition of mineral assets, specifically buying oil and gas royalties.  Blackbeard Data maintains the world’s largest database of oil and gas royalty owners and the world’s largest database of oil and gas comparables built from oil auction histories, which is invaluable to many users of Global Mapper in the energy sector.

Version 21.1 of Global Mapper introduces BlackBeard Data as part of its extensive online data portal. This subscription-based service is available through an intuitive interface, enabling users to seamlessly transfer and analyze oil and gas data from Blackbeard Data to Global Mapper, saving time and effort.

Users of Global Mapper can now access Blackbeard data by following these five easy steps:

  1. Press the Connect to Online Data button in the File toolbar or File Menu
  2. Navigate to PREMIUM CONTENT > Blackbeard Oil and Gas Data
    Select a sub-layer of interest
  3. Enter your API key or visit  https://blackbearddata.com/data-products/global-mapper

    Blackbeard Data Dialogue Box - Global Mapper V21.1Blackbeard Data Dialogue Box on Global Mapper V21.1
  4. Specify the desired data bounds, then press connect.
  5. Use the Info tool to get info about WMS or WMTS layers, or open the Attribute Editor to view attributes for the vector WFS layers.

    Blackbeard Data Screen View in Global Mapper V21.1Blackbeard Data Screen View in Global Mapper V21.1

Upgrade now to version 21.1 of Global Mapper to have direct access to Blackbeard Data (with a premium subscription) — the world’s largest database of oil and gas. For more information on how to acquire version 21.1 of Global Mapper visit globalmapper.com. For more information on how to acquire Blackbeard Data premium subscription visit blackbearddata.com.