Point clouds from aerial imagery for valuation and taxation
At the end of 2017, we were approached by TOG Netherlands. TOG is the market leader for WOZ-valuations in the Netherlands. They support around 80 municipalities in their yearly WOZ-valuations. To carry out these valuations, they make use of 3D information to determine the volume and surface area of buildings. In the past they used point clouds of the entire country produced by laser systems (LiDAR) mounted on airplanes. This data is available nationwide in the Netherlands. However, it can be up to 8 years old.
TOG was looking for a third party that could generate similar point clouds from aerial imagery. In this way they could have the most up-to-date and accurate data available. At the time of writing, more than 10 municipalities make use of our point cloud data from aerial imagery through the VRiS-tool of TOG.
In this use case, we will give a more detailed explanation of the use of point clouds in WOZ-valuations.
The yearly WOZ-valuation
Dutch municipalities determine the value of real estate every year; the WOZ-valuation. Among others, the WOZ-valuation determines the price of a number of taxes and levies. It is therefore crucial that this valuation is carried out as accurately as possible.
From the 1st of January 2022, municipalities are obliged to value real estate based on floor area. In the past, valuations were often done based on building volume. This legal change requires a lot of effort to change the data supporting the valuation. The law allows to audit 20% of all objects per year. Many municipalities use this to spread out the transition across 5 years. This makes it more easy to manage.
TOG Netherlands supports municipalities in the valuation process with its VRiS ‘3-D-tool’. With this tool, municipalities are able to precisely calculate building volume and floor area themselves. This is done by relying on LiDAR data (more precisely, the ‘Algemene Hoogtekaart Nederland’ or General Height Map of the Netherlands, which is collected through LiDAR and has an update cycle of about 8 years)
Overcoming shortcomings of LiDAR data with point clouds
The usage of AHN LiDAR data has a number of disadvantages. The first one is that the data is often outdated. New buildings and additions, like dormers, are often not included in this data. Trees are also not excluded from this dataset. This leads to overhanging trees being included in the volume calculation of houses. Which, in turn, leads to an overvaluation of the real estate. Readar has developed a method to generate point clouds from stereo aerial imagery with the usage of Semi-Global Matching.
Readar has slightly adjusted this method for TOG for it to be useful in their VRIS 3D-tool. The tool can now retrieve the data using the API provided by Readar. We also filter out any trees from the data, such that they will not be included in building volume calculations.
Recognition from the ‘Waarderingskamer’
The ‘Waarderingskamer’, or ‘property assessment board’, monitors and assesses municipalities on their execution of the law ‘Wet Waardering onroerende Zaken’ and has given some attention to our cooperation with TOG Netherlands in the WOZ journal. In the WOZ journal, an extensive report can be found on how the municipality of Bergeijk uses the tool. Interested in this report? It can be found in the WOZ journal of September 2018 which is available here.
Currently more than 10 municipalities used our data to value all real estate within their borders. From this we have learned valuable lessons to further improve the method. For example, we have already fine-tuned the ‘tree filter’, to make sure more trees are removed. By now we have also developed a method to generate point clouds using Deep Learning. This allows for a much larger coverage of the point cloud data (less gaps) when compared to Semi Global Matching. This means that less interpolation/interpretation is needed, which improves the reliability of the valuation even further.
Interested in using point clouds?
Interested in using point clouds, height data or other property information? Please contact us via: firstname.lastname@example.org.
You can also find more information on point clouds and our other products in our productsheet.