Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification

The La Grande River watershed, located in the James Bay region (54°N, Quebec, Canada), is a major contributor to the production of hydroelectricity in the province. Peatlands cover up to 20% of the terrestrial environment in this region. Their hydrological behavior is not well understood. The presen...

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Published in:Remote Sensing
Main Authors: Yann Dribault, Karem Chokmani, Monique Bernier
Format: Text
Language:English
Published: Molecular Diversity Preservation International 2012
Subjects:
fen
Online Access:https://doi.org/10.3390/rs4071887
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spelling ftmdpi:oai:mdpi.com:/2072-4292/4/7/1887/ 2023-08-20T04:07:49+02:00 Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification Yann Dribault Karem Chokmani Monique Bernier agris 2012-06-26 application/pdf https://doi.org/10.3390/rs4071887 EN eng Molecular Diversity Preservation International https://dx.doi.org/10.3390/rs4071887 https://creativecommons.org/licenses/by/3.0/ Remote Sensing; Volume 4; Issue 7; Pages: 1887-1912 remote sensing peatland fen hydrology GeoEye multispectral high resolution water level discharge object-based analysis Text 2012 ftmdpi https://doi.org/10.3390/rs4071887 2023-07-31T20:29:19Z The La Grande River watershed, located in the James Bay region (54°N, Quebec, Canada), is a major contributor to the production of hydroelectricity in the province. Peatlands cover up to 20% of the terrestrial environment in this region. Their hydrological behavior is not well understood. The present study is part of a multidisciplinary project which is aimed at analyzing the hydrological processes in these minerotrophic peatlands (fens) in order to provide effective monitoring tools to water managers. The objective of this study was to use VHR remote sensing data to understand the seasonal dynamics of the hydrology in fens. A series of 10 multispectral pan-sharpened GeoEye-1 images (with a spatial resolution of 40 cm) were acquired during the snow-free season (May to October) in 2009 and 2010, centered on two study sites in the Laforge sector (54°06'N; 72°30'W). These are two fens instrumented for continuous hydrometeorological monitoring (water level, discharge, precipitation, air temperature). An object-based classification procedure was set up and applied. It consisted of segmenting the imagery into objects using the multiresolution segmentation algorithm (MRIS) to delineate internal structures in the peatlands (aquatic, semi-aquatic, and terrestrial). Then, the objects were labeled using a fuzzy logic based algorithm. The overall classification accuracy of the 10 images was assessed to be 82%. The time series of the peatland mapping demonstrated the existence of important intra-seasonal spatial dynamics in the aquatic and semi-aquatic compartments. It was revealed that the dynamics amplitude depended on the morphological features of the fens. The observed spatial dynamics was also closely related to the evolution of the measured water levels. Text La Grande River James Bay MDPI Open Access Publishing Canada Remote Sensing 4 7 1887 1912
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic remote sensing
peatland
fen
hydrology
GeoEye
multispectral
high resolution
water level
discharge
object-based analysis
spellingShingle remote sensing
peatland
fen
hydrology
GeoEye
multispectral
high resolution
water level
discharge
object-based analysis
Yann Dribault
Karem Chokmani
Monique Bernier
Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification
topic_facet remote sensing
peatland
fen
hydrology
GeoEye
multispectral
high resolution
water level
discharge
object-based analysis
description The La Grande River watershed, located in the James Bay region (54°N, Quebec, Canada), is a major contributor to the production of hydroelectricity in the province. Peatlands cover up to 20% of the terrestrial environment in this region. Their hydrological behavior is not well understood. The present study is part of a multidisciplinary project which is aimed at analyzing the hydrological processes in these minerotrophic peatlands (fens) in order to provide effective monitoring tools to water managers. The objective of this study was to use VHR remote sensing data to understand the seasonal dynamics of the hydrology in fens. A series of 10 multispectral pan-sharpened GeoEye-1 images (with a spatial resolution of 40 cm) were acquired during the snow-free season (May to October) in 2009 and 2010, centered on two study sites in the Laforge sector (54°06'N; 72°30'W). These are two fens instrumented for continuous hydrometeorological monitoring (water level, discharge, precipitation, air temperature). An object-based classification procedure was set up and applied. It consisted of segmenting the imagery into objects using the multiresolution segmentation algorithm (MRIS) to delineate internal structures in the peatlands (aquatic, semi-aquatic, and terrestrial). Then, the objects were labeled using a fuzzy logic based algorithm. The overall classification accuracy of the 10 images was assessed to be 82%. The time series of the peatland mapping demonstrated the existence of important intra-seasonal spatial dynamics in the aquatic and semi-aquatic compartments. It was revealed that the dynamics amplitude depended on the morphological features of the fens. The observed spatial dynamics was also closely related to the evolution of the measured water levels.
format Text
author Yann Dribault
Karem Chokmani
Monique Bernier
author_facet Yann Dribault
Karem Chokmani
Monique Bernier
author_sort Yann Dribault
title Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification
title_short Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification
title_full Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification
title_fullStr Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification
title_full_unstemmed Monitoring Seasonal Hydrological Dynamics of Minerotrophic Peatlands Using Multi-Date GeoEye-1 Very High Resolution Imagery and Object-Based Classification
title_sort monitoring seasonal hydrological dynamics of minerotrophic peatlands using multi-date geoeye-1 very high resolution imagery and object-based classification
publisher Molecular Diversity Preservation International
publishDate 2012
url https://doi.org/10.3390/rs4071887
op_coverage agris
geographic Canada
geographic_facet Canada
genre La Grande River
James Bay
genre_facet La Grande River
James Bay
op_source Remote Sensing; Volume 4; Issue 7; Pages: 1887-1912
op_relation https://dx.doi.org/10.3390/rs4071887
op_rights https://creativecommons.org/licenses/by/3.0/
op_doi https://doi.org/10.3390/rs4071887
container_title Remote Sensing
container_volume 4
container_issue 7
container_start_page 1887
op_container_end_page 1912
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