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Automated High-Resolution Time Series Mapping of Mangrove Forests Damaged by Hurricane Irma in Southwest Florida
by
Murray, Tylar
, Jessen, Brita
, Barry, Michael J.
, McCarthy, Matthew J.
, Schmid, Jill
, McIntosh, Jessica
, Muller-Karger, Frank E.
, Figueroa, Marissa
in
algorithms
/ automation
/ data collection
/ estuaries
/ Florida
/ highlands
/ hurricanes
/ image analysis
/ land cover
/ mangrove forests
/ National Estuarine Research Reserve (NERR)
/ remote sensing
/ Rookery Bay
/ soil
/ sunglint
/ supercomputing
/ time series analysis
/ wetlands
/ wind
/ WorldView-2
2020
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Automated High-Resolution Time Series Mapping of Mangrove Forests Damaged by Hurricane Irma in Southwest Florida
by
Murray, Tylar
, Jessen, Brita
, Barry, Michael J.
, McCarthy, Matthew J.
, Schmid, Jill
, McIntosh, Jessica
, Muller-Karger, Frank E.
, Figueroa, Marissa
in
algorithms
/ automation
/ data collection
/ estuaries
/ Florida
/ highlands
/ hurricanes
/ image analysis
/ land cover
/ mangrove forests
/ National Estuarine Research Reserve (NERR)
/ remote sensing
/ Rookery Bay
/ soil
/ sunglint
/ supercomputing
/ time series analysis
/ wetlands
/ wind
/ WorldView-2
2020
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Do you wish to request the book?
Automated High-Resolution Time Series Mapping of Mangrove Forests Damaged by Hurricane Irma in Southwest Florida
by
Murray, Tylar
, Jessen, Brita
, Barry, Michael J.
, McCarthy, Matthew J.
, Schmid, Jill
, McIntosh, Jessica
, Muller-Karger, Frank E.
, Figueroa, Marissa
in
algorithms
/ automation
/ data collection
/ estuaries
/ Florida
/ highlands
/ hurricanes
/ image analysis
/ land cover
/ mangrove forests
/ National Estuarine Research Reserve (NERR)
/ remote sensing
/ Rookery Bay
/ soil
/ sunglint
/ supercomputing
/ time series analysis
/ wetlands
/ wind
/ WorldView-2
2020
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Automated High-Resolution Time Series Mapping of Mangrove Forests Damaged by Hurricane Irma in Southwest Florida
Journal Article
Automated High-Resolution Time Series Mapping of Mangrove Forests Damaged by Hurricane Irma in Southwest Florida
2020
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Overview
In September of 2017, Hurricane Irma made landfall within the Rookery Bay National Estuarine Research Reserve of southwest Florida (USA) as a category 3 storm with winds in excess of 200 km h−1. We mapped the extent of the hurricane’s impact on coastal land cover with a seasonal time series of satellite imagery. Very high-resolution (i.e., <5 m pixel) satellite imagery has proven effective to map wetland ecosystems, but challenges in data acquisition and storage, algorithm training, and image processing have prevented large-scale and time-series mapping of these data. We describe our approach to address these issues to evaluate Rookery Bay ecosystem damage and recovery using 91 WorldView-2 satellite images collected between 2010 and 2018 mapped using automated techniques and validated with a field campaign. Land cover was classified seasonally at 2 m resolution (i.e., healthy mangrove, degraded mangrove, upland, soil, and water) with an overall accuracy of 82%. Digital change detection methods show that hurricane-related degradation was 17% of mangrove forest (~5 km2). Approximately 35% (1.7 km2) of this loss recovered one year after Hurricane Irma. The approach completed the mapping approximately 200 times faster than existing methods, illustrating the ease with which regional high-resolution mapping may be accomplished efficiently.
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