During Nearshore Event Vegetation Gradation (DUNEVEG): Geospatial Tools for Automating Remote Vegetation Extraction
Abstract
Monitoring and modeling of coastal vegetation and ecosystems are major challenges, especially when considering environmental response to hazards, disturbances, and management activities. Remote sensing applications can provide alternatives and complementary approaches to the often costly and laborious field-based collection methods traditionally used for coastal ecosystem monitoring. New and improved sensors and data analysis techniques have become available, making remote sensing applications attractive for evaluation and potential use in monitoring coastal vegetation properties and ecosystem conditions and changes. This study involves the extraction of vegetation metrics from airborne lidar and hyperspectral imagery (HSI) collected by the US Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP) to quantify coastal dune vegetation characteristics. A custom geoprocessing toolbox and associated suite of tools were developed to allow inputs of common NCMP lidar and imagery products to help automate the workflow for extracting prioritized dune vegetation metrics in an efficient and repeatable way. This study advances existing coastal ecosystem knowledge and remote sensing techniques by developing new methodologies to classify, quantify, and estimate critical coastal vegetation metrics which will ultimately improve future estimates and predictions of nearshore dynamics and impacts from disturbance events.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2023
- Accession Number
- AD1213539
Entities
People
- Christina L. Saltus
- Glenn M. Suir
- Molly Reif
- Samuel S. Jackson
Organizations
- Engineer Research and Development Center