Retrieving surface peat moisture in an Albertan bog with Radarsat-2

Boreal peatlands are widely considered as an important carbon sink. Carbon stored in peats is driven by the movement of water. Also, the rate of sequestration and release of greenhouse gases is controlled by peat moisture. Peatlands fires usually take the form of smouldering. Once ignited, peats can smoulder for months or even years, spreading deep underground. This is the reason why peatland fires are so difficult to extinguish. A critical factor that determines whether smouldering can or cannot propagate is peat moisture content. Consequently, retrieving surface moisture is of great interest for fire management in peatlands. The objective of this thesis is to use Radarsat-2 to retrieve surface (0-5 cm) peat moisture content in an Albertan ombrotrophic bog. This approach shows promise for the burned plots (concordance correlation coefficient ρ: 0.435; accuracy: 0.997), followed by all sampled plots (ρ: -0.254; accuracy: 0.962) and unburned plots (ρ: 0.153; accuracy: 0.821). ACKNOWLEDGEMENTS I would like to thank Alberta Sustainable Resource Development for funding and Canadian Space Agency (CSA), MacDonald Dettwiler and Associates (MDA) and Natural Resources Canada (NRCan) for providing Radarsat-2 images. Dr. Mike Flannigan, as my supervisor, is providing supportive feedback all through my Master project. He helped me rebuild my confidence and interests in scientific research. His timely feedbacks and guidance clarify my academic and life perplexities. His patience, kindness, openness and toleration greatly influence my way of thinking and behavior. Without his support and guidance, I couldn’t have the opportunity and the strengths to finish my Master here. I would like to thank Dr. Dan Thompson with help in setting up the weather station, species identification, field sampling and data analysis and other guidance. His timely and helpful feedback is always highly appreciated. I would like to thank Dr. John Gamon for his valuable advice. His careful and thought-provoking questions help me think deeper about my project. I would also like to thank Ms. Chelene Krezek-Hanes for technical support in radar image ordering and processing. I would also like to thank Mr. Alec Casey and Mr. Iman Entezari for technical support in radar image processing. Thanks Stephanie Koroscil, Karen Blouin, Dan Thompson, Oleg Melnik, Jacqueline Dewar and Thomas Fleming for their help with field sampling. Thanks Ginny Marshall for proofreading. I would like to thank Mr. Ian Paine for recovering my thesis. My laptop crashed in January with my thesis inside and I didn’t have a backup copy then. Thanks to Mr. Ian’s efforts, my thesis was back! I can’t describe how grateful I am! I would also thank my parents and my sister, especially my mother. Her perseverance and optimism greatly shape who I am. I would also thank all my friends who care and help me. Without their encouragement and advice, I couldn’t have the courage and strengths to finish writing this thesis. TABLE OF CONTENTS INTRODUCTION . 1 PEATLAND FIRES . 4 SAR BACKGROUND . 5 Wavelength, polarization, and incidence angle . 9 PEATLAND SPATIAL SCALES . 11 Fine scales . 11 Mesoscales. 12 Macroscales . 13 VEGETATION.13 CANADIAN FOREST FIRE DANGER RATING SYSTEM . 15 RES EARCH OBJECTIVES . 16 METHODS . 17 STUDY AREA . 17 WEATHER STATION.19 RADAR IMAGE PROCESSING.22 Preprocessing . 22 Image processing. 23 GROUND SAMPLING SCHEME.27 Peat cores . 27 Theta probe . 28 TDR. 29 VMC RETRIEVAL . 32 Field measured VMC. 32 Developing the model . 33 Validation . 34 RES ULTS . 34 PEAT CORES, THETA PROBES AND TDR . 34 EMPIRICAL FUNCTION . 37 WEIGHTED AVERAGE FOR THE BURNED PLOTS.40 WEIGHTED AVERAGE FOR THE UNBURNED PLOTS . 42 WEIGHTED AVERAGE FOR ALL PLOTS . 44 DISCUSS ION . 47 VMCS MEASUREMENTS . 47 Spatial variation . 48 Temperature . 48 CORRELATION AND SCALES.50 EMPIRICAL MODEL.52 METHODS OF IMPROVEMENT.54 Field sampling . 54 Image fusion . 55 IMPLICATIONS FOR FUTURE FIRE MANAGEMENT . 57 CONCLUS IONS . 58 BIBLIOGRAPHY. 59 APPENDIX. 75 LIST OF TABLES Table 1. Correlation matrix for 4 dates combined for burned plots. An asterisk (*) indicates significance at 0.05 level. Same in the following tables. 38 Table 2. Correlation matrix for 4 dates combined for unburned plots. 39 Table 3. Correlation matrix for 4 dates combined for all plots combined. 40 Table 4. Weighted average for the burned plots for 0827. 41 Table 5. Weighted average for the burned plots for 4 dates combined. 41 Table 6. Weighted average for the unburned plots for 0803. 42 Table 7. Weighted average for the unburned plots for 0827. 43 Table 8. Weighted average for the unburned plots for 0920. 43 Table 9. Weighted average for the unburned plots for