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Copy file name to clipboardexpand all lines: README.md
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:point_right: Visit the [CoastSat website](http://coastsat.space) to explore and download existing satellite-derived shoreline datasets generated with CoastSat in the Pacific and Atlantic basins.
Satellite remote sensing can provide low-cost long-term shoreline data capable of resolving the temporal scales of interest to coastal scientists and engineers at sites where no in-situ field measurements are available. CoastSat enables the non-expert user to extract shorelines from Landsat 5, Landsat 7, Landsat 8, Landsat 9 and Sentinel-2 images.
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The shoreline detection algorithm implemented in CoastSat is optimised for sandy beach coastlines. It combines a sub-pixel border segmentation and an image classification component, which refines the segmentation into four distinct categories such that the shoreline detection is specific to the sand/water interface.
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The toolbox has the following functionalities:
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1. easy retrieval of satellite imagery spanning the user-defined region of interest and time period from Google Earth Engine, including state-of-the-art pre-processing steps (re-projecting the different bands, pansharpening, advanced cloud masking).
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2. automated extraction of shorelines from all the selected images using a sub-pixel resolution technique and options for quality-control.
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3. intersection of the 2D shorelines with user-defined shore-normal transects to create time-series of shoreline change.
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4. tidal correction of shoreline time-series and extraction of tidal levels at the time of image acquisition from a global tide model (FES2022)
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5. post-processing of the shoreline time-series, despiking and seasonal averaging.
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6. Beach slope estimation using satellite-derived shorelines and predicted tides
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<details>
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<summary><strong>Additional toolkits and documentation</strong></summary>
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:point_right: Other repositories and extensions related to CoastSat:
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:point_right: Other open-source repositories and extensions related to CoastSat:
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-[CoastSeg](https://github.com/dbuscombe-usgs/CoastSeg): an interactive toolbox for downloading satellite imagery, applying image segmentation models, mapping shoreline positions and more.
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-[CoastSat.slope](https://github.com/kvos/CoastSat.slope): estimates the beach-face slope from the satellite-derived shorelines obtained with CoastSat.
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-[CoastSat.PlanetScope](https://github.com/ydoherty/CoastSat.PlanetScope): shoreline extraction for PlanetScope Dove imagery (near-daily since 2017 at 3m resolution).
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-[CoastSeg](https://github.com/dbuscombe-usgs/CoastSeg): an interactive toolbox for downloading satellite imagery, applying image segmentation models, mapping shoreline positions and more.
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-[SDS_Benchmark](https://github.com/SatelliteShorelines/SDS_Benchmark): testbed for satellite-derived shorelines mapping algorithms and validation against benchmark datasets.
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-[CoastSat.islands](https://github.com/mcuttler/CoastSat.islands): 2D planform measurements for small reef islands.
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-[CoastSat.Maxar](https://github.com/kvos/CoastSat.Maxar): shoreline extraction on Maxar World-View images (in progress)
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-[InletTracker](https://github.com/VHeimhuber/InletTracker): monitoring of intermittent open/close estuary entrances.
Satellite remote sensing can provide low-cost long-term shoreline data capable of resolving the temporal scales of interest to coastal scientists and engineers at sites where no in-situ field measurements are available. CoastSat enables the non-expert user to extract shorelines from Landsat 5, Landsat 7, Landsat 8, Landsat 9 and Sentinel-2 images.
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The shoreline detection algorithm implemented in CoastSat is optimised for sandy beach coastlines. It combines a sub-pixel border segmentation and an image classification component, which refines the segmentation into four distinct categories such that the shoreline detection is specific to the sand/water interface.
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The toolbox has the following functionalities:
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1. easy retrieval of satellite imagery spanning the user-defined region of interest and time period from Google Earth Engine, including state-of-the-art pre-processing steps (re-projecting the different bands, pansharpening, advanced cloud masking).
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2. automated extraction of shorelines from all the selected images using a sub-pixel resolution technique and options for quality-control.
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3. intersection of the 2D shorelines with user-defined shore-normal transects.
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4. tidal correction using tide/water levels and an estimate of the beach slope.
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5. post-processing of the shoreline time-series, despiking and seasonal averaging.
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6. Beach slope estimation using satellite-derived shorelines and predicted tides
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