Course:EOSC311/2025/Rendering Complex Geological Features

This wiki article was made in June of 2025 as part of a project for EOSC 311, Earth and its Resources. The goal of the project was to explore a connection between Geology and the student's major. In my case, that's computer science.

Introduction

It goes without saying that most if not all of the major geological discoveries of the recent decades have involved the use of data collected in the field. Raw data though, is seldom useful without some way to interpret it. A key step in the interpretation process is visual exploration. It's hard to come to any solid conclusions (or even know what to look for in the data) without a way to get a good high level look at said data.

Geological processes are incredibly complex, often spanning vast stretches of time and space. Because of this, the best way to make sense of the information gathered is often by turning it into something we can see, manipulate and analyze it in an intuitive way. Whether it's satellite imagery or seismic readings, visualization turns the raw numbers into meaningful insight and conclusions about the way the world works.

Thankfully, we live in the age of skilled programmers, powerful graphics cards, and more recently, an explosion of advancements in the field of machine learning. We're now able to produce sophisticated, interactive, and layered geological maps that not only look impressive but actively inform scientific decisions and public policy.

This article explores how this transformation happens: from the basics of geological mapping, to the role computer science plays in making sense of it all, to the technologies enabling groundbreaking ;) discoveries. At the end, we'll also look at real-world applications, where accuracy of these digital maps is paramount.

Mapping Basics

Maps are the primary medium for displaying geological data. The specific geological information (such as rock types/age) will generally be overlaid on top of a regular map. This way, geologists can use their existing knowledge of a particular area to make connections to the new data they're analyzing.

William Smith's Geological map of Britain (1815)

Therefore, geological maps are one of the most fundamental tools in the earth sciences. These maps provide a visual summary of what lies below our feet. This helps scientists, engineers and policy makers make practical decisions based on the physical history of a region. These maps can show more than just the type of rock at a given place. There are maps of fault-lines, folds, mineral resources and groundwater flow. These MRI's of the earth allow us to get a glimpse at the hidden structure of Earth.

The origins of geological mapping date back to the early 19th century. William Smith's map of England, published in 1815, is widely considered the first national geological map. Without the modern mapping tools and technology available to us today, Smith had to do it all by hand. His key observation was that the combination of fossils encased in a rock were enough to identify that rock. It took Smith 14 years to gather the information required for his map of England. Despite the technological limitations of the time period he was living in, Smith managed to produce a remarkably accurate map. Geological maps of Britain made today still look very similar.

That being said, the technology has changed dramatically since Smith's time. Aerial photography, satellite imagery, LIDAR, and remote sensing have all become integral parts of a mapper's toolkit. With the advent of Geographic Information Systems (GIS), geological maps are now created, analyzed and shared digitally. GIS will be explained in more detail in a later section. It has become much easier to overlay different datasets (like topography, seismic activity, rock age) onto the same map, allowing for more nuanced interpretation. This also means that when new data comes in, it is easy to incorporate it with existing maps.

Mount Baker and geological data of surrounding area. Screenshot from Google Earth

For anyone curious to explore these kinds of maps firsthand, the United States Geological Survery (USGS) provides an excellent tool for viewing a compilation of geo-maps of the United States. I urge you to try downloading one of the maps listed on the left side (make sure to pick the KMZ files) and opening them in Google Earth. This way, you can see the maps in 3 dimensions, overlaid on top of Google Earth's excellent topographical data.

In short, geological mapping has come a long way—from hand-drawn sketches to multi-layered, data-rich digital systems. Yet the goal remains the same: to better understand the physical world we live in, and to use that understanding to solve real-world problems. The tools have changed, but the science continues to build on the work of generations past.

Computer Science in Geological Mapping

Behind every interactive map of geological data is a significant amount of computational work. Computer Science plays a key role in how the data is stored, processed and visualized. Well designed software is required to make practical use of field data and easily share it with others.

Efficient Rendering

One of the main challenges in geological mapping is managing large and often complex datasets. Geological surveys can generate terabytes (1 million megabytes) of data. Satellite imagery and LIDAR scans are especially heavy dataloads. The problem doesn't just come from needing to store this much data, that part is easy. The real issues come with trying to visualize, manipulate and share complex and large datasets. Rendering large datasets can take a lot of time if not done efficiently, reducing the usability of the data the slower it becomes.

We see here, as in many other areas of computer science, the trade-off between space and time. In the context of geological mapping, this presents itself as the trade-off between map resolution and system performance. The higher the resolution of a map, the longer it will take to perform operations on the data, such as querying the data, loading it or even rendering the data so we can get a good sense of what its composed of.

Use of an LOD system on a render of a house

One technique that is used throughout mapping most software to allow for high-resolution maps without the lag that comes with viewing terabytes of data at once, is to use multiple levels of detail (LOD) otherwise known as "generalization". When the user is looking at an entire dataset worth of data on a map, we show them a low-resolution version of the data. When the user zooms into a particular mountain range, we can show them a medium-resolution version of the mountain range. Finally if the user is looking at a particular peak on the mountain range, we can show them the high-resolution scans of that particular peak, without wasting computation on the parts they are focused on.

Format Compatibility

Another core issue is interoperability. Geological data often comes with a mix of sources and must be made compatible across systems. Of course, there is more than one way to represent the same information in code. Some ways are better than others and it usually depends on the context. Some important file formats:

• GeoTIFF: This is an image format that contains geographical information so it can easily be mapped to a specific location on Earth.
• KML/KMZ: This file format is used to display geographical features in a map viewer, such as Google Earth. It can contain waypoints, paths and complete image overlays (as mentioned in the Mapping Basics section).

Anyone working on software projects that deal with geological rendering need to be aware of the different formats and their respective benefits / drawbacks. Building systems that can integrate with these standards is a classic computer science problem. It requires robust parsing, error handling and adherence to the specific standards of the aforementioned file formats.

Key Technologies

At the heart of the modern geological mapping world is a suite of tools that make handling geological data much easier. As mentioned previously, GIS systems are chief among these. According to Esri (the creators of ArcGIS):

GIS is a technology that is used to create, manage, analyze, and map all types of data. GIS connects data to a map, integrating location data (where things are) with all types of descriptive information (what things are like there). This provides a foundation for mapping and analysis that is used in science and almost every industry. GIS helps users understand patterns, relationships, and geographic context. The benefits include improved communication, efficiency, management, and decision-making.

GIS has become the backbone of spatial data analysis in geology and countless other fields. A GIS allows researchers to overlay and compare different types of spatial data such as rock types, fault lines, elevation, all within a single interactive environment.

One of the most widely used GIS platforms is ArcGIS, developed by the company Esri. ArcGIS provides a vast set of tools for handling geological / geographical data. They have an online platform where anyone can browse and overlay numerous publicly available datasets.

As previously shown, Google Earth Pro (free) is also a deceptively powerful tool. With Google Earth, you can import Geological data via KML/KMZ files. The advantage with Google Earth Pro is the high definition imagery and elevation models provide an accessible way to explore geo-features without needing to deep dive into a full GIS environment.

Other important tools in the geological mapping toolkit include QGIS, a free open-source alternative to ArcGIS. For those unaware, open-source software is software whose "source-code" is available to the public to see and use.

Real World Applications

While it is a lot of fun to explore geological maps through Google Earth and GIS systems, these modern tools also have tangible benefits to society from safer buildings to life-saving disaster planning.

GIS for urban development

In Oviedo, Spain, a GIS-based geotechnical system was developed to integrate the data from thousands of tests conducted in the city into a single relational database. The resulting maps classify "man-made grounds, fluvial sediments and residual soils" as well as the "identification of unreported faults". Alongside the GIS system, a 3D subsurface model. This research effort will help future engineers / construction crews get a better sense of the ground they would be building on.

Targeting ore deposits with mineral prospectivity mapping

In Alaska, USA, GIS datasets have revolutionized mineral exploration. For example, the USGS deployed GIS models to predict areas rich in 6 different mineral deposit groups. Among these groups are rare earth elements, platinum groups, copper deposits and uranium deposits. The study discovered "numerous" large areas rated with a high potential to contain some of the groups that were selected.

Earthquake vulnerability mapping

GIS-informed seismic risk mapping in Dhaka, Bangladesh used road-network models to highlight regions where emergency response will be delayed. The researchers combined field data with satellite data to determine a "vulnerability score" for several buildings in Dhaka. Then, with the help of ArcGIS, the average response time of emergency services is calculated, taking into account the road networks road widths. The researchers make recommendations on how to improve safety for the people living in this crowded city.

These cases illustrate how combining field observations with computer science and GIS creates maps that anticipate guide and protect. Whether it's helping decide a location for a new building, pinpointing a source of a valuable resource or preparing cities for earthquakes, computer-aided geological mapping is saving resources, money and lives.

References

This Earth Science resource was created by Course:EOSC311.