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Remote sensing tools for the large-scale monitoring of vegetation dynamics in wetland ecosystems

  • Author(s): Taddeo, Sophie
  • Advisor(s): Dronova, Iryna
  • et al.
Abstract

Continued worldwide urban and agricultural expansion has triggered a loss and degradation of wetland resources. The United States alone seen a 50% decline in its wetland extent, with this percentage reaching a staggering 70% in certain states. With this widespread fragmentation and degradation of habitats, fewer sites are left with the important role of providing ecosystem services critical to the well-being of human populations. A thorough monitoring of wetland resources is necessary for rapidly identifying areas that require adaptive management and for best allocating limited conservation resources. This dissertation explores different methodological approaches for the large-scale monitoring of wetland ecosystems at low cost using open source remote sensing data. The first chapter provides a review of current monitoring practices in restored wetlands of the San Francisco estuary, California, USA. It identifies opportunities to leverage geospatial tools and datasets, including remote sensing products, to measure the contribution of individual restoration efforts towards regional wetland conservation goals. The second chapter examines the response of landscape metrics characterizing the distribution, size, and shape of vegetated patches to vegetation dynamics in a subset of restored wetlands and reference sites in the Sacramento-San Joaquin Delta of California. To portray vegetation response to restoration treatments, this chapter leverages high resolution aerial images from the National Agriculture Inventory Program and a collection of bi-monthly satellite images from the Landsat archives. The third chapter studies changes in the phenology of wetland sites throughout a 17-year period to identify phenological metrics most responsive to restoration interventions. This chapter outlines the impact of site characteristics and vegetation dynamics on landscape phenology. Finally, the fourth chapter uses a broader scale of analysis to examine how vegetation structure, composition, and spatial distribution modulate wetland greenness as measured by spectral vegetation indices derived from satellite data. By examining the relationships between field properties and spectral greenness across 1,138 wetlands of the conterminous United States, this chapter identifies the spectral vegetation indices most suited for wetland monitoring across different wetland types, vegetation densities, and disturbance levels.

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