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Massachusetts Institute of Technology and Woods Hole Oceanographic Institution

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

Abstract

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.

Degree

thesis:*
Grantor dc:publisher
Massachusetts Institute of Technology and Woods Hole Oceanographic Institution
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Garber, Samantha C.
Advisor dc:contributor.advisor
  • Nepf, Heidi M.

Subjects

dc:subject × 3

Rights

dc:rights
Statement 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.
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:darchive.mblwhoilibrary.org:1912/70398

Chain of custody

source
Harvested from
Woods Hole Oceanographic Institute
Base URL
darchive.mblwhoilibrary.org/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Garber, Samantha C.. Analyzing remote sensing-derived normal difference vegetation index to predict coastal protection by Spartina alterniflora. Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2024. https://hdl.handle.net/1912/70398