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I Remote Sensing of Mangrove Composition and Structure in The Remote Sensing of Mangrove Composition and Structure in the Galapagos Islands Benjamin W. Heumann Dissertation A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirement for the degree of Doctor of Philosophy in the Department of Geography Chapel Hill 2011 Approved by Dr. Stephen J. Walsh Dr. Conghe Song Dr. Aaron Moody Dr. George P. Malanson Dr. Dean Urban i © 2011 Benjamin W. Heumann ALL RIGHTS RESERVED ii Abstract Benjamin W. Heumann: Remote sensing of mangrove composition and structure in the Galapagos Islands (Under the direction of Dr. Stephen J. Walsh) Mangroves are unique inter-tidal ecosystems that provide valuable ecosystem goods and services. This dissertation investigates new methods of characterizing mangrove forests using remote sensing with implications for mapping and modeling ecosystem goods and services. Specifically, species composition, leaf area, and canopy height are investigated for mangroves in the Galapagos Islands. The Galapagos Islands serve as an interesting case study where environmental conditions are highly variable over short distances producing a wide range of mangrove composition and structure to examine. This dissertation reviews previous mangrove remote sensing studies and seeks to address missing gaps. Specifically, this research seeks to examine pixel and object-based methods for mapping mangrove species, investigate the usefulness of spectral and spatial metrics to estimate leaf area, and compare existing global digital surface models with a digital surface model extracted from new very high resolution imagery. The major findings of this research include the following: 1) greater spectral separability between true mangrove and mangrove associate species using object-based image analysis compared to pixel-based analysis, but a lack of separability between individual mangrove species, 2) the demonstrated necessity for novel machine-learning classification techniques rather than traditional clustering classification algorithms, 3) significant but weak relationships between spectral vegetation indices and leaf area, 4) moderate to strong relationships between grey-level co-occurrence matrix image texture and leaf area at the individual species level, 5) similar accuracy between a very high resolution stereo optical digital iii surface model a coarse resolution InSAR product to estimate canopy height with improved accuracy using a hybrid model of these two products. The results demonstrate advancements in remote sensing technology and technique, but further challenges remain before these methods can be applied to monitoring and modeling applications. Based on these results, future research should focus on emerging technologies such as hyperspectral, very high resolution InSAR, and LiDAR to characterize mangrove forest composition and structure. iv To my loving wife Carla, v Acknowledgements I would like to acknowledge the following people and organizations for their assistance and support. First, I would like to acknowledge the generous support of the National Science Foundation for a Doctoral Dissertation Research Improvement grant, the American Society of Photogrammetry and Remote Sensing for a Fischer Memorial Scholarship, the UNC Center for Galapagos Studies for acquisition of data and funding to support field work, the UNC Department of Geography for an Eyre Travel Scholarship for exploratory dissertation field work, and the UNC Graduate School for support from the opportunity fund off campus training opportunities. Second, I would like to thank all of those that helped me directly or indirectly in the field - Amy McCleary, Evan Raczkowski, Stacey Frisk, Royce Brown, Javier 1&2, Phil Page, the Galapagos National Park, and the Universidad San Francisco de Quito. I would especially like to thank Drs. Birgit Fessl and Francesca Cunningham at the Charles Darwin Research Station for their support, data, and insight into the mangrove finch's world. I would also like to thank all my fellow graduate students in geography, the Carolina Population Center, and the Center for Galapagos Studies for all the good times that helped sustain me through this difficult process. Third, I would like to thank my supervisor and committee members for their guidance and support. Finally, I would like thank all of those people that supported me up to this point, especially my parents, Hinde, Mary, and Matt and my wife, Carla. vi Preface The proposed title of this dissertation research was "Mapping suitable habitat of the critically endangered mangrove finch using remote sensing". The aim of this research was to generate the spatial data for a habitat model using remote sensing and use the output from the habitat model to help inform the Charles Darwin Research Station on where the best locations to establish new population of the mangrove finch would be. The creation of these spatial data were experimental, new types of imagery, and methods for mangroves were tested since existing methods had largely failed to accurately describe mangroves. The end result is a thorough assessment of the remote sensing of mangrove species composition, leaf area, and canopy. This research has contributed in a significant manner towards furthering remote sensing data and techniques. Unfortunately, the remote sensing data products did not provide sufficient accuracy that I felt them suitable for input into a habitat model that would be used to make conservation management decisions for a critically endangered bird. Thus, I have framed my research around finding a methodology for assessing ecosystem goods and services including, but not specifically, habitat. vii Table of Contents List of Tables .................................................................................................................................... x List of Figures ................................................................................................................................xii List of Abbreviations .................................................................................................................... xiii Chapter 1: Introduction ................................................................................................................... 1 Research Objectives .................................................................................................................... 6 Dissertation Outline .....................................................................................................................7 Contributions .............................................................................................................................. 8 References .................................................................................................................................. 11 Chapter 2 : Satellite remote sensing of mangrove forests: Recent advances and future opportunities ............................................................................................................................. 14 Abstract ...................................................................................................................................... 15 Introduction ............................................................................................................................... 16 Mangrove vegetation and ecosystems ........................................................................................ 17 Traditional approaches to mangrove remote sensing ................................................................ 18 Recent advances ........................................................................................................................ 23 Conclusions and future opportunities ...................................................................................... 36 References ................................................................................................................................. 43 Chapter 3 : An Object-Based Classification of Fringe and Basin Mangroves Using a Hybrid Decision-Tree and Support Vector Machine Approach ............................................................ 53 Abstract ..................................................................................................................................... 54 Introduction .............................................................................................................................. 55 Methods ..................................................................................................................................... 60 Results and Discussion ............................................................................................................. 70 viii Conclusions ................................................................................................................................ 81 References ................................................................................................................................. 83 Chapter 4 : Comparison of Spectral and Spatial Techniques to Map Mangrove Forest Leaf Area .......................................................................................................................................... 86 Abstract ..................................................................................................................................... 87 Introduction .............................................................................................................................
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