A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery
This paper develops and validates a new fully automated procedure for shoreline delineation from high-resolution multispectral satellite images. The model is based on a new water–land index, the Direct Difference Water Index (<i>DDWI</i>). A new technique based on the buffer overlay meth...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/3/557 |
| _version_ | 1797485094998376448 |
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| author | Hazem Usama Abdelhady Cary David Troy Ayman Habib Raja Manish |
| author_facet | Hazem Usama Abdelhady Cary David Troy Ayman Habib Raja Manish |
| author_sort | Hazem Usama Abdelhady |
| collection | DOAJ |
| description | This paper develops and validates a new fully automated procedure for shoreline delineation from high-resolution multispectral satellite images. The model is based on a new water–land index, the Direct Difference Water Index (<i>DDWI</i>). A new technique based on the buffer overlay method is also presented to determine the shoreline changes from different satellite images and obtain a time series for the shoreline changes. The shoreline detection model was applied to imagery from multiple satellites and validated to have sub-pixel accuracy using beach survey data that were collected from the Lake Michigan (USA) shoreline using a novel backpack-based LiDAR system. The model was also applied to 132 satellite images of a Lake Michigan beach over a three-year period and detected the shoreline accurately, with a >99% success rate. The model out-performed other existing shoreline detection algorithms based on different water indices and clustering techniques. The resolution shoreline position timeseries is the first satellite image-extracted dataset of its kind in terms of its high spatial and temporal resolution, and paves the road to obtaining other high-temporal-resolution datasets to refine models of beaches worldwide. |
| first_indexed | 2024-03-09T23:13:52Z |
| format | Article |
| id | doaj.art-9ecc9fdad9e34d93948835870c1896db |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T23:13:52Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-9ecc9fdad9e34d93948835870c1896db2023-11-23T17:39:42ZengMDPI AGRemote Sensing2072-42922022-01-0114355710.3390/rs14030557A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral ImageryHazem Usama Abdelhady0Cary David Troy1Ayman Habib2Raja Manish3Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USALyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USALyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USALyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USAThis paper develops and validates a new fully automated procedure for shoreline delineation from high-resolution multispectral satellite images. The model is based on a new water–land index, the Direct Difference Water Index (<i>DDWI</i>). A new technique based on the buffer overlay method is also presented to determine the shoreline changes from different satellite images and obtain a time series for the shoreline changes. The shoreline detection model was applied to imagery from multiple satellites and validated to have sub-pixel accuracy using beach survey data that were collected from the Lake Michigan (USA) shoreline using a novel backpack-based LiDAR system. The model was also applied to 132 satellite images of a Lake Michigan beach over a three-year period and detected the shoreline accurately, with a >99% success rate. The model out-performed other existing shoreline detection algorithms based on different water indices and clustering techniques. The resolution shoreline position timeseries is the first satellite image-extracted dataset of its kind in terms of its high spatial and temporal resolution, and paves the road to obtaining other high-temporal-resolution datasets to refine models of beaches worldwide.https://www.mdpi.com/2072-4292/14/3/557shoreline detectionshoreline evolutionshoreline timeserieswater indexLiDAR |
| spellingShingle | Hazem Usama Abdelhady Cary David Troy Ayman Habib Raja Manish A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery Remote Sensing shoreline detection shoreline evolution shoreline timeseries water index LiDAR |
| title | A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery |
| title_full | A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery |
| title_fullStr | A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery |
| title_full_unstemmed | A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery |
| title_short | A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery |
| title_sort | simple fully automated shoreline detection algorithm for high resolution multi spectral imagery |
| topic | shoreline detection shoreline evolution shoreline timeseries water index LiDAR |
| url | https://www.mdpi.com/2072-4292/14/3/557 |
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