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Unmanned Aerial System Derived Multi-Spectral Imagery for the Monitoring of Coastal Dune Plant Communities

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Unmanned Aerial System Derived Multi-Spectral Imagery for the Monitoring of Coastal Dune Plant Communities Unmanned Aerial System derived Multi-Spectral Imagery for the Monitoring of Coastal Dune Plant Communities A thesis submitted in partial fulfilment of the requirements for the Degree of Master of Science at Lincoln University by Michael Fake Lincoln University 2019 Abstract of a thesis submitted in partial fulfilment of the requirements for the Degree of Master of Science. Abstract Unmanned Arial System derived Multi-Spectral Imagery for the Monitoring of Coastal Dune Plant Communities by Michael Fake Plant community monitoring was conducted at Kaitorete Spit Scientific Reserve using UAS based remote sensing and traditional field-based techniques. 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. Keywords: Remote Sensing, UAS, UAV, Drone, Image Classification, Plant Community, Vegetation, Coastal, Sand Dunes, Ordination, TWINSPAN, Clustering. ii Acknowledgements This thesis was handed in on the very last day of a long and arduous journey. This thesis and the work that it entails are the result of the hard work and dedication of many different people. Without the support of my current supervisors, Dr. Adrian Patterson and Dr. Crile Doscher, this project would likely never have been completed. Without the support of my initial supervisors, Dr. Brad Martin and in particular Dr. Hannah Buckley, I may have not been around to finish it at all. I also thank my friends and family, who supported my through everything all the same. A special thanks to my office-mate, pooh-sticks world champ and best friend, Dr. Jennifer Dent. Without you, we both would have finished long ago but I’d do it all again in a heart beat. I wish to thank the Department of Conservation, who supplied the imagery for this project as part of a wider investigation into the application of UAS imagery. Thankyou also to the Coastal Restoration Trust of New Zealand, who generously awarded a young and naive student the 2014 Postgraduate Study Award. I wish to express my sincere appreciation to all those who bravley joined me out in the field. These kind people (mostly) non-begrudgingly were dragged out to a cold and windswept beach to hunt for venomous spiders and to follow me around as I pretended to know what I was doing. iii Table of Contents Abstract ....................................................................................................................................... ii Acknowledgements ..................................................................................................................... iii Table of Contents ........................................................................................................................ iv List of Tables ............................................................................................................................... vi List of Figures .............................................................................................................................. ix Chapter 1 Introduction ............................................................................................................ 1 1.1 Remote Sensing in Ecology .......................................................................................................1 1.1.1 Unmanned Aerial Systems ........................................................................................... 3 1.2 Vegetation Classification ...........................................................................................................5 1.2.1 Methods of Image Classification .................................................................................. 5 1.2.2 Spectral and Spatial Resolution in Image Classification ............................................... 7 1.3 Community Analyses with Remote Sensing ..............................................................................8 1.4 Remote Sensing of Sand Dune Environments ..........................................................................9 1.5 The rationale for the study .................................................................................................... 11 1.5.1 Aims and objectives ...................................................................................................12 1.5.2 Thesis structure ..........................................................................................................12 Chapter 2 Methodology .......................................................................................................... 14 2.1 Site Description ...................................................................................................................... 14 2.2 Data collection ....................................................................................................................... 17 2.2.1 Vegetation Surveys ....................................................................................................17 2.2.2 Image Acquisition .......................................................................................................17 2.3 GIS Analysis ............................................................................................................................ 17 2.3.1 Image Preparation......................................................................................................18 2.3.2 Preliminary Image Analysis ........................................................................................23 2.3.3 Final classification and feature extraction .................................................................28 2.4 Statistical analysis .................................................................................................................. 29 2.4.1 Clustering and Ordinations ........................................................................................30 Chapter 3 Results .................................................................................................................... 33 3.1 Image Analysis and Preparation ............................................................................................ 33 3.1.1 Georeferencing ..........................................................................................................33 3.1.2 Vegetation indices ......................................................................................................33 3.1.3 Composite Band Creation ..........................................................................................34 3.1.4 Image Classification Testing .......................................................................................34 3.2 Final Classification .................................................................................................................. 36 3.2.1 Classification Inputs ...................................................................................................36 3.2.2 Final Classification Accuracy Results ..........................................................................36 3.3 Community Analyses .............................................................................................................. 39 3.3.1 Species presence ........................................................................................................39 3.3.2 Field Based Plant Community Analysis ......................................................................40 3.3.3 GIS 0.1 m Resolution Based Plant Community Analysis ............................................43 3.3.4 GIS 0.3 m Resolution Based Plant Community Analysis ............................................47 3.3.5 GIS 0.5 m Resolution Based Plant Community Analysis ............................................50 iv 3.3.6 GIS 1 m Resolution Based Plant Community Analysis................................................54 3.4 Comparison of field and GIS data community analysis ......................................................... 57 3.4.1 Ecological meaning of the cluster divisions ...............................................................57 Chapter 4 Discussion ............................................................................................................... 61 4.1 The suitability for UAS Remote Sensing for monitoring Kaitorete Spit ................................. 61 4.1.1 The scale of ecological phenomena at Kaitorete Spit ................................................61 4.1.2 Detectable indicators of community division and health ..........................................62 4.1.3 Non-detectable indicators of community division and health ..................................69 4.2 Factors in the final results .....................................................................................................
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