Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA)
Mangrove forests provide a range of ecosystem services but may be increasingly threatened by climate change in the North Atlantic due to high-intensity storms. Hurricane Irma (Category 5) hit the northern coast of Cuba in September 2017, causing widespread damage to mangroves; losses have not yet be...
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ftdoajarticles:oai:doaj.org/article:a35ba752b6774335bf1be5209e289106 2023-06-11T04:14:59+02:00 Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) Hannah C. Turner Gillian L. Galford Norgis Hernandez Lopez Armando Falcón Méndez Daily Yanetsy Borroto-Escuela Idania Hernández Ramos Patricia González-Díaz 2023-05-01T00:00:00Z https://doi.org/10.3390/rs15102495 https://doaj.org/article/a35ba752b6774335bf1be5209e289106 EN eng MDPI AG https://www.mdpi.com/2072-4292/15/10/2495 https://doaj.org/toc/2072-4292 doi:10.3390/rs15102495 2072-4292 https://doaj.org/article/a35ba752b6774335bf1be5209e289106 Remote Sensing, Vol 15, Iss 2495, p 2495 (2023) mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs15102495 2023-05-28T00:33:02Z Mangrove forests provide a range of ecosystem services but may be increasingly threatened by climate change in the North Atlantic due to high-intensity storms. Hurricane Irma (Category 5) hit the northern coast of Cuba in September 2017, causing widespread damage to mangroves; losses have not yet been extensively documented due to financial and logistical constraints for local scientists. Our team estimated Irma’s impacts on Cuban ecosystems in a coastal and upland study area spanning over 1.7 million ha. We developed a multi-resolution time series “vegetation anomaly” approach, where post-disturbance observations in photosynthetically active vegetation (Enhanced Vegetation Index, EVI) were normalized to the reference period (dry season mean over a historical time series). The Hurricane Disturbance Vegetation Anomaly (HDVA) was used to estimate the extent, severity, and temporal patterns of ecological changes with Sentinel-2 and MODIS data and used vicarious validation with microsatellite interpretation (Planet). HDVA values were classed to convey qualitative labels useful for local scientists: (1) Catastrophic, (2) Severe, (3) Moderate, (4) Mild, and (5) No Loss. Sentinel-2 had a limited reference period (2015–2017) compared to MODIS (2000–2017), yet the HDVA patterns were similar. Mangrove and wetlands (>265,000 ha) sustained widespread damages, with a staggering 78% showing damage, largely severe to catastrophic (0–0.81 HDVA; >207,000 ha). The damaged area is 24 times greater than impacts from Irma as documented elsewhere. Caguanes National Park (>8400 ha, excluding marine zones) experienced concentrated, severe mangrove and wetland damages (nearly 4000 ha). The phenological declines from Irma’s impacts took up to 17 months to fully actualize, a much longer period than previously suggested. In contrast, dry forests saw rapid green flushes post-hurricane. With the increase of high-intensity storm events and other threats to ecosystems, the HDVA methods outlined here can be used to assess intense to ... Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Remote Sensing 15 10 2495 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba Science Q |
spellingShingle |
mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba Science Q Hannah C. Turner Gillian L. Galford Norgis Hernandez Lopez Armando Falcón Méndez Daily Yanetsy Borroto-Escuela Idania Hernández Ramos Patricia González-Díaz Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) |
topic_facet |
mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba Science Q |
description |
Mangrove forests provide a range of ecosystem services but may be increasingly threatened by climate change in the North Atlantic due to high-intensity storms. Hurricane Irma (Category 5) hit the northern coast of Cuba in September 2017, causing widespread damage to mangroves; losses have not yet been extensively documented due to financial and logistical constraints for local scientists. Our team estimated Irma’s impacts on Cuban ecosystems in a coastal and upland study area spanning over 1.7 million ha. We developed a multi-resolution time series “vegetation anomaly” approach, where post-disturbance observations in photosynthetically active vegetation (Enhanced Vegetation Index, EVI) were normalized to the reference period (dry season mean over a historical time series). The Hurricane Disturbance Vegetation Anomaly (HDVA) was used to estimate the extent, severity, and temporal patterns of ecological changes with Sentinel-2 and MODIS data and used vicarious validation with microsatellite interpretation (Planet). HDVA values were classed to convey qualitative labels useful for local scientists: (1) Catastrophic, (2) Severe, (3) Moderate, (4) Mild, and (5) No Loss. Sentinel-2 had a limited reference period (2015–2017) compared to MODIS (2000–2017), yet the HDVA patterns were similar. Mangrove and wetlands (>265,000 ha) sustained widespread damages, with a staggering 78% showing damage, largely severe to catastrophic (0–0.81 HDVA; >207,000 ha). The damaged area is 24 times greater than impacts from Irma as documented elsewhere. Caguanes National Park (>8400 ha, excluding marine zones) experienced concentrated, severe mangrove and wetland damages (nearly 4000 ha). The phenological declines from Irma’s impacts took up to 17 months to fully actualize, a much longer period than previously suggested. In contrast, dry forests saw rapid green flushes post-hurricane. With the increase of high-intensity storm events and other threats to ecosystems, the HDVA methods outlined here can be used to assess intense to ... |
format |
Article in Journal/Newspaper |
author |
Hannah C. Turner Gillian L. Galford Norgis Hernandez Lopez Armando Falcón Méndez Daily Yanetsy Borroto-Escuela Idania Hernández Ramos Patricia González-Díaz |
author_facet |
Hannah C. Turner Gillian L. Galford Norgis Hernandez Lopez Armando Falcón Méndez Daily Yanetsy Borroto-Escuela Idania Hernández Ramos Patricia González-Díaz |
author_sort |
Hannah C. Turner |
title |
Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) |
title_short |
Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) |
title_full |
Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) |
title_fullStr |
Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) |
title_full_unstemmed |
Extent, Severity, and Temporal Patterns of Damage to Cuba’s Ecosystems following Hurricane Irma: MODIS and Sentinel-2 Hurricane Disturbance Vegetation Anomaly (HDVA) |
title_sort |
extent, severity, and temporal patterns of damage to cuba’s ecosystems following hurricane irma: modis and sentinel-2 hurricane disturbance vegetation anomaly (hdva) |
publisher |
MDPI AG |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15102495 https://doaj.org/article/a35ba752b6774335bf1be5209e289106 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Remote Sensing, Vol 15, Iss 2495, p 2495 (2023) |
op_relation |
https://www.mdpi.com/2072-4292/15/10/2495 https://doaj.org/toc/2072-4292 doi:10.3390/rs15102495 2072-4292 https://doaj.org/article/a35ba752b6774335bf1be5209e289106 |
op_doi |
https://doi.org/10.3390/rs15102495 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
10 |
container_start_page |
2495 |
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1768371415386423296 |