Unmanned aerial system derived multi-spectral imagery for the monitoring of coastal dune plant communities

Abstract

Plant community monitoring was conducted at Kaitorete Spit Scientific Reserve using UAS based remote sensing and traditional field-basedtechniques. Multispectral, high resolution UAS imagery was used as the basis for image classification. Different classification methods and data manipulation techniques were evaluated in order to present the most accurate representation of plant communities for comparison against those derived from the field data. Overall image classifcation results were on par with those from similar studies, however their suitability for application to the monitoring of the specific environmental and ecological conditions at Kaitorete Spit remains of low confidence. UAS imagery was able to be used to identify coarse scale ecological features which could then be used to define distinct ecological communities in a simlar but not identical manner to that of the field data. At a finer-scale, UAS imagery could detect some, but not all, key ecological features such as individual species or fine-scale indicators of diverse habitat types.