Simulation and prediction of the expansion of OpenStreetMap building data based on the Markov-FLUS model in Shenzhen, China
OpenStreetMap (OSM), an open, crowdsourced geographic information platform, holds significant potential in fields like urban planning and resource management. Currently, most research focuses primarily on data quality issues, without considering the evolution of OSM buildings. This paper employs the...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
|
| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2459109 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | OpenStreetMap (OSM), an open, crowdsourced geographic information platform, holds significant potential in fields like urban planning and resource management. Currently, most research focuses primarily on data quality issues, without considering the evolution of OSM buildings. This paper employs the Markov-FLUS model to simulate and predict the expansion of OSM building data in Shenzhen. OSM building data in 2015 and 2019 were used to simulate the distribution of OSM buildings in 2023, and the distribution and completeness of OSM buildings in 2027 were subsequently simulated. The results indicate that by 2027, the growth rates of OSM buildings in Luohu and Longhua districts in Shenzhen will exceed 40%, with other areas growing by over 25%. The overall completeness of OSM buildings is projected to reach 39.99%. The simulation results can be used to identify future expansion of OSM building data in Shenzhen and support the sustainable development of OSM in the city. |
|---|---|
| ISSN: | 1010-6049 1752-0762 |