Link to Session Platform

Chairs(s):

NARCISA PRICOPE, University of North Carolina Wilmington

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Description:

Wetlands provide critical ecosystem services across a range of environmental gradients and are at heightened risk of degradation from anthropogenic pressures, continued development and global environmental changes. There is a growing need for high-resolution (spatially and temporally) habitat identification and precise delineation of wetlands across a variety of stakeholder groups and programs, at multiple spatial scales. Especially along the United States Atlantic Coastal Plains and beyond, the rates of wetland loss and conversion are increasing exponentially, despite wetland mitigation and restoration programs. Traditional wetland surveying and sampling approaches are costly, time-intensive and can physically degrade the systems that are being surveyed, while aerial surveys are relatively fast and unobtrusive. We propose a session that shows practical examples of integration of active (focusing on LiDAR) and passive remote sensing data collected from UASs and miniature remote sensing platforms to assess the efficacy and feasibility of using such collection methods for mapping and modeling change in wetland systems worldwide. We welcome applications that discuss a variety of systems used for deriving high resolution topography in complex forested wetlands, vegetation structure based on fused spectral (multispectral and/or hyperspectral) and LiDAR and three-dimensional data with relevance for mapping subtle changes and conversions in these previously difficult to measure ecosystems. Especially for wetland conversions from less to more salt-dominated habitat types, the ability to fuse active and passive remote sensing data derived from UAS platforms that can carry multiple sensors simultaneously can provide opportunities to move the science forward in ways previously impossible. Papers that focus on the fusion of UAS-collected LiDAR and spectral datasets with satellite imagery are also encouraged as a method of extending these datasets both spatially and temporally.

Non-Presenting Participants Agenda