Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach

Sundarban mangrove is the largest continuous mangrove forest in the world and is the habitat of an incredible amount of biodiversity. Biodiversity loss and degradation of this highly ecologically productive mangrove forest due to climate change will have a tremendous impact on the livelihood of the...

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Autores principales:	Purnendu Sardar, Sukha Ranjan Samadder
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Sundarban Mangrove Remote sensing Land cover change Multi-layer perceptron Landscape statistics Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/a2943527c2ff40169b36995204aeee2c
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id	oai:doaj.org-article:a2943527c2ff40169b36995204aeee2c
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spelling	oai:doaj.org-article:a2943527c2ff40169b36995204aeee2c2021-12-01T04:29:03ZUnderstanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach1470-160X10.1016/j.ecolind.2020.106914https://doaj.org/article/a2943527c2ff40169b36995204aeee2c2021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20308530https://doaj.org/toc/1470-160XSundarban mangrove is the largest continuous mangrove forest in the world and is the habitat of an incredible amount of biodiversity. Biodiversity loss and degradation of this highly ecologically productive mangrove forest due to climate change will have a tremendous impact on the livelihood of the people living in the deltaic region. The present study was aimed to find out the dynamics of change in different land cover for the greater Sundarban region. The multi-temporal Landsat images were used to understand the dynamics in three decades from 1998 to 2018. The analysis revealed that Sundarban mangrove forest changed very insignificantly. The change between 1998 and 2008 was approximately 1.2%, i.e. around 26.2 km2, and the change between the year 2008 and 2018 was approximately 1.27%, which consists of 28 km2. However, the dynamics of open mangrove forest and dense mangrove forest were found very high. The human habitat and aquaculture were found as the most rapidly expanding land-use type in this landscape. Area under human habitat has increased approximately 80%, i.e. nearly 654 km2 between 1998 and 2018; area under aquaculture has increased approximately 116% (i.e. around 231 km2) between 1998 and 2008. The MLP-Markov Chain based modelling of land-use has shown an overwhelming increase in human habitat in near future. However, being situated in the close vicinity of dense human population of the city Kolkata, the mangrove habitat remained intact, which is largely due to great amount of conservation efforts that have been exercised by the Govt. and the local forest department. The landscape statistical analysis for understanding the ecological dynamics of every land cover types showed that in 2018, the human habitat became second dominant category in this study area. The aquaculture practice for high economic value has pushed down the native agricultural practice in the region.Purnendu SardarSukha Ranjan SamadderElsevierarticleSundarbanMangroveRemote sensingLand cover changeMulti-layer perceptronLandscape statisticsEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 106914- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Sundarban Mangrove Remote sensing Land cover change Multi-layer perceptron Landscape statistics Ecology QH540-549.5
spellingShingle	Sundarban Mangrove Remote sensing Land cover change Multi-layer perceptron Landscape statistics Ecology QH540-549.5 Purnendu Sardar Sukha Ranjan Samadder Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach
description	Sundarban mangrove is the largest continuous mangrove forest in the world and is the habitat of an incredible amount of biodiversity. Biodiversity loss and degradation of this highly ecologically productive mangrove forest due to climate change will have a tremendous impact on the livelihood of the people living in the deltaic region. The present study was aimed to find out the dynamics of change in different land cover for the greater Sundarban region. The multi-temporal Landsat images were used to understand the dynamics in three decades from 1998 to 2018. The analysis revealed that Sundarban mangrove forest changed very insignificantly. The change between 1998 and 2008 was approximately 1.2%, i.e. around 26.2 km2, and the change between the year 2008 and 2018 was approximately 1.27%, which consists of 28 km2. However, the dynamics of open mangrove forest and dense mangrove forest were found very high. The human habitat and aquaculture were found as the most rapidly expanding land-use type in this landscape. Area under human habitat has increased approximately 80%, i.e. nearly 654 km2 between 1998 and 2018; area under aquaculture has increased approximately 116% (i.e. around 231 km2) between 1998 and 2008. The MLP-Markov Chain based modelling of land-use has shown an overwhelming increase in human habitat in near future. However, being situated in the close vicinity of dense human population of the city Kolkata, the mangrove habitat remained intact, which is largely due to great amount of conservation efforts that have been exercised by the Govt. and the local forest department. The landscape statistical analysis for understanding the ecological dynamics of every land cover types showed that in 2018, the human habitat became second dominant category in this study area. The aquaculture practice for high economic value has pushed down the native agricultural practice in the region.
format	article
author	Purnendu Sardar Sukha Ranjan Samadder
author_facet	Purnendu Sardar Sukha Ranjan Samadder
author_sort	Purnendu Sardar
title	Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach
title_short	Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach
title_full	Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach
title_fullStr	Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach
title_full_unstemmed	Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach
title_sort	understanding the dynamics of landscape of greater sundarban area using multi-layer perceptron markov chain and landscape statistics approach
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/a2943527c2ff40169b36995204aeee2c
work_keys_str_mv	AT purnendusardar understandingthedynamicsoflandscapeofgreatersundarbanareausingmultilayerperceptronmarkovchainandlandscapestatisticsapproach AT sukharanjansamadder understandingthedynamicsoflandscapeofgreatersundarbanareausingmultilayerperceptronmarkovchainandlandscapestatisticsapproach
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Understanding the dynamics of landscape of greater Sundarban area using multi-layer perceptron Markov chain and landscape statistics approach

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