A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories

Recently, there has been renewed interest in the ecosystem services of mangroves such as carbon sequestration or coastal protection, and consequently, the development of tools providing an effective and automatic monitoring of the dynamics of mangrove land coverage including rehabilitated or naturally regenerated forest stand is increasingly demanded. Satellite-based time series analysis in coastal areas can be limited by atmospheric contaminations, such as haze, and clouds and their shadows. Here, we present an “automatic regrowth monitoring algorithm” (ARMA) using the Google Earth Engine (GEE), based on Landsat interannual median composites from 1987 to 2019 with 30 m spatial resolution. The species and structural diversity were assessed using transect plot inventories. The Landsat-based normalized difference infrared index (NDII) and information obtained from plot inventories were used to assess the characteristics of the natural and rehabilitated mangrove forests. The ARMA identified the starting year of the rehabilitation project using the satellite data, the required stability period after the rehabilitation, and the stand age in the year 2019. The information obtained from the field survey data were linked to the results obtained using the ARMA. After 28 years, the rehabilitated mangroves at the study site consist of monocultures of Rhizophoraceae, while the undisturbed and naturally regenerated mangroves had greater species diversity. Nevertheless, the rehabilitated mangroves were found to reach the height of the adjacent natural mangroves. The period required to reach a stable NDII value (similar to natural stands) after rehabilitation ranged from 7 to 13 years. The careful assessment of the NDII upward trend was crucial for the performance of the ARMA. The application presented here shows, however, that the system can be used to evaluate both small- and large-scale rehabilitation projects. The results of this study provide valuable baseline information for the site assessed and for its comparison with other rehabilitated mangroves in Thailand. Due to the technical potential, we are convinced that the ARMA system is suited to investigate changes in mangrove coverage dynamics, in general, including gain (as presented here), but also mangrove losses, due to disturbances such as degradation or forest diebacks.

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Main Authors: Pimple, Uday, Simonetti, Dario, Hinks, Isabella, Oszwald, Johan, Berger, Uta, Pungkul, Sukan, Leadprathom, Kumron, Pravinvongvuthi, Tamanai, Maprasoap, Pasin, Gond, Valéry
Format: article biblioteca
Language:eng
Subjects:K01 - Foresterie - Considérations générales, U30 - Méthodes de recherche, mangrove, palétuvier, biodiversité, télédétection, inventaire forestier continu, reconstitution forestière, http://aims.fao.org/aos/agrovoc/c_4577, http://aims.fao.org/aos/agrovoc/c_16190, http://aims.fao.org/aos/agrovoc/c_33949, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_1374156575504, http://aims.fao.org/aos/agrovoc/c_13802, http://aims.fao.org/aos/agrovoc/c_7701,
Online Access:http://agritrop.cirad.fr/595247/
http://agritrop.cirad.fr/595247/1/595247.pdf
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id dig-cirad-fr-595247
record_format koha
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
mangrove
palétuvier
biodiversité
télédétection
inventaire forestier continu
reconstitution forestière
http://aims.fao.org/aos/agrovoc/c_4577
http://aims.fao.org/aos/agrovoc/c_16190
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1374156575504
http://aims.fao.org/aos/agrovoc/c_13802
http://aims.fao.org/aos/agrovoc/c_7701
K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
mangrove
palétuvier
biodiversité
télédétection
inventaire forestier continu
reconstitution forestière
http://aims.fao.org/aos/agrovoc/c_4577
http://aims.fao.org/aos/agrovoc/c_16190
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1374156575504
http://aims.fao.org/aos/agrovoc/c_13802
http://aims.fao.org/aos/agrovoc/c_7701
spellingShingle K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
mangrove
palétuvier
biodiversité
télédétection
inventaire forestier continu
reconstitution forestière
http://aims.fao.org/aos/agrovoc/c_4577
http://aims.fao.org/aos/agrovoc/c_16190
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1374156575504
http://aims.fao.org/aos/agrovoc/c_13802
http://aims.fao.org/aos/agrovoc/c_7701
K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
mangrove
palétuvier
biodiversité
télédétection
inventaire forestier continu
reconstitution forestière
http://aims.fao.org/aos/agrovoc/c_4577
http://aims.fao.org/aos/agrovoc/c_16190
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1374156575504
http://aims.fao.org/aos/agrovoc/c_13802
http://aims.fao.org/aos/agrovoc/c_7701
Pimple, Uday
Simonetti, Dario
Hinks, Isabella
Oszwald, Johan
Berger, Uta
Pungkul, Sukan
Leadprathom, Kumron
Pravinvongvuthi, Tamanai
Maprasoap, Pasin
Gond, Valéry
A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories
description Recently, there has been renewed interest in the ecosystem services of mangroves such as carbon sequestration or coastal protection, and consequently, the development of tools providing an effective and automatic monitoring of the dynamics of mangrove land coverage including rehabilitated or naturally regenerated forest stand is increasingly demanded. Satellite-based time series analysis in coastal areas can be limited by atmospheric contaminations, such as haze, and clouds and their shadows. Here, we present an “automatic regrowth monitoring algorithm” (ARMA) using the Google Earth Engine (GEE), based on Landsat interannual median composites from 1987 to 2019 with 30 m spatial resolution. The species and structural diversity were assessed using transect plot inventories. The Landsat-based normalized difference infrared index (NDII) and information obtained from plot inventories were used to assess the characteristics of the natural and rehabilitated mangrove forests. The ARMA identified the starting year of the rehabilitation project using the satellite data, the required stability period after the rehabilitation, and the stand age in the year 2019. The information obtained from the field survey data were linked to the results obtained using the ARMA. After 28 years, the rehabilitated mangroves at the study site consist of monocultures of Rhizophoraceae, while the undisturbed and naturally regenerated mangroves had greater species diversity. Nevertheless, the rehabilitated mangroves were found to reach the height of the adjacent natural mangroves. The period required to reach a stable NDII value (similar to natural stands) after rehabilitation ranged from 7 to 13 years. The careful assessment of the NDII upward trend was crucial for the performance of the ARMA. The application presented here shows, however, that the system can be used to evaluate both small- and large-scale rehabilitation projects. The results of this study provide valuable baseline information for the site assessed and for its comparison with other rehabilitated mangroves in Thailand. Due to the technical potential, we are convinced that the ARMA system is suited to investigate changes in mangrove coverage dynamics, in general, including gain (as presented here), but also mangrove losses, due to disturbances such as degradation or forest diebacks.
format article
topic_facet K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
mangrove
palétuvier
biodiversité
télédétection
inventaire forestier continu
reconstitution forestière
http://aims.fao.org/aos/agrovoc/c_4577
http://aims.fao.org/aos/agrovoc/c_16190
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1374156575504
http://aims.fao.org/aos/agrovoc/c_13802
http://aims.fao.org/aos/agrovoc/c_7701
author Pimple, Uday
Simonetti, Dario
Hinks, Isabella
Oszwald, Johan
Berger, Uta
Pungkul, Sukan
Leadprathom, Kumron
Pravinvongvuthi, Tamanai
Maprasoap, Pasin
Gond, Valéry
author_facet Pimple, Uday
Simonetti, Dario
Hinks, Isabella
Oszwald, Johan
Berger, Uta
Pungkul, Sukan
Leadprathom, Kumron
Pravinvongvuthi, Tamanai
Maprasoap, Pasin
Gond, Valéry
author_sort Pimple, Uday
title A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories
title_short A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories
title_full A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories
title_fullStr A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories
title_full_unstemmed A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories
title_sort history of the rehabilitation of mangroves and an assessment of their diversity and structure using landsat annual composites (1987–2019) and transect plot inventories
url http://agritrop.cirad.fr/595247/
http://agritrop.cirad.fr/595247/1/595247.pdf
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spelling dig-cirad-fr-5952472024-01-29T02:39:30Z http://agritrop.cirad.fr/595247/ http://agritrop.cirad.fr/595247/ A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories. Pimple Uday, Simonetti Dario, Hinks Isabella, Oszwald Johan, Berger Uta, Pungkul Sukan, Leadprathom Kumron, Pravinvongvuthi Tamanai, Maprasoap Pasin, Gond Valéry. 2020. Forest Ecology and Management, 462:118007, 17 p.https://doi.org/10.1016/j.foreco.2020.118007 <https://doi.org/10.1016/j.foreco.2020.118007> A history of the rehabilitation of mangroves and an assessment of their diversity and structure using Landsat annual composites (1987–2019) and transect plot inventories Pimple, Uday Simonetti, Dario Hinks, Isabella Oszwald, Johan Berger, Uta Pungkul, Sukan Leadprathom, Kumron Pravinvongvuthi, Tamanai Maprasoap, Pasin Gond, Valéry eng 2020 Forest Ecology and Management K01 - Foresterie - Considérations générales U30 - Méthodes de recherche mangrove palétuvier biodiversité télédétection inventaire forestier continu reconstitution forestière http://aims.fao.org/aos/agrovoc/c_4577 http://aims.fao.org/aos/agrovoc/c_16190 http://aims.fao.org/aos/agrovoc/c_33949 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_1374156575504 http://aims.fao.org/aos/agrovoc/c_13802 Thaïlande http://aims.fao.org/aos/agrovoc/c_7701 Recently, there has been renewed interest in the ecosystem services of mangroves such as carbon sequestration or coastal protection, and consequently, the development of tools providing an effective and automatic monitoring of the dynamics of mangrove land coverage including rehabilitated or naturally regenerated forest stand is increasingly demanded. Satellite-based time series analysis in coastal areas can be limited by atmospheric contaminations, such as haze, and clouds and their shadows. Here, we present an “automatic regrowth monitoring algorithm” (ARMA) using the Google Earth Engine (GEE), based on Landsat interannual median composites from 1987 to 2019 with 30 m spatial resolution. The species and structural diversity were assessed using transect plot inventories. The Landsat-based normalized difference infrared index (NDII) and information obtained from plot inventories were used to assess the characteristics of the natural and rehabilitated mangrove forests. The ARMA identified the starting year of the rehabilitation project using the satellite data, the required stability period after the rehabilitation, and the stand age in the year 2019. The information obtained from the field survey data were linked to the results obtained using the ARMA. After 28 years, the rehabilitated mangroves at the study site consist of monocultures of Rhizophoraceae, while the undisturbed and naturally regenerated mangroves had greater species diversity. Nevertheless, the rehabilitated mangroves were found to reach the height of the adjacent natural mangroves. The period required to reach a stable NDII value (similar to natural stands) after rehabilitation ranged from 7 to 13 years. The careful assessment of the NDII upward trend was crucial for the performance of the ARMA. The application presented here shows, however, that the system can be used to evaluate both small- and large-scale rehabilitation projects. The results of this study provide valuable baseline information for the site assessed and for its comparison with other rehabilitated mangroves in Thailand. Due to the technical potential, we are convinced that the ARMA system is suited to investigate changes in mangrove coverage dynamics, in general, including gain (as presented here), but also mangrove losses, due to disturbances such as degradation or forest diebacks. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/595247/1/595247.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.foreco.2020.118007 10.1016/j.foreco.2020.118007 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.foreco.2020.118007 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.foreco.2020.118007