MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m3/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests.

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Main Authors: Le Maire, Guerric, Marsden, Claire, Nouvellon, Yann, Grinand, Clovis, Hakamada, Rodrigo, Stape, Jose Luiz, Laclau, Jean-Paul
Format: article biblioteca
Language:eng
Published: Elsevier
Subjects:U30 - Méthodes de recherche, K10 - Production forestière, F62 - Physiologie végétale - Croissance et développement, Eucalyptus, plantations, biomasse, indice de surface foliaire, plantation forestière, zone tropicale, modèle mathématique, télédétection, http://aims.fao.org/aos/agrovoc/c_2683, http://aims.fao.org/aos/agrovoc/c_5990, http://aims.fao.org/aos/agrovoc/c_926, http://aims.fao.org/aos/agrovoc/c_35196, http://aims.fao.org/aos/agrovoc/c_3048, http://aims.fao.org/aos/agrovoc/c_7979, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_6789,
Online Access:http://agritrop.cirad.fr/560868/
http://agritrop.cirad.fr/560868/1/document_560868.pdf
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spelling dig-cirad-fr-5608682024-12-18T14:17:19Z http://agritrop.cirad.fr/560868/ http://agritrop.cirad.fr/560868/ MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass. Le Maire Guerric, Marsden Claire, Nouvellon Yann, Grinand Clovis, Hakamada Rodrigo, Stape Jose Luiz, Laclau Jean-Paul. 2011. Remote Sensing of Environment, 115 (10) : 2613-2625.https://doi.org/10.1016/j.rse.2011.05.017 <https://doi.org/10.1016/j.rse.2011.05.017> MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass Le Maire, Guerric Marsden, Claire Nouvellon, Yann Grinand, Clovis Hakamada, Rodrigo Stape, Jose Luiz Laclau, Jean-Paul eng 2011 Elsevier Remote Sensing of Environment U30 - Méthodes de recherche K10 - Production forestière F62 - Physiologie végétale - Croissance et développement Eucalyptus plantations biomasse indice de surface foliaire plantation forestière zone tropicale modèle mathématique télédétection http://aims.fao.org/aos/agrovoc/c_2683 http://aims.fao.org/aos/agrovoc/c_5990 http://aims.fao.org/aos/agrovoc/c_926 http://aims.fao.org/aos/agrovoc/c_35196 http://aims.fao.org/aos/agrovoc/c_3048 http://aims.fao.org/aos/agrovoc/c_7979 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6498 Sao Paulo http://aims.fao.org/aos/agrovoc/c_6789 The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m3/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/560868/1/document_560868.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.rse.2011.05.017 10.1016/j.rse.2011.05.017 http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=212195 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2011.05.017 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.rse.2011.05.017
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 U30 - Méthodes de recherche
K10 - Production forestière
F62 - Physiologie végétale - Croissance et développement
Eucalyptus
plantations
biomasse
indice de surface foliaire
plantation forestière
zone tropicale
modèle mathématique
télédétection
http://aims.fao.org/aos/agrovoc/c_2683
http://aims.fao.org/aos/agrovoc/c_5990
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_3048
http://aims.fao.org/aos/agrovoc/c_7979
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_6789
U30 - Méthodes de recherche
K10 - Production forestière
F62 - Physiologie végétale - Croissance et développement
Eucalyptus
plantations
biomasse
indice de surface foliaire
plantation forestière
zone tropicale
modèle mathématique
télédétection
http://aims.fao.org/aos/agrovoc/c_2683
http://aims.fao.org/aos/agrovoc/c_5990
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_3048
http://aims.fao.org/aos/agrovoc/c_7979
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_6789
spellingShingle U30 - Méthodes de recherche
K10 - Production forestière
F62 - Physiologie végétale - Croissance et développement
Eucalyptus
plantations
biomasse
indice de surface foliaire
plantation forestière
zone tropicale
modèle mathématique
télédétection
http://aims.fao.org/aos/agrovoc/c_2683
http://aims.fao.org/aos/agrovoc/c_5990
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_3048
http://aims.fao.org/aos/agrovoc/c_7979
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_6789
U30 - Méthodes de recherche
K10 - Production forestière
F62 - Physiologie végétale - Croissance et développement
Eucalyptus
plantations
biomasse
indice de surface foliaire
plantation forestière
zone tropicale
modèle mathématique
télédétection
http://aims.fao.org/aos/agrovoc/c_2683
http://aims.fao.org/aos/agrovoc/c_5990
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_3048
http://aims.fao.org/aos/agrovoc/c_7979
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_6789
Le Maire, Guerric
Marsden, Claire
Nouvellon, Yann
Grinand, Clovis
Hakamada, Rodrigo
Stape, Jose Luiz
Laclau, Jean-Paul
MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass
description The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m3/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests.
format article
topic_facet U30 - Méthodes de recherche
K10 - Production forestière
F62 - Physiologie végétale - Croissance et développement
Eucalyptus
plantations
biomasse
indice de surface foliaire
plantation forestière
zone tropicale
modèle mathématique
télédétection
http://aims.fao.org/aos/agrovoc/c_2683
http://aims.fao.org/aos/agrovoc/c_5990
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_3048
http://aims.fao.org/aos/agrovoc/c_7979
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_6789
author Le Maire, Guerric
Marsden, Claire
Nouvellon, Yann
Grinand, Clovis
Hakamada, Rodrigo
Stape, Jose Luiz
Laclau, Jean-Paul
author_facet Le Maire, Guerric
Marsden, Claire
Nouvellon, Yann
Grinand, Clovis
Hakamada, Rodrigo
Stape, Jose Luiz
Laclau, Jean-Paul
author_sort Le Maire, Guerric
title MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass
title_short MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass
title_full MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass
title_fullStr MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass
title_full_unstemmed MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass
title_sort modis ndvi time-series allow the monitoring of eucalyptus plantation biomass
publisher Elsevier
url http://agritrop.cirad.fr/560868/
http://agritrop.cirad.fr/560868/1/document_560868.pdf
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