Unsupervised detection of salt marsh platforms: a topographic method
Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh pl...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-03-01
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| Series: | Earth Surface Dynamics |
| Online Access: | https://www.earth-surf-dynam.net/6/239/2018/esurf-6-239-2018.pdf |
| _version_ | 1819212769240547328 |
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| author | G. C. H. Goodwin S. M. Mudd F. J. Clubb F. J. Clubb |
| author_facet | G. C. H. Goodwin S. M. Mudd F. J. Clubb F. J. Clubb |
| author_sort | G. C. H. Goodwin |
| collection | DOAJ |
| description | Salt marshes filter pollutants, protect coastlines against storm surges, and
sequester carbon, yet are under threat from sea level rise and anthropogenic
modification. The sustained existence of the salt marsh ecosystem depends on
the topographic evolution of marsh platforms. Quantifying marsh platform
topography is vital for improving the management of these valuable
landscapes. The determination of platform boundaries currently relies on
supervised classification methods requiring near-infrared data to detect
vegetation, or demands labour-intensive field surveys and digitisation. We
propose a novel, unsupervised method to reproducibly isolate salt marsh
scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of
Platforms (TIP). Field observations and numerical models show that salt
marshes mature into subhorizontal platforms delineated by subvertical
scarps. Based on this premise, we identify scarps as lines of local maxima on
a slope raster, then fill landmasses from the scarps upward, thus isolating
mature marsh platforms. We test the TIP method using lidar-derived DEMs from
six salt marshes in England with varying tidal ranges and geometries, for
which topographic platforms were manually isolated from tidal flats.
Agreement between manual and unsupervised classification exceeds 94 % for DEM
resolutions of 1 m, with all but one site maintaining an accuracy superior to
90 % for resolutions up to 3 m. For resolutions of 1 m, platforms detected
with the TIP method are comparable in surface area to digitised platforms
and have similar elevation distributions. We also find that our method allows
for the accurate detection of local block failures as small as 3 times the
DEM resolution. Detailed inspection reveals that although tidal creeks were
digitised as part of the marsh platform, unsupervised classification
categorises them as part of the tidal flat, causing an increase in false
negatives and overall platform perimeter. This suggests our method may
benefit from combination with existing creek detection algorithms. Fallen
blocks and high tidal flat portions, associated with potential pioneer zones,
can also lead to differences between our method and supervised mapping.
Although pioneer zones prove difficult to classify using a topographic
method, we suggest that these transition areas should be considered when
analysing erosion and accretion processes, particularly in the case of
incipient marsh platforms. Ultimately, we have shown that unsupervised
classification of marsh platforms from high-resolution topography is possible
and sufficient to monitor and analyse topographic evolution. |
| first_indexed | 2024-12-23T06:48:14Z |
| format | Article |
| id | doaj.art-517b1a2c0f8a4da0aa62cefeeceeb357 |
| institution | Directory Open Access Journal |
| issn | 2196-6311 2196-632X |
| language | English |
| last_indexed | 2024-12-23T06:48:14Z |
| publishDate | 2018-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth Surface Dynamics |
| spelling | doaj.art-517b1a2c0f8a4da0aa62cefeeceeb3572022-12-21T17:56:30ZengCopernicus PublicationsEarth Surface Dynamics2196-63112196-632X2018-03-01623925510.5194/esurf-6-239-2018Unsupervised detection of salt marsh platforms: a topographic methodG. C. H. Goodwin0S. M. Mudd1F. J. Clubb2F. J. Clubb3School of GeoSciences, University of Edinburgh, Edinburgh, UKSchool of GeoSciences, University of Edinburgh, Edinburgh, UKSchool of GeoSciences, University of Edinburgh, Edinburgh, UKInstitute of Earth and Environmental Science, University of Potsdam, Potsdam, GermanySalt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labour-intensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94 % for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90 % for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.https://www.earth-surf-dynam.net/6/239/2018/esurf-6-239-2018.pdf |
| spellingShingle | G. C. H. Goodwin S. M. Mudd F. J. Clubb F. J. Clubb Unsupervised detection of salt marsh platforms: a topographic method Earth Surface Dynamics |
| title | Unsupervised detection of salt marsh platforms: a topographic method |
| title_full | Unsupervised detection of salt marsh platforms: a topographic method |
| title_fullStr | Unsupervised detection of salt marsh platforms: a topographic method |
| title_full_unstemmed | Unsupervised detection of salt marsh platforms: a topographic method |
| title_short | Unsupervised detection of salt marsh platforms: a topographic method |
| title_sort | unsupervised detection of salt marsh platforms a topographic method |
| url | https://www.earth-surf-dynam.net/6/239/2018/esurf-6-239-2018.pdf |
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