Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery

Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high...

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Main Authors: Amy S. Farris, Zafer Defne, Neil K. Ganju
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Remote Sensing
Subjects:
UAS
UAV
Online Access:https://www.mdpi.com/2072-4292/11/15/1795
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spelling doaj-582f0d110bc04b779ad13eecc3d381b72020-11-25T02:20:27ZengMDPI AGRemote Sensing2072-42922019-07-011115179510.3390/rs11151795rs11151795Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and ImageryAmy S. Farris0Zafer Defne1Neil K. Ganju2Woods Hole Coastal and Marine Science Center, U.S. Geological Survey, Woods Hole, MA 02543, USAWoods Hole Coastal and Marine Science Center, U.S. Geological Survey, Woods Hole, MA 02543, USAWoods Hole Coastal and Marine Science Center, U.S. Geological Survey, Woods Hole, MA 02543, USASalt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The marsh edge from elevation data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between mean high water and mean tide level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA. The other method to calculate the salt marsh shoreline is the marsh edge by image processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The two methods were compared to each other using high resolution unmanned aircraft systems (UAS) data, and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods, and less than 0.43 meters from the digitized shoreline. The MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability.https://www.mdpi.com/2072-4292/11/15/1795marsh edgemarsh shorelineunmanned aircraft systemUASUAVdronelidarsalt marshcoastal wetlandsPlum Island
collection DOAJ
language English
format Article
sources DOAJ
author Amy S. Farris
Zafer Defne
Neil K. Ganju
spellingShingle Amy S. Farris
Zafer Defne
Neil K. Ganju
Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery
Remote Sensing
marsh edge
marsh shoreline
unmanned aircraft system
UAS
UAV
drone
lidar
salt marsh
coastal wetlands
Plum Island
author_facet Amy S. Farris
Zafer Defne
Neil K. Ganju
author_sort Amy S. Farris
title Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery
title_short Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery
title_full Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery
title_fullStr Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery
title_full_unstemmed Identifying Salt Marsh Shorelines from Remotely Sensed Elevation Data and Imagery
title_sort identifying salt marsh shorelines from remotely sensed elevation data and imagery
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2019-07-01
description Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The marsh edge from elevation data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between mean high water and mean tide level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA. The other method to calculate the salt marsh shoreline is the marsh edge by image processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The two methods were compared to each other using high resolution unmanned aircraft systems (UAS) data, and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods, and less than 0.43 meters from the digitized shoreline. The MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability.
topic marsh edge
marsh shoreline
unmanned aircraft system
UAS
UAV
drone
lidar
salt marsh
coastal wetlands
Plum Island
url https://www.mdpi.com/2072-4292/11/15/1795
work_keys_str_mv AT amysfarris identifyingsaltmarshshorelinesfromremotelysensedelevationdataandimagery
AT zaferdefne identifyingsaltmarshshorelinesfromremotelysensedelevationdataandimagery
AT neilkganju identifyingsaltmarshshorelinesfromremotelysensedelevationdataandimagery
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