Cadastral data collection and land allocation is a key requirement in the world system of today.
In Laos, a complete dataset of the country remains missing and is continuously being updated. There is a central database (LaoLandReg) which is gradually being supplemented with paper forms. Land rights are scanned analogously with fingerprints and signatures and painstakingly entered into LaoLandReg.

This presentation will outline the project that has been ongoing for the last year in collaboration with the Laotian Ministry of Land Management, commissioned by KfW, to fully digitize cadastral management. The goal was to make the entire process more efficient, transparent, and future-proof.

Current Status:

Currently, copies of the central LaoLandReg database are distributed to the individual provinces and used offline on local computers. State personnel use GPS devices to record the corner points of buildings and land parcels on-site. Attribute data, fingerprints, and signatures of neighbors are also collected. This information is then manually entered into the local database and, after several months, transmitted to the central system – a time-consuming and error-prone process.

The Solution: Don't despair – ask Open-Source GIS! Using QGIS, QFieldCloud, and QField, in particular, we automated and optimized this complex workflow. Intelligent workflows, data linking, and flexible layouts make the entire process now significantly more efficient and transparent.

Special Feature:
Thanks to this project, the new feature of COGO - Coordinate Geometry found its way to QField. COGO is a framework that allows you to define a precise location of any spatial feature, making use of mathematical functions and measurements.

Precise localization in urban areas, can be tricky despite having accurate GPS devices. Urban canyons may lead to interrupted and reflected satellite signals making navigation unreliable und imprecise.

This presentation will present the outcome of the ongoing European Horizon Initiative Egeniouss. In a consortium of more than 10 partners we have worked more than three years to get to the point where we can locate ourselves within 10 cm's in urban areas without adding an external GPS Device.
The project’s mission was to harness alternative data sources and develop a cloud service based on novel multi-sensor navigation with a tightly integrated visual localisation component to overcome known GNSS issues and augment existing EGNSS services. Following, this service is made available through a dedicated API. To validate our approach, we defined three real-world use cases to test the reliability and accuracy of the service.
We’ll showcase one of these used cases and explain how Egeniouss has been integrated into QField via its innovative plugin framework.
The presentation will cover the journey of egeniouss alongside QField and how both were constantly improved to finally serve the same groups of end-users.
New features which were specifically developed to finally meet the needs of the end-users of the egeniouss service in the urban areas, will also be presented.