Preprint Article Version 1 This version is not peer-reviewed

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)

How to cite: Dehm, D.; Becker, R.; Godre, A. SUAS Based Multispectral Imagery for Monitoring Wetland Inundation and Vegetation. Preprints 2019, 2019110326 (doi: 10.20944/preprints201911.0326.v1). Dehm, D.; Becker, R.; Godre, A. SUAS Based Multispectral Imagery for Monitoring Wetland Inundation and Vegetation. Preprints 2019, 2019110326 (doi: 10.20944/preprints201911.0326.v1).

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 which 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, after which NDVI and NDWI maps were created. The NDVI maps allowed vegetation extent and density changes over time and for National Estuarine Reserve System (NERRS) Classification Codes to be applied 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.

Subject Areas

sUAS; UAV; drone; multispectral; wetland; NDVI; NDWI; remote sensing

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