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Massachusetts Institute of Technology

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 inhomogeneity of the area tested, (3) shoot density inhomogeneity of the area tested, and (4) environmental conditions.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Grantor dc:publisher
Massachusetts Institute of Technology
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.

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/157228
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/157228

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Garber, Samantha C.. Analyzing Remote Sensing-Derived Normal Difference Vegetation Index to Predict Coastal Protection by Spartina alterniflora. Massachusetts Institute of Technology, 2024. https://hdl.handle.net/1721.1/157228