Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK)
AbstractJapanese Knotweed s.l. taxa are amongst the most aggressive vascular plant Invasive Alien Species (IAS) in the world. These taxa form dense, suppressive monocultures and are persistent, pervasive invaders throughout the more economically developed countries (MEDCs) of the world. The current paper utilises the Object-Based Image Analysis (OBIA) approach of Definiens Imaging Developer software, in combination with very high spatial resolution (VHSR) colour infra-red (CIR) and visible‑band (RGB) aerial photography in order to detect Japanese Knotweed s.l. taxa in Wales (UK). An algorithm was created using Definiens in order to detect these taxa, using variables found to effectively distinguish them from landscape and vegetation features. The results of the detection algorithm were accurate, as confirmed by field validation and desk‑based studies. Further, these results may be incorporated into Geographical Information Systems (GIS) research as they are readily transferable as vector polygons (shapefiles). The successful detection results developed within the Definiens software should enable greater management and control efficacy. Further to this, the basic principles of the detection process could enable detection of these taxa worldwide, given the (relatively) limited technical requirements necessary to conduct further analyses. View Full-Text
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Jones, D.; Pike, S.; Thomas, M.; Murphy, D. Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK). Remote Sens. 2011, 3, 319-342.
Jones D, Pike S, Thomas M, Murphy D. Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK). Remote Sensing. 2011; 3(2):319-342.Chicago/Turabian Style
Jones, Daniel; Pike, Stephen; Thomas, Malcolm; Murphy, Denis. 2011. "Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK)." Remote Sens. 3, no. 2: 319-342.