Mapping Ground Points in Senegal for Imagery Stereo-Preparation

June 28, 2023
Jan Paulovic
Ryan Aherin

About IGN FI

Valentin is a photogrammetry and LiDAR expert for IGN FI, which used to be  the international branch of the French National Institute of Geographic and Forest Information before the ownership of GeoFit group. IGN FI produces geographic data for international projects to support decision-makers on topics such as cartography, geodesy, land administration, environmental protection, agriculture, forestry and security. Many IGN FI projects are built from the ground up, meaning that they have to collect data, process them and deliver a finished product to the client. 

Creating a large database of ground control points (GCP) information for stereo-preparation

Valentin was overseeing a large-scale stereo-preparation project in Senegal in order to adjust aerial imagery and LiDAR with recognizable ground control points. The stereo-preparation comes before the bundle adjustment and all following photogrammetric steps leading to the creation of large digital terrain models for flood hazard maps. The project required his team to record over 1,000 GCPs. In order for these to be correctly identified on images, each point needed detailed information such as the exact time that the point data was collected, GNSS antenna height and a photo of the point location as well as exact matching between the measured object and the image observation.

In the past, this would have been done by sending workers out to get GNSS readings in the field and record the points with pen and paper. This would then have to be digitised manually. The process was time consuming and increased the opportunity for user error. 

Due to the complexity and scale of the project, a digital solution was needed to improve organisation and simplify the process. Furthermore, the local partner in Senegal wanted the new project to use more modern technology such as mobile phones and computers.

Easy setup between Mergin Maps and QGIS

Mergin Maps allowed Valentin to create a project in QGIS with a GeoPackage layer for the ground control points (GCP). He also created forms for collecting the GCPs and attributes that could be filled in using the Mergin Maps mobile app and synchronised to the QGIS project without any extra plugins being needed. Using Mergin Maps, the attribute data is automatically attached to the GCPs when they are collected in the field, meaning that this did not have to be done back at the office. 

Valentin used Mergin Maps to collect and organise the GCP data much quicker and with less opportunity for error than before. Due to the ability to copy and paste forms in Mergin Maps, he was able to develop a template for the collection of GCPs and their attribute data and reuse this across multiple projects in the country.  

Field deployment of the Mergin Maps project improved collaboration

One of the biggest benefits of using Mergin Maps for Valentin was the ability to coordinate the project from France with the field workers in Senegal due to the seamless use of synchronisation in Mergin Maps. The field workers could record a GCP and upload it to the project and he could validate it in real time from France.

The simplicity of using Mergin Maps was also a huge benefit for the project. According to Valentin, “The workers in Senegal had never used Mergin Maps before and they were able to operate the app, even before I had shown them.”

Using Mergin Maps to collect the field data saved time and reduced error

IGN FI were successfully able to collect GCPs for their partner in Senegal that are easy to hand off to their local partner for future development. The ability to create templates and deploy them to workers in the field in a way that is straightforward meant they did  not have to spend as much time processing and cleaning the data post-collection. 

Due to the success of this initial project, Valentin is considering several other projects where he could use Mergin Maps for CORS recognition  in Togo and another project to collect ground-truth data for hydrology and flood models.

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