Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats

Intertidal vegetation provides important ecological functions, such as food and shelter for wildlife and ecological services with increased coastline protection from erosion. In cold temperate and subarctic environments, the short growing season has a significant impact on the phenological response...

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Main Authors: Brigitte Légaré, Simon Bélanger, Rakesh Kumar Singh, Pascal Bernatchez, Mathieu Cusson
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/14/13/3000
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author Brigitte Légaré
Simon Bélanger
Rakesh Kumar Singh
Pascal Bernatchez
Mathieu Cusson
author_facet Brigitte Légaré
Simon Bélanger
Rakesh Kumar Singh
Pascal Bernatchez
Mathieu Cusson
author_sort Brigitte Légaré
collection DOAJ
description Intertidal vegetation provides important ecological functions, such as food and shelter for wildlife and ecological services with increased coastline protection from erosion. In cold temperate and subarctic environments, the short growing season has a significant impact on the phenological response of the different vegetation types, which must be considered for their mapping using satellite remote sensing technologies. This study focuses on the effect of the phenology of vegetation in the intertidal ecosystems on remote sensing outputs. The studied sites were dominated by eelgrass (<i>Zostera marina</i> L.), saltmarsh cordgrass (<i>Spartina alterniflora</i>), creeping saltbush (<i>Atriplex prostrata</i>), macroalgae (<i>Ascophyllum nodosum</i>, and <i>Fucus vesiculosus</i>) attached to scattered boulders. In situ data were collected on ten occasions from May through October 2019 and included biophysical properties (e.g., leaf area index) and hyperspectral reflectance spectra (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>R</mi><mrow><mi>r</mi><mi>s</mi></mrow></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula>). The results indicate that even when substantial vegetation growth is observed, the variation in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>R</mi><mrow><mi>r</mi><mi>s</mi></mrow></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula> is not significant at the beginning of the growing season, limiting the spectral separability using multispectral imagery. The spectral separability between vegetation types was maximum at the beginning of the season (early June) when the vegetation had not reached its maximum growth. Seasonal time series of the normalized difference vegetation index (NDVI) values were derived from multispectral sensors (Sentinel-2 multispectral instrument (MSI) and PlanetScope) and were validated using in situ-derived NDVI. The results indicate that the phenology of intertidal vegetation can be monitored by satellite if the number of observations obtained at a low tide is sufficient, which helps to discriminate plant species and, therefore, the mapping of vegetation. The optimal period for vegetation mapping was September for the study area.
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spelling doaj.art-feb771a227f94fb593acbe8dfd1178142023-12-03T14:19:49ZengMDPI AGRemote Sensing2072-42922022-06-011413300010.3390/rs14133000Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal HabitatsBrigitte Légaré0Simon Bélanger1Rakesh Kumar Singh2Pascal Bernatchez3Mathieu Cusson4Département de Biologie, Université du Québec à Rimouski, Chimie et Géographie, Québec-Océan et BORÉAS, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, CanadaDépartement de Biologie, Université du Québec à Rimouski, Chimie et Géographie, Québec-Océan et BORÉAS, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, CanadaDépartement de Biologie, Université du Québec à Rimouski, Chimie et Géographie, Québec-Océan et BORÉAS, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, CanadaDépartement de Biologie, Université du Québec à Rimouski, Chimie et Géographie, Québec-Océan et BORÉAS, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, CanadaDépartement des Sciences Fondamentales, Université du Québec à Chicoutimi, Québec-Océan 555, Boulevard de l’Université, Chicoutimi, QC G7H 2B1, CanadaIntertidal vegetation provides important ecological functions, such as food and shelter for wildlife and ecological services with increased coastline protection from erosion. In cold temperate and subarctic environments, the short growing season has a significant impact on the phenological response of the different vegetation types, which must be considered for their mapping using satellite remote sensing technologies. This study focuses on the effect of the phenology of vegetation in the intertidal ecosystems on remote sensing outputs. The studied sites were dominated by eelgrass (<i>Zostera marina</i> L.), saltmarsh cordgrass (<i>Spartina alterniflora</i>), creeping saltbush (<i>Atriplex prostrata</i>), macroalgae (<i>Ascophyllum nodosum</i>, and <i>Fucus vesiculosus</i>) attached to scattered boulders. In situ data were collected on ten occasions from May through October 2019 and included biophysical properties (e.g., leaf area index) and hyperspectral reflectance spectra (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>R</mi><mrow><mi>r</mi><mi>s</mi></mrow></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula>). The results indicate that even when substantial vegetation growth is observed, the variation in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>R</mi><mrow><mi>r</mi><mi>s</mi></mrow></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula> is not significant at the beginning of the growing season, limiting the spectral separability using multispectral imagery. The spectral separability between vegetation types was maximum at the beginning of the season (early June) when the vegetation had not reached its maximum growth. Seasonal time series of the normalized difference vegetation index (NDVI) values were derived from multispectral sensors (Sentinel-2 multispectral instrument (MSI) and PlanetScope) and were validated using in situ-derived NDVI. The results indicate that the phenology of intertidal vegetation can be monitored by satellite if the number of observations obtained at a low tide is sufficient, which helps to discriminate plant species and, therefore, the mapping of vegetation. The optimal period for vegetation mapping was September for the study area.https://www.mdpi.com/2072-4292/14/13/3000vegetation phenologyspectral signatureintertidal coastal ecosystemremote sensingeelgrass (<i>Zostera marina</i> L.)saltmarsh
spellingShingle Brigitte Légaré
Simon Bélanger
Rakesh Kumar Singh
Pascal Bernatchez
Mathieu Cusson
Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats
Remote Sensing
vegetation phenology
spectral signature
intertidal coastal ecosystem
remote sensing
eelgrass (<i>Zostera marina</i> L.)
saltmarsh
title Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats
title_full Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats
title_fullStr Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats
title_full_unstemmed Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats
title_short Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats
title_sort remote sensing of coastal vegetation phenology in a cold temperate intertidal system implications for classification of coastal habitats
topic vegetation phenology
spectral signature
intertidal coastal ecosystem
remote sensing
eelgrass (<i>Zostera marina</i> L.)
saltmarsh
url https://www.mdpi.com/2072-4292/14/13/3000
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