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Classification of Lowland Native Grassland Communities Using Hyperspectral Unmanned Aircraft System (UAS) Imagery in the Tasmanian Midlands

Faculty of Communication and Environment, Rhein-Waal University of Applied Sciences, 47475 Kamp-Lintfort, Germany
School of Technology, Environment and Design, College of Sciences and Engineering, Discipline of Geography and Environmental Sciences, University of Tasmania, Hobart 7001, Australia
Author to whom correspondence should be addressed.
Received: 31 October 2018 / Revised: 21 December 2018 / Accepted: 23 December 2018 / Published: 5 January 2019
(This article belongs to the Special Issue Drones for Biodiversity Conservation and Ecological Monitoring)
PDF [3630 KB, uploaded 5 January 2019]


This paper presents the results of a study undertaken to classify lowland native grassland communities in the Tasmanian Midlands region. Data was collected using the 20 band hyperspectral snapshot PhotonFocus sensor mounted on an unmanned aerial vehicle. The spectral range of the sensor is 600 to 875 nm. Four vegetation classes were identified for analysis including Themeda triandra grassland, Wilsonia rotundifolia, Danthonia/Poa grassland, and Acacia dealbata. In addition to the hyperspectral UAS dataset, a Digital Surface Model (DSM) was derived using a structure-from-motion (SfM). Classification was undertaken using an object-based Random Forest (RF) classification model. Variable importance measures from the training model indicated that the DSM was the most significant variable. Key spectral variables included bands two (620.9 nm), four (651.1 nm), and 11 (763.2 nm) from the hyperspectral UAS imagery. Classification validation was performed using both the reference segments and the two transects. For the reference object validation, mean accuracies were between 70% and 72%. Classification accuracies based on the validation transects achieved a maximum overall classification accuracy of 93. View Full-Text
Keywords: hyperspectral; UAS; native grassland; random forest hyperspectral; UAS; native grassland; random forest

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Melville, B.; Lucieer, A.; Aryal, J. Classification of Lowland Native Grassland Communities Using Hyperspectral Unmanned Aircraft System (UAS) Imagery in the Tasmanian Midlands. Drones 2019, 3, 5.

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