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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ftmdpi:oai:mdpi.com:/2072-4292/14/13/3000/ 2023-08-20T04:10:03+02:00 Remote Sensing of Coastal Vegetation Phenology in a Cold Temperate Intertidal System: Implications for Classification of Coastal Habitats Brigitte Légaré Simon Bélanger Rakesh Kumar Singh Pascal Bernatchez Mathieu Cusson agris 2022-06-23 application/pdf https://doi.org/10.3390/rs14133000 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs14133000 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 13; Pages: 3000 vegetation phenology spectral signature intertidal coastal ecosystem remote sensing eelgrass ( Zostera marina L.) saltmarsh classification Text 2022 ftmdpi https://doi.org/10.3390/rs14133000 2023-08-01T05:28:13Z 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 (Zostera marina L.), saltmarsh cordgrass (Spartina alterniflora), creeping saltbush (Atriplex prostrata), macroalgae (Ascophyllum nodosum, and Fucus vesiculosus) 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 (Rrs(λ)). The results indicate that even when substantial vegetation growth is observed, the variation in Rrs(λ) 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. Text Subarctic MDPI Open Access Publishing Remote Sensing 14 13 3000 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
vegetation phenology spectral signature intertidal coastal ecosystem remote sensing eelgrass ( Zostera marina L.) saltmarsh classification |
spellingShingle |
vegetation phenology spectral signature intertidal coastal ecosystem remote sensing eelgrass ( Zostera marina L.) saltmarsh classification 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 |
topic_facet |
vegetation phenology spectral signature intertidal coastal ecosystem remote sensing eelgrass ( Zostera marina L.) saltmarsh classification |
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 (Zostera marina L.), saltmarsh cordgrass (Spartina alterniflora), creeping saltbush (Atriplex prostrata), macroalgae (Ascophyllum nodosum, and Fucus vesiculosus) 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 (Rrs(λ)). The results indicate that even when substantial vegetation growth is observed, the variation in Rrs(λ) 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. |
format |
Text |
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 |
title |
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_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_sort |
remote sensing of coastal vegetation phenology in a cold temperate intertidal system: implications for classification of coastal habitats |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14133000 |
op_coverage |
agris |
genre |
Subarctic |
genre_facet |
Subarctic |
op_source |
Remote Sensing; Volume 14; Issue 13; Pages: 3000 |
op_relation |
https://dx.doi.org/10.3390/rs14133000 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14133000 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
13 |
container_start_page |
3000 |
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1774723960138629120 |