
Fences are a fundamental part of our landscapes. They delineate, protect, distinguish and give order. However, GIS data on fences and hedges is sparse. This becomes especially apparent in landscape visualizations. Even with highly detailed building information, land-cover data, and infrastructure information, a rural landscape without fences and hedges looks clearly incomplete. In this article, we describe a method for generating large-scale high-coverage barrier data from the austrian cadastre dataset and other publicly available GIS data. We evaluate this data statistically against three manually mapped regions, as well as visually in our GIS-based landscape visualization. The results show that the approach works well in regions dominated by single-family homes, but that the assumptions generally do not apply in more rural regions with alpine pastures.
Autor / Author: | Bittner, Karl; Baumgartinger, Mathias; Schauppenlehner, Thomas |
Institution / Institution: | BOKU University, Vienna/Austria; BOKU University, Vienna/Austria; BOKU University, Vienna/Austria |
Seitenzahl / Pages: | 10 |
Sprache / Language: | Englisch |
Veröffentlichung / Publication: | JoDLA – Journal of Digital Landscape Architecture, 10-2025 |
Tagung / Conference: | Digital Landscape Architecture 2025 – Collaboration |
Veranstaltungsort, -datum / Venue, Date: | Dessau Campus of Anhalt University, Germany 04-06-25 - 07-06-25 |
Schlüsselwörter (de): | |
Keywords (en): | Open data, feature extraction, mapping, GIS, VR, 3D visualization |
Paper review type: | Full Paper Review |
DOI: | doi:10.14627/537754054 |
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