Invasive species detection from high resolution aerial photographs
This project focuses on the automatic detection of invasive plant species along railway tracks. Initially, the project targets two highly invasive species: Asian Knotweed (Fallopia japonica) and Giant Hogweed (Heracleum mantegazzianum). ProRail, the Dutch railway infrastructure manager, collects yearly high-resolution helicopter imagery covering all railway tracks in the Netherlands. A deep learning-based classifier is applied to this imagery to detect the aforementioned invasive species. This work was presented as a poster at the 25th anniversary event of the Ambient Intelligence research group.
Authors
- Bram Ton (ORCID: https://orcid.org/0000-0002-9525-5633)
- Ronald Visser (ORCID: https://orcid.org/0000-0001-6966-1729)
- Etto L. Salomons (ORCID: https://orcid.org/0000-0003-2368-4970)
Institutions
- Saxion (NL)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-08
- DOI
- https://doi.org/10.5281/zenodo.23190637
- Primary Topic
- Remote-Sensing Image Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00