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Mapping Class: Work with Sentinel-2 Imagery in Geographic Imager – Part One, with Tom Patterson

Welcome to the latest edition of Mapping Class! The Mapping Class tutorial series curates demonstrations and workflows created by professional cartographers and expert Avenza software users. In this month’s edition, we welcome Tom Patterson, a map-maker extraordinaire and a true household name in the cartography world. Today Tom is sharing with us a demonstration showing how he works with Sentinel-2 Imagery Data using Geographic Imager and Adobe Photoshop. Tom uses a new dataset that that represents a “pretty difficult” image to process and offers an excellent look at how to create beautiful natural colour images from satellite data.

Part One of this exciting walkthrough covers the techniques Tom uses for accessing and importing satellite imagery data, as well as his approach to colour correction using some of the powerful built-in image editing tools in Adobe Photoshop. Tom has produced video notes below to help you follow along! Look out for Part Two, coming in next months edition of Mapping Class!

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Work with Sentinel-2 Imagery in Geographic Imager: Part One
by Tom Patterson (Video notes adapted from original)

This tutorial explains how to process Sentinel-2 satellite data, released by the European Space Agency for free, into natural colour images. Beautification is the goal—nature often can use a little help when using satellite images for maps and graphical presentations.

To do this tutorial you will need Adobe Photoshop and Avenza Geographic Imager. Trial versions for geographic imager can be found here. For this tutorial, you should also have intermediate Photoshop skills, a good internet connection, and a computer with plenty of RAM.

Getting the data

The US Geological Survey distributes Sentinel-2 data on the EarthExplorer data portal. You can also download Sentinel-2 on the Copernicus Open Access Hub, although I find EarthExplorer easier to use.

1) Downloading data from EarthExplorer requires that you first sign in as a registered user.

2) After you sign in, use the “Search Criteria” tab in the upper left to specify a point of interest. You can also draw a polygon on the map to specify a larger search area.

3) Click the “Data Sets” tab next. From the long list of data types, select “Sentinel-2.”

4) The EarthExplorer portal offers useful tools for narrowing your search. For example, you can filter by acquisition date and cloud cover. Sentinel-2 image extents are viewable as transparent map overlays. 

5) Click the “Results” tab to peruse the available images. Then click the image thumbnails to see larger image previews in false color. Scrolling down from the image previews reveals additional metadata

To download a scene from the search results list, click the “Download Options” icon. You will then see these two download options:

● L1C Tile in JPEG2000 format (XX MB)

● Full Resolution Browse in GeoTIFF format (XX MB)

Download both.

7) The Full Resolution Browse in GeoTIFF format is a false-color image (bands 11, 8A, and 4) at 20-meter resolution.

8) Decompress the L1C Tile in JPEG2000 format archive. It contains the raw Sentinel-2 bands and a true-color image. You will need to drill through multiple folders to get to these data 

Importing the data

Because Photoshop does not natively import JPEG2000 files, you will need to use a Geographic Imager to import the Sentinel-2 data. The advantage of Geographic Imager over other plugins is that it preserves georeferencing and allows you to export manipulated Sentinel-2 images as GeoTIFFs.

1) In the Photoshop drop menu, go to File/Import/GI: Advanced Import

2) Select one or more Sentinel-2 bands to import (in this case, we want Bands 4, 3, and 2 which correspond to our Red, Green, and Blue bands) and click OK. Importing could take a minute or two to complete. Each Sentinel-2 band will open as a separate Photoshop file. That’s it.

Colour Correction

The premade True Color Images are convenient to obtain, and you can easily adjust them to create acceptable results. However, they have an Achilles heel: snow- and ice-covered landscapes. Automated processing removes the very lightest tones, rendering them as empty white (below, left). In order to depict subtle details in snowy terrain, one must build the satellite image from scratch using the raw data in bands 4, 3, and 2 (below, right).

1) Use Geographic Imager to open bands 4, 3, and 2 (File/Import/GI: Advanced Import…). The import will take a couple of minutes to complete, and the three bands will open as separate Photoshop files.

2) With one of the Photoshop files active, go to the flyout menu in the upper right corner of the Channels window. Select Merge Channels…

3) In the Merge Channels window, change the mode to RGB Color and specify 3 channels.

4) Another window will pop up. Make sure that band 4 is the red channel, band 3 is the green channel, and band 2 is the blue channel. Then click okay.

5) Photoshop will then ask whether you want to save each of the three bands. Don’t save them. You will then see the merged 16-bit RGB image, which is mostly gray

Using Curves

Now the fun begins. Compared to Levels adjustments that are linear, Curves adjustments are non-linear, giving you more control over discrete portions of the tonal range in an image. They are a little tricky to use at first, but the precise results that you can achieve with this command make learning it very worthwhile.

1) Apply a Curves adjustment layer and adjust the tonal range of the image taking care to leave some value in the snow patches. I often apply two or more Curves adjustment layers, one on top of the other, to fine-tune the tonal balance. With 16-bit images, you can stretch the tonal range without worrying about banding artifacts.

2) Save your applied curves as adjustment layers so you can save and re-use them for later. This is especially important when you start mosaicing imagery data (coming in part two!) and need to ensure curves are applied consistently across multiple images.

Below is the curve that I used to adjust the image. The histogram shows the distribution of light and dark values. Moving the lower-left end of the curve to the right lightened dark trees. Moving the top-right end down added a slight amount of tone to the white snow. Both of these moves decreased overall contrast.

Touch-up with the False Colour Image

We want to add a bit more eye-catching vibrance to our image. We can do that by utilizing the included false colour imagery and using the colour properties and blending tools to really make the mountainous terrain pop. 

1) Since we need the false colour imagery to match the resolution of our RGB image, we need to upscale it. This can be done using the image sizing properties and resampling using the “Preserve Details” setting.

2) Overlay this upscaled false colour image over top of the RGB layer. You can then adjust the blending modes to create a nice vibrant image. In this case, I use the “Soft Light” blending mode, which is great for making the alpine terrain really stand out.

3) Create a selective colour adjustment layer to touch out individual colour tones in the image. For example, I try to remove much of the yellow tones in the image, as yellow tones are atypical for the “cold” alpine-like terrain we find in this image. 

Coming up in Part Two:

The land areas in this image now stand out quite well. They look quite a bit more vibrant than the raw data and offer a bit better tonality than what we find in the automatically generated true-colour image included in the download. What we can do next is work on making the water areas stand out as well. I’ll show you how you can use the mosaic tool in Geographic Imager to work with elevation data to create layer masks that make adjusting water areas easy.

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About the Author

Tom Patterson worked as a cartographer at the U.S. National Park Service, Harpers Ferry Center until retiring in 2018. He has an M.A. in Geography from the University of Hawai‘i at Mānoa. Presenting terrain on maps is Tom’s passion. He publishes his work on ShadedRelief.com and is the co-developer of the Natural Earth dataset and the Equal Earth projection. Tom has served as President and Executive Director of the NACIS. He is now Vice-Chair of the International Cartographic Association, Commission on Mountain Cartography.

Cartographer Chronicles: Dan Cole

When it comes to map-making, Dan Cole is a true master. A passionate academic, Dan has designed maps for research and academia for over 40 years. As the GIS Coordinator and Chief Cartographer of the Smithsonian Institution in Washington, DC., Dan has created maps and cartographic pieces for museum exhibits enjoyed by hundreds of thousands of visitors every year. As a researcher, Dan has authored scholarly publications in several renowned academic journals, and co-edited the book “Mapping Native America: Cartographic Interactions between Indigenous Peoples, Government, and Academia.”  

For Dan, his interest in maps began when he was a child. He often enjoyed being the “navigator” on family vacations and building off a natural fondness for exploration he developed hiking trails as a Boy Scout. In his freshman year at the University at Albany – State University of New York, Dan first became interested in a career in cartography while studying under esteemed cartographer Dr. Michael Dobson. The opportunity to turn a genuine interest into a full-fledged career was too good to pass up, and Dan soon found himself enrolling in every cartography, geography, and remote sensing course he could. In the final year of his Bachelor of Geography degree, Dan became a cartography teaching assistant, providing him his first opportunity to act in a teaching role. 

Immediately after graduating, Dan was recruited to an assistantship position at Michigan State University (MSU). Here he published his first research paper, which was co-authored alongside Richard Groop, now a professor emeritus in Geography at MSU. Completing a Masters degree in Geography in 1979, Dan moved to Oregon State University (OSU) and began collaborating with cartography professor Jon Kimerling, first as a TA, and later to run the Cartographic Lab there.

“Were there Dinosaurs in your backyard?” – One of Dan’s maps on display in the Deep Time Hall at the Smithsonian National Museum of Natural History

Leaving OSU in 1981, Dan took on a variety of roles at several recognizable institutions across the country. Some of these roles included; leading the Cartographic Lab at the University of Maryland, working as a cartographic technician for the National Oceanic and Atmospheric Administration (NOAA), contract cartography work for the Woods Hole Oceanographic Institute, and taking on a course instructor position at Montgomery College. In 1986, Dan began working at the Smithsonian Institution (SI) and was able to pursue his passion for research full-time. Some of his earliest mapping pieces with SI became an integral part of the “Handbook of North American Indians”, a series of scholarly reference volumes documenting the culture, language, and history of all indigenous peoples in North America. Through a cooperative arrangement, he was also responsible for researching the changes to the Bureau of Indian Affair’s “Indian Land Areas” map in 1987 and 1989.

“My first five years there mostly involved cartographic research, doing both manual and computer-based mapping for the Handbook of North American Indians—at the time we used Adobe Illustrator 88!”

Later, Dan moved to a role as the GIS Coordinator with the Smithsonian’s IT Department. There, he was exposed to the entire breadth of cartographic projects spanning the Smithsonian’s impressive list of research disciplines. He worked on projects related to biodiversity and species ranges, created maps documenting climate change, and contributed to interactive map exhibits showing the impacts humans have on the environment. From volcanology and mineralogy to prehistoric studies and even the study of dinosaurs, Dan became involved in most of the Smithsonian’s major subject areas. Several of Dan’s map creations even feature in the permanent exhibits at the Smithsonian National Museum of Natural History.

Pathways and origins of invasive marine species, one of 40 maps created for the Ocean Hall exhibit at the Smithsonian National Museum of Natural History

Although each unique exhibit and area of study came with its own specific objectives, from a cartographic standpoint, he found that most still shared a few key concerns. He noted that one of the biggest challenges for almost all museum researchers is to geo-reference the vast number of artifacts and biological specimens that are contained in the museum’s collections. Such a process is crucial to analyze where specimens were found in the past and to provide insights on where they could be found in the future based on changes to the environment.

“Collections for nearly all museums around the world, including the Smithsonian, have environmental characteristics documented with the collection site. But most, by far, do not have coordinate locations for artifacts and specimens collected before the GPS era; rather, the majority of their collections have descriptive locations. So we must use Natural Language Processing—a computer science-based technique—to process coordinates from the written descriptions.”

By the mid-1990s, digital mapping processes had become an integral component of map creation. Dan became one of the first adopters of MAPublisher, using the first version of the software to work with maps and geographic data in the Adobe Illustrator environment. Today, MAPublisher continues to play a crucial role in map production at SI, and Dan still uses MAPublisher to produce maps for some of the museum’s most popular exhibits.

Since obtaining MAPublisher in the 1990s, I have been involved with over 20 different exhibits and multiple publications. All of these required importing shapefiles to Adobe Illustrator, PDF, or EPS formats so that publishers or exhibit staff could work with them. While other digital mapping software has improved over the years, I find the placement of typography is still handled more elegantly with MAPublisher.”

One of five maps that form part of the “Narwhals: Revealing an Arctic Legend” exhibit at the Smithsonian National Museum of Natural History (now a travelling exhibit!)

The museum environment presents some unique challenges for a cartographer. In a museum setting, maps need to be designed to communicate with the general public, synthesizing and presenting complex information for an audience that may be unfamiliar with the subject matter. This differs from research-focused work, which typically requires static printed maps that adhere to the strict guidelines of academic journal and book publications, and is typically viewed by experts in that particular field of study. For museum exhibits, cartographers need to employ careful design techniques to make maps informative and engaging to diverse audiences of all ages. These techniques result in maps that vary widely in format, from traditional static poster maps to animated and interactive maps that tell dramatic stories or serve as learning tools. Commenting on some of the unique challenges in today’s “pandemic era”, Dan notes that virtual online exhibits have made the use of web-mapping and interactive maps more commonplace.

“For the immediate and long-range future, I see greater use of static, animated and interactive maps online for public education on a variety of topics, with less interactivity in-person.”

Dan continues to oversee GIS support and teaching for staff at SI. He greatly enjoys the opportunity to work on diverse projects from a variety of interesting areas of study. As the GIS Coordinator at SI, he now covers over 400 GIS and satellite image processing users, plus over 500 story map writers and developers, including staff with very little knowledge of geography, cartography, or GIS. His passion for map-making remains to this day, and his maps continue to be enjoyed by visitors from around the world. An educator at heart, Dan has some parting advice for any students or young professionals seeking to break into the wonderful world of cartography;

“The advice that I give to nearly everyone interested in a cartography or GIS career is: while you’re still in school, plan to get a minor or double major in the field that interests you. Get a broad-based education that enables you to serve your clients in any field and join professional and academic organizations to expose yourself to others’ work. Most importantly, even once you are employed, never stop learning!”

“The Great Inka Roads” – One of 15 maps created for the exhibit at the Smithsonian National Museum of the American Indian

Mapping Class: Efficient Labeling using attribute expression builder with Steve Spindler

Welcome back to this month’s edition of Mapping Class. The Mapping Class tutorial series curates video tutorials and workflows created by experienced cartographers and Avenza software users. Joining us once again is Steve Spindler, a longtime MAPublisher user, and expert cartographer. Steve is here to show you a quick tip for using the attribute expression builder within MAPublisher to quickly perform batch edits of labels. 

Steve has produced a short video to demonstrate how he uses the expression builder to quickly edit street names. The Avenza team has produced video notes (below) to help you follow along.

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Label efficiently using Attribute Expression Builder
by Steve Spindler (video notes by the Avenza team)

With MAPublisher, labeling your maps is a breeze. With powerful tools such as LabelPro, labeling is only a matter of selecting the data you want to label, and configuring a robust set of rules that control how each label is placed and styled. But before you can start labeling, you must have high-quality, accurate attribute information for your map data. Since labels are typically generated by displaying text values contained in an attribute column, it is important that attributes are not only accurate but are also formatted in a way that is optimized for display on a map. In many cases, cartographers need to spend time reformatting or editing attribute information before they can generate labels, a process that can become quite time-consuming. Nowhere else is this problem more common than when dealing with street names and road network data.

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When labeling streets, cartographers often spend time correcting, or even generating brand new attribute information that can be used to create more concise, effective street labels. This typically involves changing street prefixes and suffixes to a condensed short form (i.e “North Cherry Boulevard” becomes “N Cherry Blvd”). For smaller projects, this can be done by manually editing the individual attribute values directly within the MAP Attribute panel. For large projects, especially those dealing with hundreds or even thousands of map features, manual editing would be very time-consuming.

For a more efficient approach, Steve shows how you can use the Expression Builder to easily modify large selections of attribute values. The first step is to open the MAP attribute table, which displays all the attribute information contained within a specific map layer. Steve identifies the attribute column that contains the text street names and will use this to build out a new attribute column to create his labels.

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Next, Steve opens the Edit Schema window of the attribute table. Here, you can access column information such as the data type, default value, field visibility, and most importantly; the expression builder.

The expression builder may seem intimidating at first, but with a little bit of effort, it can be an incredibly powerful tool for calculating attribute values and performing batch-edits on your data. The tool uses built-in operators and items in the objects list (attribute names and values, constants, functions) to calculate custom attribute information based on a specified set of expressions. In this case, Steve first creates an expression set that modifies the suffix values in the Street name field (i.e “Boulevard”) and substitutes them with the appropriate short form (“Blvd”). The expression is used to populate a new attribute column called “Road_suffix”. The end result means attribute values such as “East Utica Street” will be passed to a new attribute value of “East Utica St”.

This image has an empty alt attribute; its file name is inputs.jpg
IF_CASE(name,
ENDSWITH(name, “ Street“),SUBSTITUTE( name , “Street”, “St”),
ENDSWITH(name, “ Drive“),SUBSTITUTE( name , “Drive”, “Dr”),
ENDSWITH(name, “ Road“),SUBSTITUTE( name , “Road”, “Rd”),
ENDSWITH(name, “ Court“),SUBSTITUTE( name , “Court”, “Ct”),
ENDSWITH(name, “ Way“),SUBSTITUTE( name , “Way”, “Wy”),
ENDSWITH(name, “ Lane“),SUBSTITUTE( name , “Lane”, “La”),
ENDSWITH(name, “ Route“),SUBSTITUTE( name , “Route”, “Rt”),
ENDSWITH(name, “ Boulevard“),SUBSTITUTE( name , “Boulevard”, “Blvd”),
ENDSWITH(name, “ Turnpike“),SUBSTITUTE( name , “Turnpike”, “Tpke”),
ENDSWITH(name, “ Avenue“),SUBSTITUTE( name , “Avenue”, “Ave”),
ENDSWITH(name, “ Place“),SUBSTITUTE( name , “Place”, “Pl”),
ENDSWITH(name, “ Circle“),SUBSTITUTE( name , “Court”, “Cr”),
ENDSWITH(name, “ Highway“),SUBSTITUTE( name , “Highway”, “Hwy”),
ENDSWITH(name, “ Expressway“),SUBSTITUTE( name , “Expressway”, “Exp”)
)


Next, Steve creates a second set of expressions that will further adjust his Road_suffix attribute column to substitute any street name prefixes (North, East, South, West) with their corresponding short-form (N, E, S, W). This second expression (see code block below) is used to populate another new attribute column called “Label”, which will ultimately be used to generate the final formatted label layer. 

((IF_CASE( Road_suffix ,
STARTSWITH(Road_suffix, “West “), SUBSTITUTE( Road_suffix, “West “, “W “),
STARTSWITH(Road_suffix, “South “), SUBSTITUTE( Road_suffix, South “, “S “),
STARTSWITH(Road_suffix, “North “), SUBSTITUTE( Road_suffix, “North “, “N “),
STARTSWITH(Road_suffix, “East “), SUBSTITUTE( Road_suffix, “East “, “E “)
))

This image has an empty alt attribute; its file name is ExpressionAttributes.jpg

Note that these expressions are specific to the dataset and map area Steve is using for his project. When using expression builders for your own maps, pay careful attention to the attribute values specific to your area of interest. The best part about expression sets is that they are highly flexible, meaning you can build upon and modify existing expressions, save them to your library, and even use them across multiple different mapping projects!

With his newly created “Label” attribute column, it’s simply a matter of configuring the LabelPro tool to display these formatted label values. With a bit of configuration, the end result is a clean, uncluttered, collision-free label layer. The labels now use all the correct prefixes and suffixes Steve required. By saving his expression sets to his library folder, Steve can now quickly and easily repeat the exact same batch-editing process for new maps with only a few clicks! 

This image has an empty alt attribute; its file name is ExpressionBuilder-1024x249.jpg

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About the Author

Steve Spindler has been designing compelling cartographic pieces for over 20 years. His company, Steve Spindler Cartography, has developed map products for governments, city planning organizations, and non-profits from across the country. He also manages wikimapping.com, a public engagement tool that allows city planners to connect and receive input from their community using maps. To learn more about Steve Spindler’s spectacular cartography work, visit his personal website. To view Steve’s other mapping demonstrations, visit cartographyclass.com

Mapping Class: Georeferencing Techniques Part Two – Working with Scanned Maps, with Hans van der Maarel

Welcome back to another exciting edition of Mapping Class, a video-blog series where we curate tutorials and workflows created by expert cartographers and Avenza power users from around the world. Today we release Part Two of our Georeferencing Techniques tutorial with Hans van der Maarel, owner of Red Geographics. In Part Two, Hans demonstrates some techniques he has developed for working with more challenging georeferencing tasks, including dealing with unknown projection information and working with scanned maps. If you missed Part One, in which Hans covers the basics of Georeferencing in MAPublisher, check it out here.

Hans has produced a jam-packed video walkthrough detailing his georeferencing process. The Avenza team has produced video notes (below) to help you follow along.

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Georeferencing Techniques Part Two: Working with Scanned Maps
by Hans van der Maarel (video notes by the Avenza team)

As we discussed in last month’s Mapping Class, georeferencing is the process of taking imagery or map data that lacks geographic location information and associating it with specific coordinates on Earth. Previously, Hans showed us how MAPublisher provides a few tools that make georeferencing simple vector map data a painless process (Check out part one here!). Best of all, using the built-in georeferencing tools, this can be done entirely within the Adobe Illustrator environment.

However, what can you do if you are working with historical maps or scanned images that lack spatial referencing or detailed projection information? This can present a challenge for many cartographers, as the projection information is necessary to create an effective cartographic product that will minimize distortion and maximize the spatial accuracy of the final result. To tackle this problem, Hans shares a series of tips and tricks that he uses for working with scanned historical maps. He uses a beautiful historical map of Northwest Africa to demonstrate his approach.

Right away, Hans identifies a few obstacles. First, he notices that the scan is not a perfect copy of the original map. Due to natural curves and bends in the physical paper version of the map, there is minor distortion in the digital image that arose when the map was scanned. This could create problems for georeferencing the image, as the “fitting” process can be susceptible to image distortions, even when a suitable projection is determined. Thus it is always a good idea to examine your scanned map prior to beginning the georeferencing process. Becoming aware of potential issues with the scanned map data can help inform decisions on the data’s suitability for a particular mapping task. Acknowledging that the distortion is relatively minor in this scanned map, Hans chooses to proceed with the georeferencing process.

Hans notices that the scanned map image does not provide any details on the original projection information. Instead, Hans must make an “educated guess” on which projection was being used. With a bit of research, he discovers another map from roughly the same era and displaying a similar region. Recognizing the similarities between this map, and his scanned map, Hans decides to implement a Lambert Zenithal (Azimuthal) Equal Area Projection.

Hans discovered this map from 1968, which displays approximately the same area. He chooses to use the projection information from this map to help with the georeferencing process of his scanned map.

Hans can begin his georeferencing process by first setting up a new MAP View with the Lambert Azimuthal Equal Area Projection, a conical projection used in many atlas-style maps. To help with the georeferencing process, Hans has used the Import tool to display a vector line layer of coastlines using Natural Earth DataHe can use this coastline data as a guide to help align his scanned map during the georeferencing process.

Before moving on, Hans brings up two important things one must consider when working with conical projections: the central meridian and the latitude of origin. When working with scanned maps that include graticule lines, a quick and easy way to help identify the central meridian is to look for the meridian line that closest approximates a straight line. Using the graticules on the scanned map, Hans can approximate a central meridian of about 11 Degrees. In the MAP View Editor, a user can open the projected Coordinate System Editor and modify the definition for the lambert azimuthal equal-area projection to have a central meridian that matches his estimation.

Placing the scanned map layer onto his newly modified MAP view, Hans can then begin the process of manually aligning the map image to match his projected coastline data. One of the easiest ways to support this process is to configure the MAP View editor panel to display layer thumbnails. With this configured, a user can begin manually adjusting the MAP layers until they are suitably aligned.

Hans reiterates that this process is not an exact science. He has made several assumptions on the projection parameters, and the overall accuracy of the original map. He indicates that a user should spend some time trying to get the best possible result, however it will be difficult to achieve a perfect match (especially given the distortions that can occur when a map is scanned from a physical copy). This process can take anywhere from minutes to hours, and requires a lot of manual adjustment, trial and error, and most importantly, patience! The result, however, is that the finalized scanned map layer is correctly projected and georeferenced into a MAP view. From here, adding data layers, annotations, labels, or tracing vector layers from the scanned map can all be completed in a spatially aware mapping environment.

Providing a second example using a slightly different approach, this time Hans uses a map of the Arctic Region. He indicates that although he has been provided with a map of the entire polar region, the client is only interested in the area surrounding the Bering Strait (between Russia and Alaska). As with the previous example, the first step is to identify the best projection to use. Hans correctly guesses that the map provided likely uses the Polar Azimuthal Equidistant Projection based on visual inspection. However, it should be noted that there is room for trial and error here, and users should not be afraid to explore the large coordinate system and projections library included with MAPublisher to try out and test different projections to help narrow down one that fits best.

The first thing Hans notices is that the scanned map image is rotated about -90 Degrees from what is displayed in his reference coastline data. Once again, by visiting the MAP View Editor, Hans can rotate his Map layers without breaking the spatial referencing information of his original map data. By doing this, Hans assures that his map layers are aligned on the same rotational angle, and can then begin to focus on scaling the layers.

Hans uses the MAP view editor panel to apply manual adjustments to the map layers. He notes that a cartographer should always consider the area of the map they are most interested in. For example, although his map covers the entire polar region, Hans indicates the final product will only display the regions surrounding the Bering Strait. Given this, the georeferencing process should be primarily concerned with accurate alignment in the Bering Strait area, while distortion in other areas is seen as acceptable.  In the example below, you can see how Hans has achieved a suitable level of georeferencing accuracy in his primary area of interest, despite the non-important areas (i.e the Canadian Polar region, eastern Siberia, Greenland) having relatively low georeferencing accuracy.

With his newly georeferenced scanned map layers. A cartographer can now use the information contained within these scans to supplement a larger cartographic process. For example, Hans can now use the scanned maps to digitize boundaries, or geographic features that may not be present in modern digital datasets (for example, historical boundaries for different countries, or terrain features that are no longer present)

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About the Author

Hans van der Maarel is the owner of Red Geographics, located in Zevenbergen, Netherlands. Red Geographics is a long-time partner of Avenza and Hans is a well-known power user of both MAPublisher and Geographic Imager. He uses the products for a wide range of cartographic projects for several international organizations and offers training courses and consultancy expertise aimed at developing workflows for clients. In addition to that, he is currently a board member of NACIS. To find out more about Red Geographics, and to see more work by Hans, visit redgeographics.com

Mapping Class: Georeferencing Techniques Part One – The Basics, with Hans van der Maarel

Welcome back to another exciting edition of Mapping Class, a new video-blog series where we curate tutorials and workflows created by expert cartographers and Avenza power users from around the world. For this article, we are excited to introduce Hans van der Maarel, owner of Red Geographics, and expert cartographer. Joining us from Netherlands, Hans has put together a video tutorial showcasing tips and tricks for tackling Georeferencing in a variety of different mapping scenarios. In this first part, Hans goes over the basics of georeferencing in MAPublisher, using a neat city map of Zevenbergen. Tune in for Part Two, coming soon, which will reveal how Hans approaches more challenging georeferencing tasks, including dealing with unknown projection information and working with historical maps.

Hans has produced a short video walkthrough detailing part one of his georeferencing process. The Avenza team has produced video notes (below) to help you follow along.

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Georeferencing Techniques Part One: The Basics
by Hans van der Maarel (video notes by the Avenza team)

Georeferencing is the process of taking imagery or map data that lacks geographic location information and associating it with specific coordinates on Earth. Georeferencing is a very common, but sometimes challenging step that is necessary for producing accurate, meaningful cartographic products. By georeferencing map data, cartographers can ensure that the features on their maps are located correctly, and in a way that accurately represents the real world. Georeferencing also makes it easy to add and update maps with new data layers, as location information stored within the new map layers will be accurately overlaid in the correct position on older map projects. The process for georeferencing maps can be complicated, but Hans has outlined some easy-to-follow steps for quickly performing and validating simple georeferencing tasks with vector map data.

In general, effective georeferencing needs to include at minimum three known control points. In this example, Hans has included an additional fourth control point to provide additional accuracy. 

When locating control points, it is a good idea to choose points that roughly approximate the four corners (quadrants) of your map area. Doing so can ensure the georeferencing result is accurate for the entire coverage of the map area and minimizes distortion/shearing effects as the map layers are matched to the final coordinate system. Cartographers should take time to ensure the chosen control points are as accurate as possible, as errors in control point placement will propagate across all locations in the map. Poor control point placement can lead to overall poor georeferencing accuracy. 

Using the MAP Page location tool, place four control points at known, easily identifiable locations. Hans recommends placing control points at recognizable map features that can be easily seen on the reference imagery. For this example, Hans chose to use the corners and edges of major structures (i.e larger buildings/reservoirs) or the centers of well-known major road intersections. When using road features as reference control points, Hans recommends using the center of the feature rather than the edge. This can compensate for variation in road edge placement that can occur when the vector line layer does not completely match the true road/lane width in the imagery.

Mapping Class Georeferencing control point

Next, open the Georeferencing tool and select the “Add World Locations” option. From here, use the built-in web map to calculate latitude/longitude coordinates for each of your known control points. Using the satellite imagery view can make this process easier, especially when dealing with physical features on the map (i.e building corners). Repeat this for each of the four control points.

The resulting table will show a list of set coordinates for each of these control points. From here, if you already know the projection the map data is already in, you may set this coordinate system at this stage. If you are unsure, the georeferencer tool will automatically provide a suggested list of coordinate systems that match the control points you have set. These “best” matches are provided based on measuring the error between your user set coordinates and the real-world locations on the web map. Ideally, you want the lowest combined error value. In general, the suggested coordinate systems at the top of the list are often the best choice.

Once you select the desired coordinate system, the tool will automatically create a new MAP View where you can house your newly georeferenced map data. You will notice that the MAP Page Locations you created earlier will be displayed alongside the newly georeference control points. This is a great way to help validate your georeferencing as you will be able to observe the accuracy (or inaccuracy) of your placed control points.

Finally, it is a good idea to use the Find Places tool to validate your georeferencing results. Try searching for identifiable landmarks or major features on your map (i.e. train stations). Simply search for a location using the Find Places tool, and compare this to the georeferenced locations on your map.

This concludes Part One of “Georeferencing Techniques with Hans van der Maarel“. Now that you have covered the basics of Georeferencing in MAPublisher, tune in for part two in the next edition of Mapping Class. There you will see how Hans tackles more complex georeferencing projects, including what to do when you have small-scale maps that come from scanned or printed images, or where projection or referencing information is unavailable. Hans will be using a beautiful historical map of northwest Africa to demonstrate this problem. Look for it in the Avenza Resources Blog next month.

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About the Author

Hans van der Maarel is the owner of Red Geographics, located in Zevenbergen, Netherlands. Red Geographics is a long-time partner of Avenza and Hans is a well-known power user of both MAPublisher and Geographic Imager. He uses the products for a wide range of cartographic projects for several international organizations and offers training courses and consultancy expertise aimed at developing workflows for clients. In addition to that, he is currently a board member of NACIS. To find out more about Red Geographics, and to see more work by Hans, visit redgeographics.com