Observing Changes in the Mangrove Forests of the South Florida Everglades following Hurricane Irma using Remote Sensing Measurements
Abstract
The South Florida mangrove forests provide invaluable ecosystem services, including carbon storage, habitat for many species, and protection of coastal areas from extreme weather events. In September 2017, Hurricane Irma hit the coast of southwest Florida impacting a large swath of mangrove forests. A combination of hurricane strength winds and high storm surge across the area resulted in defoliation, broken branches, and downed trees changing the forest structure. Evaluating changes in mangrove forests structure and their recovery is important as loss or change in mangrove forest can lead to loss in the ecosystems services they provide for the Everglades.
In this study we quantify changes to mangrove forests caused by Hurricane Irma, as well as their recovery overtime. The study relies on both new generation remote sensing technology and a wide array of available multispectral data. New generation technologies such as NASA Goddard's Lidar, Hyperspectral and Thermal imager (G-LiHT) provide an opportunity to asses changes in mangrove forests using 3D and high resolution data to asses mangrove forests at different tree structure levels (i.e canopy, tree trunks, forest floor). We use high-resolution airborne imagery collected by G-LiHT before and after Hurricane Irma allowing us to investigate changes in woody vegetation and canopy structure of mangroves induced by Irma. Coarse woody debris and standing dead biomass models have been developed using novel metrics derived from corrected G-LiHT data and field observations. Traditional multispectral data provides opportunity to monitor and asses forest changes overtime using remotely sensed measurements that help asses changes in mangrove phenology. We use the Normalized Difference Vegetation Index (NDVI) from multiple multispectral remote sensing instruments to observe and model reduction and recovery of mangrove canopy in the Everglades overtime. Based on both data types, we develop methods and models needed to quantify and understand the damage and recovery of mangrove forest in the Everglades due to Hurricane Irma. We plan to use these methodologies to evaluate damage and recovery of mangrove forests in response to extreme weather events, worldwide.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.B11E2379C
- Keywords:
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- 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCES;
- 0480 Remote sensing;
- BIOGEOSCIENCES;
- 1294 Instruments and techniques;
- GEODESY AND GRAVITY