New space-based approaches to studying disturbance-recovery trends in wetlandscapes

点击翻译按钮获取中文摘要

Wetland-dominated landscapes - or "wetlandscapes" - are characterized by networks of variably connected, highly dynamic wetlands. They provide vital ecosystem services related to water resources, biodiversity and carbon cycling. Many of these landscapes are facing serious threats due to climate-mediated and anthropogenic (land use) changes. Wetlandscape resilience - their ability to continue providing ecosystem services in the presence of shifting change regimes - is a critical question requiring an understanding of ecological and hydrological dynamics. However, these dynamics are often difficult to quantify in wetlandscapes because of their high temporal variability and spatial heterogeneity. While satellite Earth observation data have been playing an increasingly important role in the study of wetlandscapes, most satellite sensors lack either the spatial resolution or temporal observation frequency to adequately capture their spatio-temporal dynamics. However, trends in open satellite data and high-performance computing capabilities are transforming the way in which landscape dynamics are studied. In particular, the concept of "Virtual Constellations" (VCs) has emerged in the field of land cover monitoring as a potential solution to the problem of spatial and temporal resolution. VCs involve the integration of data from multiple satellite sensors to address a single monitoring objective. A particular challenge in the development this concept is the fusion of data from disparate sensors. Moderate resolution optical and Synthetic Aperture Radar (SAR) sensors are commonly used to monitor wetland hydrology and vegetation, but how to integrate information from both types of sensors to generate spatially and temporally consistent estimates of dynamic land surface parameters like inundation, connectivity or vegetation trends represents a key research gap. My research program develops upon the concept of VCs and optical-SAR fusion to address the problem of resilience of wetlandscapes to climate and land use changes. Accordingly, this program seeks to address three research objectives: (1) Quantify basin-scale inundation dynamics in wetlandscapes through the development of novel optical-SAR compositing approaches; (2) Study spatio-temporal trends of wetland connectivity with fine resolution image time series and graph theory metrics; and (3) Develop an understanding of the hydrological and ecological responses to fire disturbances in peat-dominated wetlandscapes. Study sites will be selected from Arctic, boreal, temperate and sub-tropical wetlandscapes, representing a climate and ecosystem gradient. New methods that integrate data from historical and contemporary optical sensors like Landsat and Sentinel-1 with SAR data from the Sentinel-1 mission and the RADARSAT Constellation Mission (RCM) will be foundational to all three objectives. Data from the anticipated long-wavelength NASA-ISRO SAR mission will also be incorporated as they become available.