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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ftmdpi:oai:mdpi.com:/2072-4292/15/10/2495/ 2023-08-20T04:08:32+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 agris 2023-05-09 application/pdf https://doi.org/10.3390/rs15102495 EN eng Multidisciplinary Digital Publishing Institute Ecological Remote Sensing https://dx.doi.org/10.3390/rs15102495 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 15; Issue 10; Pages: 2495 mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba Text 2023 ftmdpi https://doi.org/10.3390/rs15102495 2023-08-01T10:00:21Z 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 ... Text North Atlantic MDPI Open Access Publishing Remote Sensing 15 10 2495 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba |
spellingShingle |
mangroves multitemporal remote sensing deforestation climate change Sentinel-2 Cuba 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 |
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 |
Text |
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 |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15102495 |
op_coverage |
agris |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Remote Sensing; Volume 15; Issue 10; Pages: 2495 |
op_relation |
Ecological Remote Sensing https://dx.doi.org/10.3390/rs15102495 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
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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