Article
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SUAS Based Multispectral Imagery for Monitoring Wetland Inundation and Vegetation
Version 1
: Received: 25 November 2019 / Approved: 27 November 2019 / Online: 27 November 2019 (04:02:59 CET)
Version 2 : Received: 28 November 2019 / Approved: 28 November 2019 / Online: 28 November 2019 (07:30:55 CET)
Version 2 : Received: 28 November 2019 / Approved: 28 November 2019 / Online: 28 November 2019 (07:30:55 CET)
How to cite: Dehm, D.; Becker, R.; Godre, A. SUAS Based Multispectral Imagery for Monitoring Wetland Inundation and Vegetation. Preprints 2019, 2019110326 Dehm, D.; Becker, R.; Godre, A. SUAS Based Multispectral Imagery for Monitoring Wetland Inundation and Vegetation. Preprints 2019, 2019110326
Abstract
Mapping short-term wetland vegetation and water storage changes is valuable for monitoring the biogeochemical processes of wetland systems. Old Woman Creek National Estuarine Research Reserve is a dynamic freshwater estuary that experiences intermittent changes in water level over the course of a year. Small unmanned aerial systems (sUAS) are useful tools in monitoring changes as they are rapidly deployed, repeatable, and high-resolution. In this study, commercial quadcopters were paired with a red/green/near-infrared MAPIR Survey 3W camera to produce normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) maps to observe short-term changes at OWC. Orthomosaics were produced for flights on 8 days throughout 2018 and early 2019. The orthomosaics were calibrated to bottom-of-atmosphere reflectance using the Empirical Line Correction method and NDVI and NDWI maps were created. The NDVI pixel values were used to generate maps of vegetation extent showing density changes over time. Identifying dominant vegetation in these maps allowed for the application of the National Estuarine Reserve System (NERRS) Classification Codes to zones of interest. NDWI provided water extent at different water levels and when paired with LiDAR and bathymetric data yielded water volume and residence time estimates. The produced maps contribute to the overall understanding of habitats affected by water inundation variations.
Keywords
sUAS; UAV; drone; multispectral; wetland; NDVI; NDWI; remote sensing
Subject
Environmental and Earth Sciences, Environmental Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Commenter: Richard Becker
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