District heating networks are a critically important part of urban infrastructure, ensuring stable heat supply to residential buildings, schools, hospitals, and businesses. They consist of an extensive system of pipelines, mostly laid underground, that deliver heat from the generation source to the end consumer.
Despite their importance, heating networks remain virtually “invisible” to city residents—until a leak, rupture, or localized defect occurs. In such cases, the entire system becomes vulnerable, increasing the risk of accidents, energy loss, and costly maintenance. This creates an urgent need to update the approach to planning, monitoring, and repair.
This case study demonstrates how 3D mapping can be used to create a detailed digital model of a section of heating infrastructure based on images captured by drone and smartphone with LiDAR. The data was processed using an ASUS ROG G513QY-HQ008 laptop, equipped with an AMD Ryzen™ 9 5900HX processor and AMD Radeon™ RX 6800M graphics card, along with professional Pix4D software.
Benefits of creating digital Maps of Heating Networks
Using 3D mapping in heating network management significantly improves design quality, reduces operational costs, and increases maintenance efficiency. Digital models provide engineers with precise spatial data that can be immediately used in project modeling.
International experience (e.g., HSC, Singapore) shows that 3D mapping can:
- Reduce the number of test excavations by 30–50%
- Cut annual inspection costs by up to $1.8 million
- Reduce fieldwork duration by 67,200 hours per year
- Increase overall pipeline installation productivity by 5%
Thermal imaging drones play a special role: they detect zones of abnormal heat radiation, often indicating hidden defects—damaged pipe insulation, leaks, or overheated areas. Data that previously required excavation is now available remotely and quickly, without disturbing surfaces or stopping traffic.
How the 3D Mapping Process Works
A 3D map is an accurate digital terrain model that allows users to view the condition of an area or object with centimeter-level precision. For heating networks, this means not only designing new sections but also detecting defects in existing pipelines, enabling preventative repair planning and avoiding emergencies.
Creating a 3D surface map with Pix4D involves:
- Capturing images of the area using a drone or LiDAR-equipped phone.
- Uploading images and accompanying data; the software reads positioning and orientation info.
- Aligning and matching identical points: the software analyzes images, finds common points, and determines distances based on image orientation.
- Processing hundreds of images and identifying thousands of points to create a sparse point cloud—this becomes the foundation for the future 3D map.
- Building a dense 3D point cloud, integrating and validating LiDAR data (if available), and removing erroneous values.
- Triangulating points to form a continuous surface, then texturing it using photo data to generate a complete 3D surface model with texture.
Laptop Test with AMD Ryzen™ 9 5900HX Processor
Processing geospatial data, 3D modeling, and real-time analysis require high computing power and stability. A powerful laptop is essential for fast, efficient Pix4D performance.
For this case, the ASUS ROG G513QY-HQ008 was used, featuring the high-performance AMD Ryzen™ 9 5900HX processor with 8 cores and 16 threads.
Calculations using the AMD Ryzen™ 9 5900HX were fast and efficient. The laptop’s 1 TB SSD proved valuable for storing large, graphic-heavy files. It passed testing successfully and was well-suited for building 3D models of heating networks.
This case confirms that 3D mapping is evolving from an experimental tool into a fundamental element of modern engineering. Its importance goes beyond isolated use cases—it’s reshaping the entire paradigm of urban heating infrastructure planning and management.
The key value of the technology lies not only in accurately replicating spatial objects but also in integrating real-time data into technical decision-making.
Models created through photogrammetry and LiDAR scanning enable engineers to interact with assets digitally—just as they would physically—but with much greater efficiency, time savings, and safety.
Looking ahead, the implementation of 3D mapping will foster a fundamentally new approach to managing heating networks—focused on preventive action, forecasting technical conditions, and building integrated digital infrastructure. This is not just a technological upgrade, but a transition to a new level of critical urban infrastructure management.
