Analyzing remote sensing-derived normal difference vegetation index to predict coastal protection by Spartina alterniflora

dc.contributor.advisor Nepf, Heidi M.
dc.contributor.author Garber, Samantha C.
dc.date.accessioned 2024-08-29T17:54:13Z
dc.date.available 2024-08-29T17:54:13Z
dc.date.issued 2024-09
dc.description Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2024.
dc.description.abstract Coastal vegetation can provide protection to the coastline through its root structures, which reduce soil erosion, and its stem structures, which dissipate wave energy. The drag a plant induces could be used to quantify the amount of coastal protection that is provided. This study combined field measurements and drone surveys to develop methods for quantifying vegetation drag, focusing on Spartina alterniflora (S. alterniflora), a smooth cordgrass native to the study site: Waquoit Bay National Estuarine Research Reserve. The drag of a single plant is proportional to frontal area. The drag per bed area is proportional to the drag of a single plant and the number of stems per bed area. This study collected plant samples over the growing season to generate allometric relationships between tiller height and individual plant biomass and frontal area, which provides a way to translate remotely-sensed measures of biomass into stem count and frontal area per bed area. The frontal area was measured through digital imaging of individual plants. The elastic modulus of the stem was also measured using an Instron testing machine. For sixteen 1m x 1m test plots, Normalized Difference Vegetation Index (NDVI) extracted from drone multispectral imagery was compared to measured stem count and estimated biomass. The study compared two different years and three time points within a growing season [August 2022; June, August, October 2023). In addition, at three plots the stem count was manually altered by cutting out 50% and 100% of the plants. This study found that while NDVI can be used to determine the abundance of S. alterniflora, there are several limitations that cause the correlations to be case-specific. Limitations to NDVI-S. alterniflora correlations included: (1) saturation, (2) species in-homogeneity of the area tested, (3) shoot density inhomogeneity of the area tested, and (4) environmental conditions.
dc.identifier.citation Garber, S. C. (2024) Analyzing remote sensing-derived normal difference vegetation index to predict coastal protection by Spartina alterniflora [Master's thesis, Massachusetts Institute of Technology and Woods Hole Oceanographic Institution]. Woods Hole Open Access Server. https://doi.org/10.1575/1912/70398
dc.identifier.doi 10.1575/1912/70398
dc.identifier.uri https://hdl.handle.net/1912/70398
dc.language.iso en_US
dc.publisher Massachusetts Institute of Technology and Woods Hole Oceanographic Institution
dc.relation.ispartofseries WHOI Theses
dc.rights ©2024 Samantha C. Garber. The author hereby grants to MIT and WHOI a nonexclusive, worldwide, irrevocable, royalty-free license to exercise any and all rights under copyright, including to reproduce, preserve, distribute and publicly display copies of the thesis, or release the thesis under an open-access license.
dc.subject NDVI
dc.subject Spartina alterniflora
dc.subject Coastal protection
dc.title Analyzing remote sensing-derived normal difference vegetation index to predict coastal protection by Spartina alterniflora
dc.type Thesis
dspace.entity.type Publication
relation.isAuthorOfPublication 4eea7cac-9854-4e5e-9b6c-d5f30d51b08a
relation.isAuthorOfPublication.latestForDiscovery 4eea7cac-9854-4e5e-9b6c-d5f30d51b08a
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