InletTracker: An open-source Python toolkit for historic and near real-time monitoring of coastal inlets from Landsat and Sentinel-2

Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at multi-decadal time scales. Here, we introduce InletTracker (https://github.com/VHeimhuber/InletTracker), a new tool that reconstructs the time-evolving...

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Vydané v:	Geomorphology (Amsterdam, Netherlands) Ročník 389; s. 107830
Hlavní autori:	Heimhuber, Valentin, Vos, Kilian, Fu, Wanru, Glamore, William
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 15.09.2021
Predmet:	Australia Coastal monitoring computer software data collection Google Earth Engine ICOLL Intermittent estuaries Internet Landsat Least-cost pathfinding Morphodynamics Remote sensing socioeconomics Tidal inlets Australia ICOLL Least-cost pathfinding Morphodynamics Google Earth Engine Tidal inlets Coastal monitoring Intermittent estuaries Remote sensing
ISSN:	0169-555X, 1872-695X
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Abstract	Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at multi-decadal time scales. Here, we introduce InletTracker (https://github.com/VHeimhuber/InletTracker), a new tool that reconstructs the time-evolving state of dynamic coastal inlets over the last 30+ years from publicly available Landsat 5, 7 and 8 and Sentinel-2 satellite imagery. InletTracker is a Google Earth Engine enabled python toolkit that uses a novel least-cost pathfinding approach to trace inlets along and across the berm (i.e., barrier, bar), and then analyses the resulting transects to infer whether an inlet is open or closed. To evaluate the performance of InletTracker, we applied the tool at 12 intermittent coastal inlets with different maximum inlet widths (≤30-200 m), geomorphological setting and opening frequency located across Southeastern and Southwestern Australia. This exercise involved 6363 unique binary inlet state predictions (i.e., open vs. closed) that were validated against visually inferred inlet states (from the satellite imagery itself), on-ground observational records, and in-situ water levels from inside the inlets. InletTracker reproduced the visually inferred inlet states with an average accuracy across all sites of 89% for the combined Landsat and Sentinel-2 record (15-30 m resolution) and 94% for the Sentinel-2 record only (10 m resolution). Overall, we found good agreement between the predictions of the tool and the three independent validation datasets for all but the smallest sites. Our results demonstrate that InletTracker will enable coastal engineers, managers, and researchers to gain new insights into the dynamics and drivers of coastal inlets or similar shallow water landforms such as river mouths, tidal flats, floodplains, wetlands or delta channel networks. Further, the high spatial (i.e., 10 m) and temporal (i.e., 5-daily) resolution provided by Sentinel-2 makes InletTracker a viable option for near real-time monitoring of even relatively small inlets with a minimum channel width of around 10 m and frequent, short-duration, openings. [Display omitted] •We present a new method for automated monitoring of dynamic coastal inlets.•Path finding is used to accurately trace openings through multi-decadal imagery.•The method is tested based on 12 intermittent coastal inlets in Australia.•Validation revealed excellent performance for detecting inlet states.•The tool will provide new insights into inlet dynamics around the globe.
AbstractList	Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at multi-decadal time scales. Here, we introduce InletTracker (https://github.com/VHeimhuber/InletTracker), a new tool that reconstructs the time-evolving state of dynamic coastal inlets over the last 30+ years from publicly available Landsat 5, 7 and 8 and Sentinel-2 satellite imagery. InletTracker is a Google Earth Engine enabled python toolkit that uses a novel least-cost pathfinding approach to trace inlets along and across the berm (i.e., barrier, bar), and then analyses the resulting transects to infer whether an inlet is open or closed. To evaluate the performance of InletTracker, we applied the tool at 12 intermittent coastal inlets with different maximum inlet widths (≤30-200 m), geomorphological setting and opening frequency located across Southeastern and Southwestern Australia. This exercise involved 6363 unique binary inlet state predictions (i.e., open vs. closed) that were validated against visually inferred inlet states (from the satellite imagery itself), on-ground observational records, and in-situ water levels from inside the inlets. InletTracker reproduced the visually inferred inlet states with an average accuracy across all sites of 89% for the combined Landsat and Sentinel-2 record (15-30 m resolution) and 94% for the Sentinel-2 record only (10 m resolution). Overall, we found good agreement between the predictions of the tool and the three independent validation datasets for all but the smallest sites. Our results demonstrate that InletTracker will enable coastal engineers, managers, and researchers to gain new insights into the dynamics and drivers of coastal inlets or similar shallow water landforms such as river mouths, tidal flats, floodplains, wetlands or delta channel networks. Further, the high spatial (i.e., 10 m) and temporal (i.e., 5-daily) resolution provided by Sentinel-2 makes InletTracker a viable option for near real-time monitoring of even relatively small inlets with a minimum channel width of around 10 m and frequent, short-duration, openings. Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at multi-decadal time scales. Here, we introduce InletTracker (https://github.com/VHeimhuber/InletTracker), a new tool that reconstructs the time-evolving state of dynamic coastal inlets over the last 30+ years from publicly available Landsat 5, 7 and 8 and Sentinel-2 satellite imagery. InletTracker is a Google Earth Engine enabled python toolkit that uses a novel least-cost pathfinding approach to trace inlets along and across the berm (i.e., barrier, bar), and then analyses the resulting transects to infer whether an inlet is open or closed. To evaluate the performance of InletTracker, we applied the tool at 12 intermittent coastal inlets with different maximum inlet widths (≤30-200 m), geomorphological setting and opening frequency located across Southeastern and Southwestern Australia. This exercise involved 6363 unique binary inlet state predictions (i.e., open vs. closed) that were validated against visually inferred inlet states (from the satellite imagery itself), on-ground observational records, and in-situ water levels from inside the inlets. InletTracker reproduced the visually inferred inlet states with an average accuracy across all sites of 89% for the combined Landsat and Sentinel-2 record (15-30 m resolution) and 94% for the Sentinel-2 record only (10 m resolution). Overall, we found good agreement between the predictions of the tool and the three independent validation datasets for all but the smallest sites. Our results demonstrate that InletTracker will enable coastal engineers, managers, and researchers to gain new insights into the dynamics and drivers of coastal inlets or similar shallow water landforms such as river mouths, tidal flats, floodplains, wetlands or delta channel networks. Further, the high spatial (i.e., 10 m) and temporal (i.e., 5-daily) resolution provided by Sentinel-2 makes InletTracker a viable option for near real-time monitoring of even relatively small inlets with a minimum channel width of around 10 m and frequent, short-duration, openings. [Display omitted] •We present a new method for automated monitoring of dynamic coastal inlets.•Path finding is used to accurately trace openings through multi-decadal imagery.•The method is tested based on 12 intermittent coastal inlets in Australia.•Validation revealed excellent performance for detecting inlet states.•The tool will provide new insights into inlet dynamics around the globe.
ArticleNumber	107830
Author	Fu, Wanru Heimhuber, Valentin Vos, Kilian Glamore, William
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Snippet	Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at...
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SubjectTerms	Australia Coastal monitoring computer software data collection Google Earth Engine ICOLL Intermittent estuaries Internet Landsat Least-cost pathfinding Morphodynamics Remote sensing socioeconomics Tidal inlets
Title	InletTracker: An open-source Python toolkit for historic and near real-time monitoring of coastal inlets from Landsat and Sentinel-2
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