Development of Methods to Map and Monitor Peatland Ecosystems and Hydrologic Conditions Using Radarsat-2 Synthetic Aperture Radar
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Development of methods to map and monitor peatland ecosystems and hydrologic conditions using Radarsat-2 Synthetic Aperture Radar by Koreen Millard A thesis submitted to the Faculty of Graduate and Postdoctoral Affairs in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Geography of Environmental Change Carleton University Ottawa, Ontario © 2016, Koreen Millard Abstract Peatland ecosystems exhibit a wide range of biophysical conditions and Synthetic Aperture Radar (SAR) remote sensing provides a method to collect information about these conditions over large areas. The ability to extract useful hydrologic and vegetation information across peatlands is currently limited due to complex interactions of spatially and temporally-variable conditions on the SAR response. The overarching purpose of this thesis was to advance our understanding of SAR backscatter response to peatland hydrology and vegetation and to develop new approaches for remote mapping and monitoring of peatland environments with SAR. Specifically, this thesis aimed to 1) improve methods for peatland ecosystem mapping and classification accuracy assessment with a Random Forest classifier; and 2) develop methods for surface soil moisture and water table depth retrieval in peatlands using SAR remote sensing data. At Alfred Bog, a peatland in eastern Ontario, Canada, active remote sensing data (SAR and Light Detection and Ranging) were used for these purposes. A Random Forest classification workflow was developed, resulting in an improved peatland ecosystem mapping technique. Recommendations for appropriate training data sample selection with this classifier were also developed. This workflow enabled the creation of a site- wide peatland ecosystem map, which was used to better understand the SAR response to hydrological and vegetation conditions within the different peatland ecosystem classes. For the retrieval of surface hydrologic information, groups of highly correlated variables were identified from a large number of SAR parameters ii (including SAR intensity, polarimetric decomposition and discriminator variables) and a subset of these were compared with trends in soil moisture, water table and vegetation spatial variability and change over time. The Freeman-Durden Power due to Rough Surface parameter was found to be positively correlated with soil moisture, while the Touzi AlphaS1 parameter was found to be negatively correlated with water table depth from the surface. Various polarimetric parameters were used to build statistical models of soil moisture and, in some cases, CART-models resulted in high explained variance but independent validation indicated that these models were over-fit. These results are important, as many examples were found in the literature where, through statistical models, SAR was reported to be a strong predictor of soil moisture but models were not properly validated. To determine if models could predict soil moisture from SAR at times when no field measured data existed, linear mixed effects models were built that accounted for the temporal autocorrelation due to the repeated measures design of field data. While some models resulted in high explained variance, most of the explained variance was attributed to the variability between peatland classes and/or the specific date that the image was acquired, rather than the SAR data itself. These models also presented challenges in independent validation. Overall, this thesis points to some fundamental limitations on our ability to accurately monitor peatland hydrology with SAR due to the complexity of the scattering response where complex surface conditions exist. It highlights a need for extensive field monitoring campaigns and testing to further refine approaches for remote hydrologic monitoring in natural environments. iii Acknowledgements First, I would like to thank my supervisor, Murray Richardson, for his support and guidance over the past few years. Thank you for taking me on as a student, encouraging me to gain experience a wide variety of environments and technologies, passing on so many important skills and for being available to talk issues and questions through throughout this entire process. I would also like to thank my committee members (Doug King and Scott Mitchell) for providing valuable comments and guidance throughout the various stages of this research. Funding for this research was provided by an NSERC Discovery Grant to Murray Richardson, the Northern Scientific Training Program and South Nation Conservation Authority. Scholarships from NSERC, OGS and Carleton University were invaluable. This thesis would not have been possible without the immense assistance I was given in field data collection from: Cassandra Michel, Marisa Ramey, Cameron Samson, Melissa Dick, Lindsay Armstrong, Alex Foster, Keegan Smith, Fernanda Moreira-Amaral. Those long, hard, sloggy days in the bog were the best part! Dan Thompson and Marc Parisien (NRCan) deserve a huge acknowledgement for enabling me to experience peatlands in the western sub-arctic and for answering my seemingly endless questions about stats over breakfast. Jean Morin (Parks Canada) is gratefully acknowledged for his enthusiasm and in-kind support throughout the three field seasons I was able to explore Wood Buffalo National Park. iv The employees of the Environment Department at the Debeers Victor Mine and the Muskeg Crew are gratefully acknowledged for dealing with my requests for field and helicopter access so I could learn about peatlands in the eastern sub-arctic. Ridha Touzi and Gabriel Gosselin deserve acknowledgement for bringing me into the SAR world and teaching me so much about polarimetry. Elyn Humphreys provided a wealth of knowledge about peatlands and field sampling and is thanked for setting up and maintaining the met-station at Alfred. Sarah Banks, Lori White and Jon Pasher (ECCC) were instrumental in getting me much of the data I needed and encouraging our collaboration in various related projects. South Nation Conservation Authority deserves special thanks for introducing me to Alfred Bog and encouraging my research there. Dave Rowlands (DND) is thanked for his support over the years and for setting the LiDAR data acquisitions in motion. Karim Mattar (DRDC), Jeff Secker (DRDC) and Luke Copeland (U. Ottawa) are thanked for the guidance they provided while I investigated interferometry and the use of Gamma software. I cannot begin to calculate how many thanks Doug Stiff deserves. For strapping UAVs on your back and carrying them into the bog on snow shoes, to constantly re- enforcing my confidence in my ability to complete this, and to picking up the slack in life while I type away- thank you. Finally, I cannot forget to thank my parents for fostering my curiosity and love for all things outdoors. Who knew all that playing in the mud was just training for my PhD! v Table of Contents Abstract ...................................................................................................................................................... ii Acknowledgements ............................................................................................................................... iv Integrated Manuscripts and Co-Authorship Information ...................................................... xi Chapter 1 Introduction ......................................................................................................................... 1 1.1 Background & Justification ..................................................................................................... 2 1.2 Research Objectives ................................................................................................................... 7 1.3 Thesis Overview .......................................................................................................................... 9 Chapter 2 Literature Review ........................................................................................................... 13 2.1 Peatlands ..................................................................................................................................... 13 2.2 Remote Sensing and Mapping of Peatland Ecosystems ............................................ 17 2.3 Use of SAR for monitoring peatland hydrology ........................................................... 30 2.4 Concluding Remarks ............................................................................................................... 33 Chapter 3 Study Location, Design Rationale and Data Sources and Processing ......... 35 3.1 Rationale for geographic location of study .................................................................... 35 3.2 Data Sources .............................................................................................................................. 39 3.3 Data Reliability and assessment of error ....................................................................... 48 3.3 Analytical Software and techniques ................................................................................. 54 Chapter 4 Wetland mapping with LiDAR derivatives, SAR polarimetric decompositions, and LiDAR–SAR fusion using a random forest classifier ............. 57 4.1 Study area ................................................................................................................................... 60 4.2 Methods ......................................................................................................................................