Using Single- and Multi-Date UAV and Satellite Imagery to Accurately Monitor Invasive Knotweed Species

0495294 - BÚ 2019 RIV CH eng J - Journal Article
Martin, F.-M. - Müllerová, Jana - Borgniet, L. - Dommanget, F. - Breton, V. - Evette, A.
Using Single- and Multi-Date UAV and Satellite Imagery to Accurately Monitor Invasive Knotweed Species.
Remote Sensing. Roč. 10, č. 10 (2018), s. 1-15, č. článku 1662. E-ISSN 2072-4292
R&D Projects: GA MŠMT LTC18007; GA MŠMT 8J18FR021
Institutional support: RVO:67985939
Keywords : invasive plant management * spatial dynamics monitoring * Unmanned Aerial Vehicle
OECD category: Biodiversity conservation
Impact factor: 4.118, year: 2018

We assessed the potential of several single- and multi-date indices derived from satellite and UAV imagery for the detection and mapping of the problematic knotweeds (Fallopia japonica, Fallopia x bohemica) in two different landscapes (i.e., open vs. highly heterogeneous areas). The idea was to develop a simple classification procedure, usable in various contexts and requiring little training to be used by non-experts. We also rationalized errors of omission by applying simple buffer boundaries around knotweed predictions to know if heterogeneity across multi-date images could lead to unfairly harsh accuracy assessment and, therefore, ill-advised decisions. Although our crisp satellite results were rather average, our UAV classifications achieved high detection accuracies. Additionally, the buffer boundary results showed detection rates often exceeding 90–95% for both satellite and UAV images, suggesting that classical accuracy assessments were overly conservative.
Permanent Link: http://hdl.handle.net/11104/0290307