Semester Award Granted

Summer 2025

Submission Date

August 2025

Document Type

Thesis

Degree Name

Master of Science (MS)

Thesis/Dissertation Advisor [Chair]

Sudhagar Nagarajan

Abstract

Coastal landscapes are dynamic interfaces shaped by natural forces and human activity, requiring precise, multiscale monitoring for effective conservation. This research investigates some of the coastal monitoring challenges related to shoreline erosion, terrain modeling, and mangrove species classification at the Jupiter Inlet Lighthouse Outstanding Natural Area (ONA), a 120-acre coastal preserve in southeast Florida. The first study applies conditional entropy and partial correlation to assess the relationship between shoreline retreat and environmental variables using UAS-derived shoreline data collected from 2017 to 2023. The second study enhances Digital Terrain Model (DTM) accuracy, a critical factor in erosion assessments, by applying RandLA-Net, a deep learning model, to classify points derived from UAS-SfM point clouds. The third study uses UAV-based hyperspectral imagery and classification techniques to map mangrove species, producing a distribution map that supports future spatiotemporal monitoring and guides replanting strategies in erosion-prone areas. Collectively, these studies integrate geospatial technologies and statistical modeling to advance data-driven coastal monitoring strategies, informing shoreline stabilization and vegetation management under evolving climatic and anthropogenic pressures.

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