Geospatial data for civil engineering

Civil engineers and urban planners are tasked with the development, maintenance, and improvement of infrastructure, all of which require an in-depth knowledge of both the manmade and natural environments. Geospatial data and geographic information systems (GIS) enable civil engineers to map landscapes, analyze infrastructure, and model scenarios digitally. These workflows complement more traditional civil engineering practices such as surveying and drafting to enhance project efficiency and outcomes.

Geospatial data is used by civil engineers and planners in both the private and public sectors. For example, a civil engineer working for a department of transportation (DOT) may use GIS to map sidewalks in a community and better understand their accessibility, informing expansion plans. Similarly, a DOT may hire a professional from a civil engineering firm to execute this project for them. In either case, geospatial data is an essential tool for civil engineers as they analyze the physical world and develop new solutions for adapting infrastructure to meet society’s evolving needs.

Top 4 use cases for geospatial data in civil engineering

There are many different applications of geospatial data and GIS in civil engineering. At Ecopia AI (Ecopia), we work with planners and civil engineers specializing in a wide variety of disciplines. However, we tend to see geospatial data used most commonly for four specific civil engineering project types: transportation planning, stormwater management, telecommunications, and utilities. 

Transportation planning

Transportation infrastructure requires constant maintenance and improvements to ensure it meets safety standards and community demand. Civil engineers leverage GIS to map out and better understand transportation networks, using geospatial data to represent specific features for analysis. For example, geospatial data layers used by civil engineers for transportation planning can include individual traffic lanes, medians, crosswalks, and intersections. Even surrounding land cover data can be analyzed to provide further details about transportation networks; many civil engineers are conducting tree canopy analysis near bus stops to understand how urban heat impacts mass transit accessibility and safety. 

With these detailed geospatial data layers, civil engineers can perform analytics to support various transportation planning initiatives. In general, these initiatives focus on three main priorities for transportation infrastructure: safety, accessibility, and sustainability. For instance, civil engineering firms are often contracted by government agencies to support Vision Zero or active transportation planning goals. Additionally, civil engineers are integral parts of multimodal network analysis, Americans with Disabilities Act (ADA) compliance, and green infrastructure planning. All of these applications require high-precision geospatial data that digitally represents transportation infrastructure.

Stormwater management

Stormwater infrastructure is typically managed by civil engineers specializing in hydrology. With geospatial data representing land cover, particularly impervious surfaces, civil engineers can understand how precipitation events will impact a community. Comprehensive, accurate, and up-to-date impervious surface data (representing land cover types that do not absorb water, like asphalt or concrete) enable civil engineers to model stormwater scenarios and analyze the capacity of current drainage infrastructure. This is particularly important as both the intensity and frequency of climate events increase, land use changes, and drainage systems age.

Civil engineers specializing in stormwater management are often contracted by municipalities to either develop or enhance a stormwater utility fee (SUF) program. In a nutshell, SUFs are fees established by public works departments to fund drainage system maintenance and improvements. SUFs can be calculated a few different ways, but many municipalities leverage impervious surface data to charge a fee based on a property’s contribution to runoff. Civil engineers are frequently behind the scenes of municipal stormwater programs, leading the geospatial analysis and data implementation that establishes SUF structures. Similarly, civil engineers use geospatial data to support municipal stormwater efforts on flood modeling projects that improve understanding of climate risk, boost resilience, and place less strain on infrastructure.

Telecommunications

Telecommunications infrastructure is also managed by civil engineers. From identifying new areas for network expansion to laying or repairing broadband or fiber cables, civil engineers work with geospatial data to understand and plan telecommunications network infrastructure. Government organizations typically hire civil engineering firms for telecommunications work to improve the connectivity of their region for residents, workers, and visitors.

The type of geospatial data needed for these projects varies based on the specific goal. For instance, a state looking to expand broadband internet access to more communities may hire a civil engineering firm to identify broadband serviceable locations (BSLs), which would require a comprehensive building footprint and geocoded address database. Alternatively, a civil engineer working with a municipality to enhance 5G connectivity would need accurate 3D building, tree, and bridge data to understand how signals could be impacted by tall infrastructure.

Utilities

Utility work is another specialty area for civil engineers. Planning out, laying, and maintaining the right-of-way of utility networks requires mapping technology and data to strategically understand where infrastructure should go based on demand and environmental considerations. Civil engineers often use utility map data in GIS for these purposes, but also layer in land cover data to provide necessary context for construction work. For example, knowing where a protected wetland area is located is crucial for planning utility work for a neighboring apartment complex. 

Another utility use case rapidly rising in popularity among civil engineers is mapping out road markings to expedite construction permitting. When conducting underground utility projects for municipalities, civil engineers must secure permits from local authorities and be sure to restore road markings after asphalt is repoured upon project completion. Having an up-to-date map of these road markings before beginning underground work helps increase project efficiency, and geospatial data provides all of the necessary information about paint striping that can be difficult to glean from imagery alone.

6 types of geospatial data in civil engineering

As the physical world is made up of many diverse and dynamic elements, digitally capturing the details needed for civil engineering projects requires a variety of geospatial data types. While essentially all geospatial data is applicable in the civil engineering industry, the following six types are most commonly used for transportation planning, stormwater, telecommunications, and utility projects. 

Transportation features

Vector data denoting specific transportation network features is frequently used by civil engineers to understand the safety, accessibility, and sustainability of transportation infrastructure. For example, map data layers that identify different types of crosswalks and their widths are critical for analyzing pedestrian network access and safety. Similarly, mapping out individual lane types provides insight into why traffic jams or accidents may be more likely to occur in one area over another. 

Impervious surfaces

Helpful for both stormwater management and general infrastructure sustainability analytics, impervious surface data enables civil engineers to understand how runoff will impact a project area. Impervious surface data can be used in either raster or vector format for geospatial analysis, although vector layers provide the highest precision and granularity. With data layers that differentiate between types of impervious surfaces, such as roads, buildings, parking lots, and sports grounds, civil engineers can assess the environmental risk of communities and develop or enhance infrastructure to be more resilient to flooding and similar hazards.

Land cover

While impervious surfaces tend to get the most attention, civil engineers also often use full land cover data that includes pervious surfaces. Comprehensive land cover data provides deeper context for a variety of civil engineering applications, from transportation planning to telecommunications and beyond. For instance, stormwater management projects can benefit from the addition of pervious surfaces as civil engineers can see how natural features reduce runoff risk. Likewise, seeing the full land cover surroundings of a public transit network helps indicate where infrastructure needs to be improved for resilience and sustainability. Land cover data is most useful for civil engineers when in a vector format, but can sometimes be leveraged in raster format as long as the pixel size is granular enough to provide sufficient detail.

Building footprints

Another layer commonly used by civil engineers is building footprint data. Building footprints provide a 2D representation of property structures, and are helpful for a wide range of civil engineering applications. Building data is particularly useful for telecommunications and utility projects, as they indicate where services can be provided. Additionally, analyzing building footprint locations with other geospatial data, such as land cover or existing utility lines, informs project decision-making by providing more context about specific locations. 

3D buildings

While 2D building footprints are extremely valuable for many civil engineering projects, 3D buildings can add even more infrastructure detail, particularly for telecommunications applications. Rolling out 5G network coverage across a geographic area requires knowledge of how signals will be impacted by infrastructure, and 3D building data is becoming increasingly popular for civil engineers seeking to understand these constraints. 3D trees and bridges are also helpful for planning telecommunications networks, as they too can affect signal strength. 

Geocoding

Building data is a critical foundational element of most mapping projects, but many civil engineers also require geolocated address information associated to those buildings. Geocoding data links an address string to a set of latitude and longitude coordinates so that addresses can be mapped. Civil engineers use this added context to link relevant property information with the geospatial data they are analyzing. For example, a civil engineering firm working for a state government to increase internet access by identifying broadband-serviceable locations needs a geolocated address database to understand not only where structures exist, but also where the network can be expanded.

Imagery

One of the most powerful types of geospatial information available to civil engineers is imagery captured by satellites, planes, street-view cars, and even drones. Imagery provides snapshots of the real world that can be helpful basemaps for civil engineering projects, and many teams also analyze imagery to create data. When combined with the flexibility and usability of vector or high-resolution raster data, imagery helps civil engineers develop a digital, comprehensive view of their project area without even visiting the site in-person.

Where to get geospatial data for civil engineering projects

The civil engineering profession has existed in one form or another for centuries, although the application of geospatial data has occurred in more recent decades. There are many ways to collect and source geospatial information for the wide variety of projects civil engineers are engaged with, ranging in technical complexity, accuracy, and efficiency. 

Surveying

Perhaps the most well-known method of collecting geospatial information in civil engineering is surveying. Surveying requires civil engineers to physically visit their project area and record measurements for all relevant information. Sometimes this can be done via drone or even a geospatial surveying app, but even with these more advanced methods, surveying is an extremely labor-intensive process. This is especially true over large project areas, where physical surveying could take so long that data collected at the beginning of a project can become stale and unusable. However, surveying can be beneficial for hyper-local projects where in-person assessment can supplement geospatial data analysis.

Manual digitization

The traditional way to create geospatial data requires GIS analysts or civil engineers themselves to manually trace features from imagery into digitized vector data. This process is not only extremely resource-intensive, but also can lead to inconsistencies if performed by multiple individuals. This is because people interpret imagery uniquely, and may have slightly different methodologies for digitizing vectors than their peers. Manual digitization is best used for one-off feature creation, since the time it takes to manually trace and classify all relevant features for a project can cause data to quickly become stale. For example, it took Fehr & Peers 6 months to manually digitize only 4% of San Bernardino County’s sidewalks for active transportation planning analysis. Over large areas, manual digitization is simply not feasible.

Open source

The advent of geospatial technology has led to an increase in openly available data for many geographies around the world. Open source data is a valuable tool for educational purposes and sharing high-level information, but cannot be relied upon for accurate analysis. This is because open source data is generally not monitored by any data governing standards, is often created through crowd-souring methods, and is not updated regularly. As a result, open source data lacks the completeness, accuracy, and freshness civil engineers require for their projects.

Third-party providers

As GIS has become more pervasive across industries, more and more companies devoted to geospatial data creation are now providing civil engineers with the ability to source high-precision data for their projects. Third-party data providers typically have standardized schemas, methodologies, and update schedules, meaning the data they provide is more comprehensive, accurate, and up-to-date than open source options. However, not all data providers have the same commitments to quality as civil engineers, so it’s important to carefully evaluate data before fully integrating it into an analysis.

Harnessing the power of AI for civil engineering

Thanks to advancements in artificial intelligence (AI), it’s now possible for civil engineers to source third-party data created at scale that meets their high quality standards. Ecopia’s AI-based mapping systems ingest imagery from our global partner network and extract vector features with consistent GIS-professional accuracy, so civil engineers can scale their engagements and ultimately deliver more value from project hours to their clients. 

To give you an idea, we were able to help Fehr & Peers scale their mapping of transportation features in San Bernardino County by 45x, with data now powering decision-making in active transportation planning, ADA compliance, and bike and pedestrian safety analysis. Similarly, Ecopia was able to scale impervious surface mapping by 18x for the City of Detroit, uncovering more than $5.6M in missed annual stormwater utility fee revenue. Our Building-Based Geocoding data even helped Dewberry secure around $1B in broadband equity funding for both Alaska and Arizona. By working with Ecopia, these organizations were able to scale their projects without sacrificing quality, achieving objectives by devoting project hours to strategic analysis rather than tedious data creation.

If you’re looking to scale your own civil engineering projects with high-precision geospatial data, get in touch with Ecopia’s dedicated civil engineering team.