Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar

Reducing carbon emissions from deforestation and degradation (REDD) requires detailed insight into how the forest biomass is measured and distributed. Studies so far have estimated forest biomass stocks using rough assumptions and unreliable data. High-resolution data and robust methods are required to capture the spatial variability of forest biomass with sufficient precision. Here we aim to improve on previous approaches by using radar satellite ALOS PALSAR (25-m resolution) and optical Landsat-derived tree cover (30-m resolution) observations to estimate forest biomass stocks in Madagascar, for the years 2007–2010. The radar signal and in situ biomass were highly correlated (R2 = 0.71) and the root mean square error was 30% (for biomass ranging from 0 to 500 t/ha). Using our map at 25-m resolution for the entire island of Madagascar, we estimated the total above-ground forest carbon for the four years 2007, 2008, 2009 and 2010 to be 1.1173 ± 0.0304, 1.1029 ± 0.0303, 1.0916 ± 0.0301 and 1.0773 ± 0.0298 PgC, respectively. Carbon stocks were found to have decreased constantly over this period due to anthropogenic deforestation and likely also to climate change. The results are expected to serve as a more accurate benchmark for monitoring progress on REDD and to provide strong supports for current and future spaceborne missions such as ALOS-2, SAOCOM and BIOMASS.

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Main Authors: Ho Tong Minh, Dinh, Ndikumana, Emile, Vieilledent, Ghislain, McKey, Doyle B., Baghdadi, Nicolas
Format: article biblioteca
Language:eng
Subjects:K01 - Foresterie - Considérations générales, U30 - Méthodes de recherche, http://aims.fao.org/aos/agrovoc/c_4510,
Online Access:http://agritrop.cirad.fr/587923/
http://agritrop.cirad.fr/587923/7/1-s2.0-S0034425718302104-main.pdf
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spelling dig-cirad-fr-5879232021-11-09T09:50:46Z http://agritrop.cirad.fr/587923/ http://agritrop.cirad.fr/587923/ Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar. Ho Tong Minh Dinh, Ndikumana Emile, Vieilledent Ghislain, McKey Doyle B., Baghdadi Nicolas. 2018. Remote Sensing of Environment, 213 : 206-214.https://doi.org/10.1016/j.rse.2018.04.056 <https://doi.org/10.1016/j.rse.2018.04.056> Researchers Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar Ho Tong Minh, Dinh Ndikumana, Emile Vieilledent, Ghislain McKey, Doyle B. Baghdadi, Nicolas eng 2018 Remote Sensing of Environment K01 - Foresterie - Considérations générales U30 - Méthodes de recherche Madagascar http://aims.fao.org/aos/agrovoc/c_4510 Reducing carbon emissions from deforestation and degradation (REDD) requires detailed insight into how the forest biomass is measured and distributed. Studies so far have estimated forest biomass stocks using rough assumptions and unreliable data. High-resolution data and robust methods are required to capture the spatial variability of forest biomass with sufficient precision. Here we aim to improve on previous approaches by using radar satellite ALOS PALSAR (25-m resolution) and optical Landsat-derived tree cover (30-m resolution) observations to estimate forest biomass stocks in Madagascar, for the years 2007–2010. The radar signal and in situ biomass were highly correlated (R2 = 0.71) and the root mean square error was 30% (for biomass ranging from 0 to 500 t/ha). Using our map at 25-m resolution for the entire island of Madagascar, we estimated the total above-ground forest carbon for the four years 2007, 2008, 2009 and 2010 to be 1.1173 ± 0.0304, 1.1029 ± 0.0303, 1.0916 ± 0.0301 and 1.0773 ± 0.0298 PgC, respectively. Carbon stocks were found to have decreased constantly over this period due to anthropogenic deforestation and likely also to climate change. The results are expected to serve as a more accurate benchmark for monitoring progress on REDD and to provide strong supports for current and future spaceborne missions such as ALOS-2, SAOCOM and BIOMASS. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/587923/7/1-s2.0-S0034425718302104-main.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.rse.2018.04.056 10.1016/j.rse.2018.04.056 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2018.04.056 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.rse.2018.04.056
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
http://aims.fao.org/aos/agrovoc/c_4510
K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
http://aims.fao.org/aos/agrovoc/c_4510
spellingShingle K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
http://aims.fao.org/aos/agrovoc/c_4510
K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
http://aims.fao.org/aos/agrovoc/c_4510
Ho Tong Minh, Dinh
Ndikumana, Emile
Vieilledent, Ghislain
McKey, Doyle B.
Baghdadi, Nicolas
Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar
description Reducing carbon emissions from deforestation and degradation (REDD) requires detailed insight into how the forest biomass is measured and distributed. Studies so far have estimated forest biomass stocks using rough assumptions and unreliable data. High-resolution data and robust methods are required to capture the spatial variability of forest biomass with sufficient precision. Here we aim to improve on previous approaches by using radar satellite ALOS PALSAR (25-m resolution) and optical Landsat-derived tree cover (30-m resolution) observations to estimate forest biomass stocks in Madagascar, for the years 2007–2010. The radar signal and in situ biomass were highly correlated (R2 = 0.71) and the root mean square error was 30% (for biomass ranging from 0 to 500 t/ha). Using our map at 25-m resolution for the entire island of Madagascar, we estimated the total above-ground forest carbon for the four years 2007, 2008, 2009 and 2010 to be 1.1173 ± 0.0304, 1.1029 ± 0.0303, 1.0916 ± 0.0301 and 1.0773 ± 0.0298 PgC, respectively. Carbon stocks were found to have decreased constantly over this period due to anthropogenic deforestation and likely also to climate change. The results are expected to serve as a more accurate benchmark for monitoring progress on REDD and to provide strong supports for current and future spaceborne missions such as ALOS-2, SAOCOM and BIOMASS.
format article
topic_facet K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
http://aims.fao.org/aos/agrovoc/c_4510
author Ho Tong Minh, Dinh
Ndikumana, Emile
Vieilledent, Ghislain
McKey, Doyle B.
Baghdadi, Nicolas
author_facet Ho Tong Minh, Dinh
Ndikumana, Emile
Vieilledent, Ghislain
McKey, Doyle B.
Baghdadi, Nicolas
author_sort Ho Tong Minh, Dinh
title Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar
title_short Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar
title_full Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar
title_fullStr Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar
title_full_unstemmed Potential value of combining ALOS PALSAR and Landsat-derived tree cover data for forest biomass retrieval in Madagascar
title_sort potential value of combining alos palsar and landsat-derived tree cover data for forest biomass retrieval in madagascar
url http://agritrop.cirad.fr/587923/
http://agritrop.cirad.fr/587923/7/1-s2.0-S0034425718302104-main.pdf
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