Mapping shoreline indicators on a sandy beach with supervised edge detection of soil moisture differences

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This study describes a method to map shoreline indicators on a sandy beach. The hypothesis is that, on this beach, spectral albedo is predominantly determined by moisture content and water lines can, therefore, be detected as albedo contrasts. A laboratory experiment is performed to relate moisture content to image albedo, and supervised edge detection is subsequently used to map the shoreline indicators with remote sensing imagery. The algorithm is tested with data from visible, near-infrared and shortwave-infrared wavelength regions. These results are compared to shoreline indicators obtained by a field survey and a shoreline indicator derived from a digital elevation model. Both the water line present when the imagery was acquired, as well as the maximum extent of the last flood, can be detected as a single edge. Older high water lines are confused with the last high water line and appear dispersed, as there are multiple debris lines present on the beach. The low water line, usually in saturated sand, also appears dispersed due to the presence of channels and troughs. Shorelines are constant moving boundaries, which is why shoreline indicators are used as a proxy. Unlike a mathematical indicator that is based on an elevation model, our method is more sensitive to the dynamic nature of shorelines. Supervised edge-detection is a technique for generating reproducible measurements of shoreline indicator positions over time, and aids in the monitoring of coastline migration.
LanguageEnglish
Pages231-238
JournalInternational Journal of Applied Earth Observation and Geoinformation (JAG)
Volume74
DOIs
Publication statusPublished - 2019

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Water piping systems
Soil moisture
Edge detection
Beaches
shoreline
beach
soil moisture
Moisture
Infrared radiation
albedo
Debris
Remote sensing
Sand
detection
indicator
moisture content
Wavelength
imagery
Monitoring
Experiments

Keywords

  • Edge detection
  • template matching
  • Shoreline
  • Indicator
  • Sandy beach
  • Schiermonnikoog
  • ITC-ISI-JOURNAL-ARTICLE

Cite this

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abstract = "This study describes a method to map shoreline indicators on a sandy beach. The hypothesis is that, on this beach, spectral albedo is predominantly determined by moisture content and water lines can, therefore, be detected as albedo contrasts. A laboratory experiment is performed to relate moisture content to image albedo, and supervised edge detection is subsequently used to map the shoreline indicators with remote sensing imagery. The algorithm is tested with data from visible, near-infrared and shortwave-infrared wavelength regions. These results are compared to shoreline indicators obtained by a field survey and a shoreline indicator derived from a digital elevation model. Both the water line present when the imagery was acquired, as well as the maximum extent of the last flood, can be detected as a single edge. Older high water lines are confused with the last high water line and appear dispersed, as there are multiple debris lines present on the beach. The low water line, usually in saturated sand, also appears dispersed due to the presence of channels and troughs. Shorelines are constant moving boundaries, which is why shoreline indicators are used as a proxy. Unlike a mathematical indicator that is based on an elevation model, our method is more sensitive to the dynamic nature of shorelines. Supervised edge-detection is a technique for generating reproducible measurements of shoreline indicator positions over time, and aids in the monitoring of coastline migration.",
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AB - This study describes a method to map shoreline indicators on a sandy beach. The hypothesis is that, on this beach, spectral albedo is predominantly determined by moisture content and water lines can, therefore, be detected as albedo contrasts. A laboratory experiment is performed to relate moisture content to image albedo, and supervised edge detection is subsequently used to map the shoreline indicators with remote sensing imagery. The algorithm is tested with data from visible, near-infrared and shortwave-infrared wavelength regions. These results are compared to shoreline indicators obtained by a field survey and a shoreline indicator derived from a digital elevation model. Both the water line present when the imagery was acquired, as well as the maximum extent of the last flood, can be detected as a single edge. Older high water lines are confused with the last high water line and appear dispersed, as there are multiple debris lines present on the beach. The low water line, usually in saturated sand, also appears dispersed due to the presence of channels and troughs. Shorelines are constant moving boundaries, which is why shoreline indicators are used as a proxy. Unlike a mathematical indicator that is based on an elevation model, our method is more sensitive to the dynamic nature of shorelines. Supervised edge-detection is a technique for generating reproducible measurements of shoreline indicator positions over time, and aids in the monitoring of coastline migration.

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