Land cover change across 45 years in the world’s largest mangrove forest (Sundarbans): the contribution of remote sensing in forest monitoring

Hossain, Kanan Akbar; Masiero, Mauro; Pirotti, Francesco

doi:10.1080/22797254.2022.2097450

Cited by 26 publications

(11 citation statements)

References 73 publications

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“…Conversely, the red, orange, and pink areas correspond to different built-up structures, aquacultural farms, and other land uses. One can note the substantial reduction in forest area, particularly in the northern part of the Sundarbans, which has been replaced by various human developments, including buildings, roads, and infrastructures, as well as shrimp farms, which is completely aligned with other studies (Hossain et al, 2022;Faruque et al, 2022;Halder et al, 2021;Khan et al, 2021;Abdullah et al, 2019;Quader et al, 2017).…”

Section: Lulc Changes In the Sundarbanssupporting

confidence: 66%

Harnessing Complexity: Integrating Remote Sensing and Fuzzy Expert System for Evaluating Land Use Land Cover Changes and Identifying Mangrove Forest Vulnerability in Bangladesh

Islam,

Rafi,

Jannat

et al. 2024

Preprint

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In this study, we analyze Landsat images to examine the alterations in land cover within the Sundarbans and its surrounding regions in Bangladesh, spanning twenty-one years from 2000 to 2021. Furthermore, we develop a vulnerability map considering the combined effect of eight socioeconomic, geophysical, and climatic factors. The results show that a significant portion of the mangrove forest has been transformed into aquaculture practices because of the expansion of high-value shrimp cultivation. A decrease in forest areas and the expansion of aquaculture zones suggest a livelihood shift among the local population over time. This transition has adversely affected human activities within the ecosystem and the biodiversity of mangrove forests. Consequently, it is imperative to implement suitable measures to enhance the state of mangrove forests and safeguard their biodiversity. The vulnerability analysis shows that the highly vulnerable, moderately vulnerable, and low vulnerable areas cover 35.66%, 26.86%, and 19.42%, respectively. The vulnerability maps generated in this research could serve as a valuable resource for coastal planners seeking to ensure the sustainable stewardship of these coastal mangrove forests. These results offer a detailed understanding of coastal mangrove LULC patterns and vulnerability status, which will be useful for policymakers and resource managers to incorporate into coastal land use and environmental management practices urgently.

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Section: Lulc Changes In the Sundarbanssupporting

confidence: 66%

Harnessing Complexity: Integrating Remote Sensing and Fuzzy Expert System for Evaluating Land Use Land Cover Changes and Identifying Mangrove Forest Vulnerability in Bangladesh

Islam,

Rafi,

Jannat

et al. 2024

Preprint

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“…[23]. For example, Bangladesh and Indian governments recently made an agreement to build a coal-fed thermal power plant in Rampal, 14 km north of the Sundarbans [40]. Many environmental activists reported that the proposed location of the Rampal Power Station would violate provisions of the Ramsar Convention and UNESCO rules for World Heritage Site, threatening the biodiversity and ecological values of the Sundarbans [26].…”

Section: Socio-ecological Aspectsmentioning

confidence: 99%

Estimating Economic and Livelihood Values of the World’s Largest Mangrove Forest (Sundarbans): A Meta-Analysis

Kanan,

Masiero,

Pirotti

2024

Forests

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We explored the state of the art economic and livelihood valuation of ecosystem services (ES) in the Sundarbans mangroves, including a comparative analysis between the Bangladesh and Indian parts of the region. We identified 145 values from 26 studies to estimate the Sundarbans’ economic and livelihood values. The number of ES valuation studies of the Sundarbans is scant, and it has gradually increased over time, focusing mainly on the estimation of provisioning ES (66.2%), followed by regulating and maintenance (25.5%), and cultural (8.3%) ES. However, recently, attention has been paid to estimation, regulating and maintenance, and cultural ES. The number of studies on ES was higher for the Bangladesh (73%) part of the Sundarbans than the Indian (27%) one. The estimated economic values of the Sundarbans’ provisioning, regulating and maintenance, and cultural ES were US $ 713.30 ha−1 yr−1, US $ 2584.46 ha−1 yr−1, and US $ 151.88 ha−1 yr−1, respectively. Except for cultural ES, the identified values for the other two ES categories were about 1.5 to 2.5 times higher for the Bangladesh Sundarbans compared to the Indian ones. The results of the meta-regression model showed that the estimated economic and livelihood values of ES are affected by the associated variables (e.g., type of ES, valuation methods, study area, population, and GDP). Our study also identified some remarkable gaps and limitations in the economic and livelihood valuation of the ES of the Sundarbans, highlighting the need for further research to find out the values of all ES to help with policy decision-making.

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“…In light of climate change, the report highlighted the need for adaption techniques and policies to help the agricultural sector. Akbar Hossain et al (2022) studied the spatio-temporal dynamics of vegetation cover change in the Sundarbans mangrove forest using remote sensing and GIS. They discovered that during the last few decades, the Sundarbans' vegetation cover has dramatically diminished, mostly as a result of cyclonic storms and human activities like shrimp farming and wood harvesting.…”

Section: Literature Reviewmentioning

confidence: 99%

Vegetation Cover Change Analysis during 1989-2020 of Coastal Barguna District, Bangladesh Using Remote Sensing and GIS Technology

Islam

Yeasmin

Karmaker

et al. 2023

IRSPSD International

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This paper represents an advanced assessment of a satellite imagery-based vegetation transition detection method for Bangladesh's southern district of Barguna. Bangladesh has been identified as the most vulnerable country to the effects of climate change due to deteriorating vegetative cover and urbanization pushing forces. This paper aims to use GIS and remote sensing techniques to estimate vegetation change and determine the conversion pattern in the coastal district of Barguna, Bangladesh, from 1989 to 2020. The major methodology used in this research is NDVI differencing and supervised image classification to validate the conversion over time. With a combination of satellite imagery bands, NDVI uses multi-spectral remote sensing techniques to discover vegetation index, water, empty spaces, and forests. To categorize the canopy into distinct kinds, we use NDVI threshold values of 0, 0.1, 0.15, and 0.2. Our findings reveal significant geographical variations in bare regions, sparse, moderate, and thick vegetation types. We discovered that over the last 31 years, a total of 412.90 km 2 (49.25 percent) of land has been deforested, with the transition rate being particularly high in dense vegetation. This research of vegetation cover change can help predict the recurrence of natural disasters, give humanitarian assistance, and enable innovative protection tactics.

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Land cover change across 45 years in the world’s largest mangrove forest (Sundarbans): the contribution of remote sensing in forest monitoring

Cited by 26 publications

References 73 publications

Harnessing Complexity: Integrating Remote Sensing and Fuzzy Expert System for Evaluating Land Use Land Cover Changes and Identifying Mangrove Forest Vulnerability in Bangladesh

Harnessing Complexity: Integrating Remote Sensing and Fuzzy Expert System for Evaluating Land Use Land Cover Changes and Identifying Mangrove Forest Vulnerability in Bangladesh

Estimating Economic and Livelihood Values of the World’s Largest Mangrove Forest (Sundarbans): A Meta-Analysis

Vegetation Cover Change Analysis during 1989-2020 of Coastal Barguna District, Bangladesh Using Remote Sensing and GIS Technology

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