Estimates show that nearly 75% of the world's population still does not have access to formally accepted land registration systems. According to UT PhD student Sophie Crommelinck, cadastral mapping can be automated using an intelligent and interactive computer program she developed and described in her thesis. As a result, parcel delimitation takes 38% less time.
A large part of the world does not yet have reliable land registration systems, including several East African countries. The lack of cadastral registered land rights leads to uncertainty about land ownership and sometimes to life-threatening conflicts. Documenting borders is often the most expensive part of a land administration system. "You need a lot of technically trained manpower to perform cadastral measurements, but also expensive technologies to measure the borders," says Crommelinck.
Interactive computer program
In her dissertation, Crommelinck describes a computer program that uses the same techniques as facial recognition software. She uses these techniques to recognise physical land borders on satellite, aerial and drone photography. "This system can be applied in areas where boundaries are defined by physical objects such as fences, walls, hedges, roads, buildings or rivers. The objects must be visible and there must be a need for cheaper land administration approaches, as is often the case in Kenya, Rwanda and Ethiopia," says Crommelinck. Using machine learning, the program ‘learns’ which objects in the photos are likely to indicate land borders.
Ultimately, her research leads to a process in which one person indicates the definitive boundaries in an interactive program. First, the program calculates the most probable land borders, after which someone with knowledge of the area selects the right plots. The system was tested on satellite, aerial and drone photos of parcels spread over Ethiopia, Rwanda and Kenya. "We show that our approach is less labour-intensive and more efficient than manual demarcation," says Crommelinck. Not only does it require 38% less time, but it also requires 80% less clicking per plot.
Crommelinck's research is part of the EU project its4land. Its4land develops innovative applications for land registration. The Faculty of ITC (Geo-informatics Sciences and Earth Observations) of the UT is the leading partner of this project. More information and a short animation about its4land can be found on their website.
Sophie Crommelinck carried out her research under the supervision of Prof. Dr. George Vosselman in the Department of Earth Observation Science (Faculty ITC). The public defence of her thesis will take place on Friday 25 October 2019. The digital version of her thesis titled Automating image-based cadastral boundary mapping can be downloaded.