Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine

Carbon stocks in forest ecosystems, when released as a result of forest degradation, contribute to greenhouse gas (GHG) emissions. To quantify and assess the rates of these changes, the Intergovernmental Panel on Climate Change (IPCC) recommends that the REDD+ mechanism use a combination of Earth ob...

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Main Authors: Arifou Kombate, Fousseni Folega, Wouyo Atakpama, Marra Dourma, Kperkouma Wala, Kalifa Goïta
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/11/11/1889
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author Arifou Kombate
Fousseni Folega
Wouyo Atakpama
Marra Dourma
Kperkouma Wala
Kalifa Goïta
author_facet Arifou Kombate
Fousseni Folega
Wouyo Atakpama
Marra Dourma
Kperkouma Wala
Kalifa Goïta
author_sort Arifou Kombate
collection DOAJ
description Carbon stocks in forest ecosystems, when released as a result of forest degradation, contribute to greenhouse gas (GHG) emissions. To quantify and assess the rates of these changes, the Intergovernmental Panel on Climate Change (IPCC) recommends that the REDD+ mechanism use a combination of Earth observational data and field inventories. To this end, our study characterized land-cover changes and forest-cover dynamics in Togo between 1985 and 2020, using the supervised classification of Landsat 5, 7, and 8 images on the Google Earth Engine platform with the Random Forest (RF) algorithm. Overall image classification accuracies for all target years ranged from 0.91 to 0.98, with Kappa coefficients ranging between 0.86 and 0.96. Analysis indicated that all land cover classes, which were identified at the beginning of the study period, have undergone changes at several levels, with a reduction in forest area from 49.9% of the national territory in 1985, to 23.8% in 2020. These losses of forest cover have mainly been to agriculture, savannahs, and urbanization. The annual change in forest cover was estimated at −2.11% per year, with annual deforestation at 422.15 km<sup>2</sup> per year, which corresponds to a contraction in forest cover of 0.74% per year over the 35-year period being considered. Ecological Zone IV (mountainous, with dense semi-deciduous forests) is the one region (of five) that has best conserved its forest area over this period. This study contributes to the mission of forestry and territorial administration in Togo by providing methods and historical data regarding land cover that would help to control the factors involved in forest area reductions, reinforcing the system of measurement, notification, and verification within the REDD+ framework, and ensuring better, long-lasting management of forest ecosystems.
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spelling doaj.art-5483924bb7414ae587a5950fd9f4fca42023-11-24T05:27:07ZengMDPI AGLand2073-445X2022-10-011111188910.3390/land11111889Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth EngineArifou Kombate0Fousseni Folega1Wouyo Atakpama2Marra Dourma3Kperkouma Wala4Kalifa Goïta5Centre d’Applications et de Recherches en Télédétection (CARTEL), Département de Géomatique Appliquée, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, CanadaGéomatique et Modélisation des Écosystèmes, Laboratoire de Botanique et Écologie Végétale (LBEV), Département de botanique, Faculté des sciences, Université de Lomé, 01 BP 1515 Lomé, TogoUnité de Recherche en Systématique et Conservation de la Biodiversité, Laboratoire de Botanique et Écologie Végétale (LBEV), Département de botanique, Faculté des sciences, Université de Lomé, 01 BP 1515 Lomé, TogoGéomatique et Modélisation des Écosystèmes, Laboratoire de Botanique et Écologie Végétale (LBEV), Département de botanique, Faculté des sciences, Université de Lomé, 01 BP 1515 Lomé, TogoGéomatique et Modélisation des Écosystèmes, Laboratoire de Botanique et Écologie Végétale (LBEV), Département de botanique, Faculté des sciences, Université de Lomé, 01 BP 1515 Lomé, TogoCentre d’Applications et de Recherches en Télédétection (CARTEL), Département de Géomatique Appliquée, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, CanadaCarbon stocks in forest ecosystems, when released as a result of forest degradation, contribute to greenhouse gas (GHG) emissions. To quantify and assess the rates of these changes, the Intergovernmental Panel on Climate Change (IPCC) recommends that the REDD+ mechanism use a combination of Earth observational data and field inventories. To this end, our study characterized land-cover changes and forest-cover dynamics in Togo between 1985 and 2020, using the supervised classification of Landsat 5, 7, and 8 images on the Google Earth Engine platform with the Random Forest (RF) algorithm. Overall image classification accuracies for all target years ranged from 0.91 to 0.98, with Kappa coefficients ranging between 0.86 and 0.96. Analysis indicated that all land cover classes, which were identified at the beginning of the study period, have undergone changes at several levels, with a reduction in forest area from 49.9% of the national territory in 1985, to 23.8% in 2020. These losses of forest cover have mainly been to agriculture, savannahs, and urbanization. The annual change in forest cover was estimated at −2.11% per year, with annual deforestation at 422.15 km<sup>2</sup> per year, which corresponds to a contraction in forest cover of 0.74% per year over the 35-year period being considered. Ecological Zone IV (mountainous, with dense semi-deciduous forests) is the one region (of five) that has best conserved its forest area over this period. This study contributes to the mission of forestry and territorial administration in Togo by providing methods and historical data regarding land cover that would help to control the factors involved in forest area reductions, reinforcing the system of measurement, notification, and verification within the REDD+ framework, and ensuring better, long-lasting management of forest ecosystems.https://www.mdpi.com/2073-445X/11/11/1889land-cover changeREDD+Google Earth Enginerandom forestlandsatTogo
spellingShingle Arifou Kombate
Fousseni Folega
Wouyo Atakpama
Marra Dourma
Kperkouma Wala
Kalifa Goïta
Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine
Land
land-cover change
REDD+
Google Earth Engine
random forest
landsat
Togo
title Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine
title_full Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine
title_fullStr Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine
title_full_unstemmed Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine
title_short Characterization of Land-Cover Changes and Forest-Cover Dynamics in Togo between 1985 and 2020 from Landsat Images Using Google Earth Engine
title_sort characterization of land cover changes and forest cover dynamics in togo between 1985 and 2020 from landsat images using google earth engine
topic land-cover change
REDD+
Google Earth Engine
random forest
landsat
Togo
url https://www.mdpi.com/2073-445X/11/11/1889
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