Mapping and monitoring of mangrove along the Odisha coast based on remote sensing and GIS techniques

Roy, Santanu Sen; Mahapatra, Manik; Chakraborty, Abhishekh

doi:10.1007/s40808-018-0529-7

Cited by 19 publications

(15 citation statements)

References 24 publications

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“…After the first period characterized by mangroves decline (i.e., 1988-2001), we found an 18.84 % increase of mangrove area between 2001 and 2019. A similar trend was recorded for mangroves by Gevana et al (2015) in Philippines, Roy et al (2019) in India and Islam et al (2020) in Bangladesh. According to these authors, such an increase is attributable to continuous restoration activities of degraded mangroves.…”

Section: Spatio-temporal Dynamics Of Mangroves and Future Scenariosupporting

confidence: 81%

“…This study used remote sensing techniques, and GIS in combination with Markovian chain model on satellite images to map spatio-temporal dynamics of mangrove forests and predict their future trends in Benin. Several other studies have used these modelling techniques to assess land use and land cover changes and predict their future courses (e.g., Padonou et al, 2017) including in mangrove ecosystems (Roy et al, 2019;Islam et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Classic remote sensing technics applied by Roy et al (2019) was considered. This technic consisted into five main steps: (i) acquisition of freely available satellite images, (ii) images classification, (iii) field data verification, (iv) images validation, and (v) images interpretation.…”

Section: Remote Sensed Data and Sourcementioning

confidence: 99%

“…Remote sensing techniques and GIS are widely used approaches for mapping, monitoring and detecting changes in forest cover (Mayaux et al, 2003), including in mangroves (e.g., Roy et al, 2019;Islam et al, 2020). Furthermore, knowledge on land use/land cover transition has been used as inputs in Markovian chain model to predict the future expansion and land-use/land-cover change in many instances (e.g., Padonou et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Mapping spatio-temporal changes in mangroves cover and projection in 2050 of their future state in Benin

et al. 2022

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Mangroves are precious ecosystems that provide vital socio-economic, environmental and cultural benefits to humanity. However, they are declining alarmingly due to human activities and natural hazards. Assessment of their spatio-temporal dynamics is essential to monitor these ecosystems and guide their management to ensure sustainability. We assessed the spatio-temporal dynamics of mangroves and predicted their future trends using remote sensing techniques and Markovian chain analysis. Landsat images TM/ETM+ (for 1988, 2001 and 2019) were obtained, processed, classified and analyzed using remote sensing techniques and GIS. The changes observed during these periods (1988–2001, 2001-2019 and 1988–2019) were used to predict future trends up to 2050, using Markovian chain analysis. The results showed that the mangrove area studied, which occupied 5205.24 ha in 1988, declined by 62.07% between 1988 and 2001 but increased by 18.84% from 2001 to 2019. This increase is attributed to strengthened mangrove restoration efforts. The mangroves had mainly been converted into grassland (52.35% in 1988-2001 and 7.31% in 2001-2019) and other vegetation types (17.57% in 1988-2001 and 27.05% in 2001-2019). Their decline was most severe in the municipalities of Abomey-Calavi and Ouidah, which therefore require greater conservation efforts. Our projection based on Markovian chain analysis suggests that these mangroves will continue to decline, but slowly. This study provides essential information to guide future mangrove conservation action in the study area.

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Section: Spatio-temporal Dynamics Of Mangroves and Future Scenariosupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Section: Remote Sensed Data and Sourcementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping spatio-temporal changes in mangroves cover and projection in 2050 of their future state in Benin

et al. 2022

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“…Landscape planning decisions can be made more easily and design solutions can be brought to fore more effectively using change information as indicator for understanding landscape-level processes such as urbanization, deforestation, agricultural encroachment, etc. Due to this critical importance, many authors utilized remote sensing and GIS for monitoring change processes all around the world ( Jones et al, 2013;Kayhko et al, 2011;Misra et al, 2015;Roy, Mahapatra, & Chakraborty, 2019;Zhang, Thapa, Ross, & Gann, 2016).…”

Section: Change Analysismentioning

confidence: 99%

Quantitative Approach for Complementary Analysis of a Touristic Coastal Landscape: The Case of Erdemli (Mersin), Turkey.

Alphan¹

2020

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Understanding Potential Drivers of Mangrove Loss in Bhitarkanika and Mahanadi Delta, India, to Enhance Effective Restoration and Conservation Efforts

Dhyani

Panda

Kadaverugu

et al. 2022

Science for Sustainable Societies

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Mapping and monitoring of mangrove along the Odisha coast based on remote sensing and GIS techniques

Cited by 19 publications

References 24 publications

Mapping spatio-temporal changes in mangroves cover and projection in 2050 of their future state in Benin

Mapping spatio-temporal changes in mangroves cover and projection in 2050 of their future state in Benin

Quantitative Approach for Complementary Analysis of a Touristic Coastal Landscape: The Case of Erdemli (Mersin), Turkey.

Understanding Potential Drivers of Mangrove Loss in Bhitarkanika and Mahanadi Delta, India, to Enhance Effective Restoration and Conservation Efforts

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