Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine
Mangroves form the dominant coastal plant community of low-energy tropical intertidal habitats and provide critical ecosystem services to humans and the environment. However, more frequent and increasingly powerful hurricanes and storm surges are creating additional pressure on the natural resilienc...
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MDPI AG
2025-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/14/2485 |
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| author | Michael R. Routhier Gregg E. Moore Barrett N. Rock Stanley Glidden Matthew Duckett Susan Zaluski |
| author_facet | Michael R. Routhier Gregg E. Moore Barrett N. Rock Stanley Glidden Matthew Duckett Susan Zaluski |
| author_sort | Michael R. Routhier |
| collection | DOAJ |
| description | Mangroves form the dominant coastal plant community of low-energy tropical intertidal habitats and provide critical ecosystem services to humans and the environment. However, more frequent and increasingly powerful hurricanes and storm surges are creating additional pressure on the natural resilience of these threatened coastal ecosystems. Advances in remote sensing techniques and approaches are critical to providing robust quantitative monitoring of post-storm mangrove forest recovery to better prioritize the often-limited resources available for the restoration of these storm-damaged habitats. Here, we build on previously utilized spatial and temporal ranges of European Space Agency (ESA) Sentinel satellite imagery to monitor and map the recovery of the mangrove forests of the British Virgin Islands (BVI) since the occurrence of back-to-back category 5 hurricanes, Irma and Maria, on September 6 and 19 of 2017, respectively. Pre- to post-storm changes in coastal mangrove forest health were assessed annually using the normalized difference vegetation index (NDVI) and moisture stress index (MSI) from 2016 to 2023 using Google Earth Engine. Results reveal a steady trajectory towards forest health recovery on many of the Territory’s islands since the storms’ impacts in 2017. However, some mangrove patches are slower to recover, such as those on the islands of Virgin Gorda and Jost Van Dyke, and, in some cases, have shown a continued decline (e.g., Prickly Pear Island). Our work also uses a linear ANCOVA model to assess a variety of geospatial, environmental, and anthropogenic drivers for mangrove recovery as a function of NDVI pre-storm and post-storm conditions. The model suggests that roughly 58% of the variability in the 7-year difference (2016 to 2023) in NDVI may be related by a positive linear relationship with the variable of population within 0.5 km and a negative linear relationship with the variables of northwest aspect vs. southwest aspect, island size, temperature, and slope. |
| format | Article |
| id | doaj-art-e8e9c9db3a4246f49b80609def03fe1b |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-e8e9c9db3a4246f49b80609def03fe1b2025-08-20T02:47:14ZengMDPI AGRemote Sensing2072-42922025-07-011714248510.3390/rs17142485Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth EngineMichael R. Routhier0Gregg E. Moore1Barrett N. Rock2Stanley Glidden3Matthew Duckett4Susan Zaluski5Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USADepartment of Biological Sciences, University of New Hampshire, Durham, NH 03824, USAInstitute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USAInstitute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USADepartment of Mathematics, University of New Hampshire, Durham, NH 03824, USACenter for Marine and Maritime Studies, H. Lavity Stoutt Community College, Road Town, Tortola, British Virgin IslandsMangroves form the dominant coastal plant community of low-energy tropical intertidal habitats and provide critical ecosystem services to humans and the environment. However, more frequent and increasingly powerful hurricanes and storm surges are creating additional pressure on the natural resilience of these threatened coastal ecosystems. Advances in remote sensing techniques and approaches are critical to providing robust quantitative monitoring of post-storm mangrove forest recovery to better prioritize the often-limited resources available for the restoration of these storm-damaged habitats. Here, we build on previously utilized spatial and temporal ranges of European Space Agency (ESA) Sentinel satellite imagery to monitor and map the recovery of the mangrove forests of the British Virgin Islands (BVI) since the occurrence of back-to-back category 5 hurricanes, Irma and Maria, on September 6 and 19 of 2017, respectively. Pre- to post-storm changes in coastal mangrove forest health were assessed annually using the normalized difference vegetation index (NDVI) and moisture stress index (MSI) from 2016 to 2023 using Google Earth Engine. Results reveal a steady trajectory towards forest health recovery on many of the Territory’s islands since the storms’ impacts in 2017. However, some mangrove patches are slower to recover, such as those on the islands of Virgin Gorda and Jost Van Dyke, and, in some cases, have shown a continued decline (e.g., Prickly Pear Island). Our work also uses a linear ANCOVA model to assess a variety of geospatial, environmental, and anthropogenic drivers for mangrove recovery as a function of NDVI pre-storm and post-storm conditions. The model suggests that roughly 58% of the variability in the 7-year difference (2016 to 2023) in NDVI may be related by a positive linear relationship with the variable of population within 0.5 km and a negative linear relationship with the variables of northwest aspect vs. southwest aspect, island size, temperature, and slope.https://www.mdpi.com/2072-4292/17/14/2485mangrove recoveryforest healthhurricanes Irma and Mariagoogle earth enginesentinel satellite imageryNDVI |
| spellingShingle | Michael R. Routhier Gregg E. Moore Barrett N. Rock Stanley Glidden Matthew Duckett Susan Zaluski Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine Remote Sensing mangrove recovery forest health hurricanes Irma and Maria google earth engine sentinel satellite imagery NDVI |
| title | Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine |
| title_full | Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine |
| title_fullStr | Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine |
| title_full_unstemmed | Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine |
| title_short | Assessing Mangrove Forest Recovery in the British Virgin Islands After Hurricanes Irma and Maria with Sentinel-2 Imagery and Google Earth Engine |
| title_sort | assessing mangrove forest recovery in the british virgin islands after hurricanes irma and maria with sentinel 2 imagery and google earth engine |
| topic | mangrove recovery forest health hurricanes Irma and Maria google earth engine sentinel satellite imagery NDVI |
| url | https://www.mdpi.com/2072-4292/17/14/2485 |
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