Mapping Invasive Lupinus polyphyllus Lindl. in Semi-natural Grasslands Using Object-Based Image Analysis of UAV-borne Im
- PDF / 8,854,988 Bytes
- 16 Pages / 595.276 x 790.866 pts Page_size
- 80 Downloads / 139 Views
DGPF
ORIGINAL ARTICLE
Mapping Invasive Lupinus polyphyllus Lindl. in Semi‑natural Grasslands Using Object‑Based Image Analysis of UAV‑borne Images Jayan Wijesingha1 · Thomas Astor1 · Damian Schulze‑Brüninghoff1 · Michael Wachendorf1 Received: 8 January 2020 / Accepted: 17 July 2020 © The Author(s) 2020
Abstract Knowledge on the spatio-temporal distribution of invasive plant species is vital to maintain biodiversity in grasslands which are threatened by the invasion of such plants and to evaluate the effect of control activities conducted. Manual digitising of aerial images with field verification is the standard method to create maps of the invasive Lupinus polyphyllus Lindl. (Lupine) in semi-natural grasslands of the UNESCO biosphere reserve “Rhön”. As the standard method is labour-intensive, a workflow was developed to map lupine coverage using an unmanned aerial vehicle (UAV)-borne remote sensing (RS) along with object-based image analysis (OBIA). UAV-borne red, green, blue and thermal imaging, as well as photogrammetric canopy height modelling (CHM) were applied. Images were segmented by unsupervised parameter optimisation into image objects representing lupine plants and grass vegetation. Image objects obtained were classified using random forest classification modelling based on objects’ attributes. The classification model was employed to create lupine distribution maps of test areas, and predicted data were compared with manually digitised lupine coverage maps. The classification models yielded a mean prediction accuracy of 89%. The maximum difference in lupine area between classified and digitised lupine maps was 5%. Moreover, the pixel-wise map comparison showed that 88% of all pixels matched between classified and digitised maps. Our results indicated that lupine coverage mapping using UAV-borne RS data and OBIA provides similar results as the standard manual digitising method and, thus, offers a valuable tool to map invasive lupine on grasslands. Keywords Invasive plant species · Lupinus polyphyllus lindl. · Unmanned aerial vehicles · Object-based image analysis · Spatial coverage mapping · Grassland Zusammenfassung Kartierung der invasiven Lupinus Polyphyllus Lindl. auf naturnahem Grünland mit UAV-gestützten Bildern und objektba sierter Bildanalyse. Die Kenntnis der raum-zeitlichen Verteilung invasiver Pflanzenarten ist unerlässlich a) für die Erhaltung der Artenvielfalt in Grünland, das durch das Eindringen solcher Pflanzen bedroht ist, und b) für die Kontrolle der Wirksamkeit von Gegenmaßnahmen. Die manuelle Digitalisierung von Luftbildern mit Feldvergleich ist bisher die Standardmethode zur Erstellung von Karten der invasiven Lupinus polyphyllus Lindl. (Lupine) in naturnahen Magerrasen des UNESCO-Biosphärenreservats "Rhön". Da dieses Verfahren arbeitsaufwändig ist, wurde eine neue Methode zur Kartierung der Verbreitung der Lupine auf Basis von UAV-gestützter Fernerkundung (RS) und objektbasierter Bildanalyse (OBIA) entwickelt. Dabei * Jayan Wijesingha jayan.wijesingha@uni‑kassel.de; gnr
Data Loading...
