Using Global Mapper and Global Mapper Mobile to Prepare for a 186-Mile Bike Ride

After I crossed the finish line of the Trek Across Maine in 2018, I immediately signed up for the next ride without hesitation.

The cycling event takes place over three days and spans 180 miles — starting in the western mountains of Maine and ending on the state’s coast. It benefits the American Lung Association, which is why I chose it as my first cycling event to participate in. I rode in honor of my grandmother who had COPD.

Me in Belfast, Maine after finishing my first Trek Across Maine in June 2018.

When I finished the 2018 Trek, I was so excited that:

  1. I survived!
  2. I got to see a beautiful part of the state I live in
  3. I would be so much more confident on the next Trek because now I knew the route

But then the Trek organizers changed the route for 2019. *womp, womp, womp*

Instead of starting at Sunday River and ending in Belfast, the 2019 Trek would start and end in Brunswick, making a 186-mile loop in central Maine. The route wouldn’t “trek across” anymore, it would “trek around”.

On top of learning about the new route, I hurt my knee badly in January while doing a simple leg stretch (lame!) which was a training-changing injury. So, with a lowered confidence, I wanted to learn more about the new route.

Here’s how I used Global Mapper to visualize and mentally prepare for the 2019 Trek, and how I used Global Mapper Mobile to record my 186-mile journey.

Using Online Data and the Path Profile Tool in Global Mapper

The Trek provides GPX files for each day of the ride on the organization’s website. I downloaded these files; dragged them into Global Mapper; and uploaded elevation data, satellite imagery, and a street map from Global Mapper’s free online data sources.

Using the elevation data, I created path profile views of each of the three riding days. This allowed me to see which of the days would have the largest climbs and where those hills were located. After only a few minutes looking at the data, I could see that Day 2 would be the most challenging. Only ten miles into the 62-mile day, there would be a 375-foot climb, four 225-foot hills, and another 375-footer at mile 45.

Day 1 of the Trek Across Maine
Here’s the elevation of Day 1, the route from Brunswick to Lewiston, Maine.
Day 2 of the Trek Across Maine
Here’s Day 2 from Lewiston to Waterville, which looked like (and proved to be) the hardest day of Trek 2019.
Day 3 of the Trek Across Maine
Here’s Day 3, which appeared to be much easier than Day 2 with only one 250-foot climb at mile 31.

I also explored the “design” of the route by looking at it over satellite imagery to see the vegetation and water bodies I would be riding by. Although Day 2 appeared to be the toughest, it also looked as if it would provide some beautiful views over lakes in the rural Fayette and Readfield area.

Satellite imagery and the Trek Across Maine route in Global Mapper
The three-day route of the Trek Across Maine over satellite imagery. Day 1 is red, Day 2 is green, and Day 3 is blue.

Planning Training Rides in Global Mapper

Looking at the path profiles helped me plan my own rides for training. After talking to some cyclists and looking up popular routes in my area, I planned a 28-mile training ride from my apartment in Portland to Gray that included a 375-foot climb — a hill similar to those two big ones on Day 2.

Using the Digitizer in Global Mapper and my online data, I mapped out this training ride, too.

Training ride from Portland to Gray, Maine
Here is the 28-mile training ride I planned with the computer cursor hovering over the top of the 375-foot climb around mile 10.

Exporting my Map for the Road

In addition to using Global Mapper to look at the path profiles of each day of the Trek, I also used it to add vector points representing each rest stop along the route. After adding these points, I was ready to export my map as a Global Mapper Mobile Package (GMMP) file. Global Mapper 21 and Global Mapper Mobile v2 will allow for a native projection to be retained in a GMMP file. So as I exported, I chose to retain my projection, in my case just for visualization purposes.

I uploaded this file to my Global Mapper Mobile app, and planned on adding data to it while on the 186-mile ride.

Exporting a Global Mapper Mobile Package
Exporting a Global Mapper Mobile Package file from Global Mapper Mobile.

Picture Points and the Measuring Tool in Global Mapper Mobile

June 14, 2019 was the first day of the Trek. I had my map in my Global Mapper Mobile app, and I was ready to start documenting my ride!

There are a few ways I could add photos to my map in Global Mapper Mobile. I could create points on my map from geotagged photos, or I could take photos right in the app and add them as attributes to previously existing points. Since I take so many photos with my iPhone camera, I chose to add photos using the Picture Point Create Mode — creating points from photos I had taken outside of Global Mapper Mobile.

Creating a picture point in Global Mapper Mobile
Here are screenshots of the process of creating a picture point on my map in Global Mapper Mobile. I added a photo of my coworker Jeff and me at the second stop on Day 3.

I originally planned on using the app primarily for documenting my ride, but I found it useful in other instances.

When Day 2 really turned out to be the hardest day, I opened Global Mapper Mobile at the third rest stop to see the distance between me and Colby College — the destination of that day. It was a long 21.6 kilometers (13.4 miles) to ride with sore seat-bones and my disappointment in the shortage of fluffernutter sandwiches at this stop.

Using the Measure tool in Global Mapper Mobile
Using the Measuring tool, I figured out how much further I had to go to get to the last stop of Day 2 of the Trek Across Maine.

Global Mapper and Global Mapper Mobile: Easy as Riding a Bike

As Day 2 proved to me, riding a bike isn’t always easy. But GIS software can be!

I am not a GIS professional. I know that editing and exporting a simple map of a bike route isn’t rocket science. But Global Mapper’s user-friendliness made that non-rocket science even easier.

It took just a few minutes of viewing the route with elevation, street, and satellite data to get a better idea of what the 2019 Trek would be like. Even though exporting my Trek map to Global Mapper Mobile was the first time I had used the desktop and mobile apps in tandem, it was a very straight-forward process.

Uploading a map from Global Mapper Mobile to the Global Mapper desktop
A screenshot of the final photo I added to my map in Global Mapper Mobile. It’s a photo of my team and I just after crossing the finish line.

When I returned back to the office after my second Trek Across Maine, I exported my GMMP file from Global Mapper Mobile and imported it to my Global Mapper desktop. I clicked the vector point labeled “Finish Line” with the Feature Info tool, and up popped a photo of me and my Trek Across Maine team.

Immediately after that picture was taken, I signed up for Trek 2020 without hesitation.


Chelsea Ellis


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.

Top 5 Tools and Functions of the Global Mapper LiDAR Module

In anticipation of the increasing availability and use of LiDAR and other point cloud datasets, the LiDAR Module, an add-on to Global Mapper, was first introduced in version 15 of the software. Over the last five years, this popular component has rapidly evolved and offers an array of powerful tools.

In this blog entry, we highlight the top five most important tools and functions in the LiDAR Module, including extracting vector features, processing UAV-collected images into point clouds, filtering LiDAR data, and generating 3D meshes or models.


Pixels-to-Points Tool in Global Mapper
3D Point cloud of a barn viewed created with the Pixels-to-Points tool

1. Pixels-to-Points

The newest addition to the LiDAR Module, Pixels-to-Points is a tool for creating a high-density point cloud, orthoimage, and 3D meshe from overlapping images, especially those captured using a drone

Based on the principles of photogrammetry, the Pixels-to-Points process identifies objects in multiple images and from multiple perspectives to generate a 3D point cloud. As a by-product of the point-generation process, the tool can also create an orthoimage by gridding the RGB values in each point, as well a 3D mesh, complete with photorealistic textures.

Pixels-to-Points offers photogrammetric point cloud creation that is both affordable and straightforward, and is increasingly used as an alternative to traditional LiDAR collection.


Auto Classification of LiDAr points
Buildings and trees identified and reclassified in a LiDAR layer

2) Auto Point Reclassification

The LiDAR Module’s automatic reclassification tools can accurately identify points representing ground, vegetation, buildings, and utility cables.

Algorithms in the LiDAR Module analyze the geometric properties and characteristics of point clouds to quickly classify these features. This process is commonly used to identify, classify, and filter ground points when creating a Digital Terrain Model (DTM), or as a first step in the process of isolating specific feature types when extracting vector features, such as buildings or trees, from a point cloud.


Feature Extraction using the Global Mapper LiDAR Module
Vector lines representing above-ground power cables extracted from LiDAR data

3) Feature Extraction

The Feature Extraction tool is used to create vector objects from appropriately classified points.

Based on a series of customizable settings, points representing buildings, trees, and utility cables are analyzed and automatically delineated as a series of 3D vector objects or, in the case of buildings, as a 3D mesh.

Feature extraction is particularly useful for creating building footprints, defining roof structures, powerlines, and other 3D features from classified LiDAR data.


Digitizing the edge of a curb using the Global Mapper LiDAR Module
Digitizing the edge of a curb using the perpendicular profile function

4) Custom Feature Extraction

Custom Feature Extraction is a function for delineating atypical 3D features from point cloud data.

This function allows for the creation of accurate 3D line or area features by defining control vertices in a sequential series of perpendicular path profile views. Examples of using Custom Feature Extraction might be for defining road curbs, pipelines, or drainage ditches,


3D Mesh created using the Global Mapper LiDAR Module
3D Mesh of a suburban neighborhood created from selected points in a point cloud

5) Mesh Creation from LiDAR Points

Mesh Creation is a function that uses a selected group of points to create a 3D vector object complete with photorealistic colors or textures.

The LiDAR Module offers the ability to create a mesh or model using the 3D geometry and colors of a selected group of points. When viewed in 3D, this model displays as a multifaceted photo-realistic 3D representation of the corresponding feature.

For information about all of the features that the LiDAR Module has to offer, visit our website here.