Remote Sensing, Vol. 11, Pages 2382: Estimation of Usable Area of Flat-Roof Residential Buildings Using Topographic Data with Machine Learning Methods (Remote Sensing)

The real estate appraisal largely consists of estimating the property’s value based on thetransaction prices of similar buildings with the usable area being one of the main comparative units.A Polish appraiser finds data mentioned in the Price and Value Register (PVR). However, one ofthe authors’ previous studies indicated that the PVR contained highly incomplete information onusable area of residential buildings rendering it impractical for real estate appraisal purposes. Here,we propose a machine learning method to estimate the usable area of flat-roof residential buildingsbased on Light Detection and Ranging (LiDAR) data as well as the Database of Topographic Objects(BDOT10k). First, we train models with different architectures on the exact project data of residentialbuildings available online, obtained mostly from the design offices Lipi ´nscy and Archon. Then,we apply trained algorithms on available residential building in Koszalin, Poland, using BDOT10kand LoD1 standard LiDAR data, and compare the results with usable area reported in PVR. Resultsshow that the usable area of flat-roof houses without garages and extensions can be calculated withgreat accuracy up to 4%, while for more complex flat-roof buildings-up to 4–10%, depending on howdetailed data are available. The model may be used by real estate appraisers to approximate theunknown usable area of residential buildings with known transaction prices, and as such increasethe number of properties that can be compared to the evaluated real estate. To estimate the usablearea of buildings with more complex roofs, a higher standard of LiDAR data is needed.