Robust Segmentation of Aerial Image Data Recorded for Landscape Ecology Studies

  • Rafael Guillermo Gonzalez Acuña
  • Junli Tao
  • Daniel Breen
  • Barbara Breen
  • Steve Pointing
  • Len Gillman
  • Reinhard Klette
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9555)


Remote sensing from unmanned aerial vehicles provides an opportunity to bridge the gap between fine scale ground-based measurements and broad scale observations from conventional aircraft and satellites. The advantages of this approach include safe access to hazardous or difficult terrain and conditions, the ability to survey at specific times and spatial scales, and the increasingly affordable cost of this technology. These benefits have led to a rapidly expanding range of applications in natural resource management and research including mapping of terrain, vegetation cover and condition, threatened species, habitat and the impacts of agriculture, forestry, urbanisation and climate change. The analysis of these often large datasets requires reliable segmentation and classification algorithms to efficiently process information for use in landscape ecology and adaptive management. In this paper, four segmentation methods are compared using images of native vegetation, introduced weeds and agriculture recorded from a quadcopter flown over a warm temperate island (Waiheke Island, New Zealand), and also images recorded from a fixed wing UAV in a polar desert (McMudro Dry Valleys, Antarctica). We propose a post-processing method to improve the segmentation performance of the algorithms and demonstrate how this can contribute to improving research outcomes in natural resource management, conservation and agriculture.


Image segmentation Aerial video data UAV Waiheke Island Antarctica Performance evaluation Segmentation measure 



Authors thank Dongwei Liu for experimental support.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rafael Guillermo Gonzalez Acuña
    • 1
  • Junli Tao
    • 2
  • Daniel Breen
    • 2
  • Barbara Breen
    • 2
  • Steve Pointing
    • 2
  • Len Gillman
    • 2
  • Reinhard Klette
    • 2
  1. 1.Centro de Investigaciones en ÓpticaLeónMexico
  2. 2.Auckland University of TechnologyAucklandNew Zealand

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