Semi-supervised Learning from Street-View Image and OpenStreetMap for Automatic Building Height Estimation
Accurate building height estimation is key to the automatic derivation of 3D city models from emerging big geospatial data, including Volunteered Geographical Information (VGI), where a low-cost and automatic solution for large-scale building height estimation is currently missing. More recently, the fast development of VGI data platforms, especially OpenStreetMap (OSM) and crowdsourced street-view image (SVI), offers a stimulating opportunity to fill this research gap. In this work, we propose a semi-supervised learning (SSL) method to automatically estimate building height from Mapillary SVI and OSM data, which is able to create low-cost and open-source 3D city models in LoD1.
Specifically, the proposed method consists of three parts: first, we propose an SSL schema with the option of setting different ratio of "pseudo label" during the supervised regression; second, we extract multi-level morphometric features from OSM data (i.e., buildings and streets) for the purposed of inferring building height; last, we design a building floor estimation workflow with a pre-trained facade object detection network to generate "pseudo label" from SVI and assign it to the corresponding OSM building footprint.
| Abbr. name | Definition | Range/ Unit |
|---|---|---|
| Building* | ||
| area | Area of the building | meter |
| perimeter | Perimeter of the building | meter |
| circularcompactness | The ratio between the area of the building footprint and the area of the circumscribed circle. | [0, 1] |
| longestaxislength | Length of the longest axis of the building footprint. Axis is defined as a diameter of minimal circumscribed circle around the convex hull. | meter |
| elongation | Elongation of the minimum bounding box around the building footprint. | [0, 1] |
convexity |
Area of the footprint divided by the area of the convex hull around the footprint. | [0, 1] |
| orientation | Orientation of the longest axis of bounding rectangle in range 0 – 45. It captures the deviation of orientation from cardinal directions | degree |
| corners | Calculates number of corners of the building. | count |
| sharedwall | Length of wall shared with other buildings. | meters |
| Block* | ||
| Features of buildings in blocks | ||
| blockcount | Number of buildings in the block that the building is part of. | count |
| avBlockFootprintArea | Average footprint area of buildings in the block | squared meter |
| stdBlockFootprintArea | Standard deviation of footprint areas of buildings in the block. | squared meter |
| blockTotalFootprintArea | Total building footprint of the block. Unit: squared meters. | squared meter |
| Features of block itself | ||
| BlockPerimeter | Total perimeter of the block. | meter |
| BlockLongestAxisLength | Length of the longest axis of whole block footprint. | meter |
| BlockElongation | Elongation of the minimum bounding box around the whole block footprint. |
[0, 1] |
| BlockConvexity | Convexity of the whole block footprint. | [0, 1] |
| BlockOrientation | Orientation of the whole block footprint. | degree |
| BlockCorners | Number of corners of the whole block footprint. | count |
| Street & intersection* | ||
| closeness500 | Local closeness centrality for the closest street to the building. | [0, 1] |
| betweenness | Betweenness centrality of the closest street to the building. | [0, 1] |
| global_closeness | Global closeness centrality of the closest street to the building. | [0, 1] |
openness |
Openness of the closest street to building. Proportion of the street where buildings are or not present on the sides of the street. | [0, 1] |
| width_deviations | Standard deviation of the width of the closest street to the building. Width is defined here as the average distance between buildings on both sides of the street. | meters |
| widths_street | Width of the closest street to the building. | meters |
| lengths_street | Length of the closest street to the building. | meters |
| distance_road | Distance between the building and the closest street. | meters |
| distance_intersection | Distance between the building and the closest intersection. | meters |
| Street-based block* | ||
street_based_block_phi |
Anisotropy index of the street-based block at the building location. | [0, 1] |
| street_based_block_area | Area of the street-based block at the building location. | squared meter |
| * 50,200,500m buffers applied and the mean and std values were calculated. |
Dr. Hao Li
Email: hao_bgd.li@tum.de
Technische Universität München, Dartment Aerospace and Geodesy
Professur für Big Geospatial Data Management
Lise Meitner Str. 9, 85521 Ottobrunn