Volume XLII-2/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W6, 55-62, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W6-55-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W6, 55-62, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W6-55-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Aug 2017

23 Aug 2017

WETLAND VEGETATION INTEGRITY ASSESSMENT WITH LOW ALTITUDE MULTISPECTRAL UAV IMAGERY

M. A. Boon1,2 and S. Tesfamichael3 M. A. Boon and S. Tesfamichael
  • 1Department of Zoology, University of Johannesburg, P.O. Box 524, Auckland Park, 2006, South Africa
  • 2Kite Aerial Imagery (Pty) Ltd, 1422 Topaas Street, Waverley, 0186, South Africa
  • 3Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, P.O. Box 524, Auckland Park, 2006, South Africa

Keywords: Multispectral imagery, wetlands, vegetation, UAV, Structure-from-motion, NDVI

Abstract. The use of multispectral sensors on Unmanned Aerial Vehicles (UAVs) was until recently too heavy and bulky although this changed in recent times and they are now commercially available. The focus on the usage of these sensors is mostly directed towards the agricultural sector where the focus is on precision farming. Applications of these sensors for mapping of wetland ecosystems are rare. Here, we evaluate the performance of low altitude multispectral UAV imagery to determine the state of wetland vegetation in a localised spatial area. Specifically, NDVI derived from multispectral UAV imagery was used to inform the determination of the integrity of the wetland vegetation. Furthermore, we tested different software applications for the processing of the imagery. The advantages and disadvantages we experienced of these applications are also shortly presented in this paper.

A JAG-M fixed-wing imaging system equipped with a MicaScene RedEdge multispectral camera were utilised for the survey. A single surveying campaign was undertaken in early autumn of a 17 ha study area at the Kameelzynkraal farm, Gauteng Province, South Africa. Structure-from-motion photogrammetry software was used to reconstruct the camera position’s and terrain features to derive a high resolution orthoretified mosaic. MicaSense Atlas cloud-based data platform, Pix4D and PhotoScan were utilised for the processing. The WET-Health level one methodology was followed for the vegetation assessment, where wetland health is a measure of the deviation of a wetland’s structure and function from its natural reference condition. An on-site evaluation of the vegetation integrity was first completed. Disturbance classes were then mapped using the high resolution multispectral orthoimages and NDVI. The WET-Health vegetation module completed with the aid of the multispectral UAV products indicated that the vegetation of the wetland is largely modified (“D” PES Category) and that the condition is expected to deteriorate (change score) in the future. However a lower impact score were determined utilising the multispectral UAV imagery and NDVI. The result is a more accurate estimation of the impacts in the wetland.