Mapping wetlands of the Sundaban Delta and it's environs using ERS-1 SAR data

Dwivedi, R. S.; Rao, B. R. M.; Bhattacharya, S. D.

doi:10.1080/014311699212227

Cited by 64 publications

(29 citation statements)

References 6 publications

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“…Further investigations using medium-resolution optical imagery in conjunction with radar (SAR) data were presented by Pasqualini et al [150], using Space Shuttle Imaging Radar SIR-C SAR data and SPOT XS and ERS-1 radar data for mapping mangroves in Madagascar; Dwivedi et al [151] applied ERS-1 SAR and IRS 1B LISS II data on the Sundarbans; Shanmugam et al [152] performed a sensor fusion between IRS-1D LISS III and ERS-2 SAR imagery in Tamil Nadu, India; and Souza Filho and Paradella [153,154] worked with RADARSAT-1 fine mode C-band HH and Landsat-5 TM data in the Brazilian Amazon region. Lucas et al [147] used the Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR), with L-band and HH polarization, and in conjunction with other remotely sensed data, such as Landsat and Shuttle Radar Topography Mission height data.…”

Section: Overview Of Mangrove-mapping Studies and Methods Based On Ramentioning

confidence: 99%

Remote Sensing of Mangrove Ecosystems: A Review

et al. 2011

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Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high-and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR) data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the OPEN ACCESSRemote Sens. 2011, 3 879 services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove ecosystem mapping, as well as the numerous methods and techniques used for data analyses, and to further discuss their potential and limitations.

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Section: Overview Of Mangrove-mapping Studies and Methods Based On Ramentioning

confidence: 99%

Remote Sensing of Mangrove Ecosystems: A Review

et al. 2011

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“…Whilst the number of studies is extremely limited, researchers have shown that space-borne SAR can be used in conjunction with optical data or as an alternative in the mapping of mangroves (Aschbacher et al, 1995;Dwivedi et al, 1999;Kushwaha et al, 2000;Simard et al, 2002). The main advantages of SAR are that it is not limited to daylight and, most importantly, it can penetrate cloud cover.…”

Section: Geo-spatial Monitoring and Analysismentioning

confidence: 99%

Ethnobiology, socio-economics and management of mangrove forests: A review

et al. 2008

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“…Remote sensing, on the other hand, is comparatively very effective in terms of cost, time and accuracy [7,31] and therefore is efficient in monitoring mangrove species dynamics because of its synoptic and repeated coverage and historical data [32]. For mapping and change detection purposes, a number of studies conducted in the Sundarbans have applied remote sensing tools (for example [15,[33][34][35][36][37][38]); however, most of the studies have kept their focus only on determining spatial change. Giri and co-authors [39] identified mangrove composition and their changes at the species level in the Sundarbans, but this was only for the Indian Territory.…”

Section: Introductionmentioning

confidence: 99%

Mapping Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans

Ghosh

Kumar

Roy

2016

Forests

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Abstract:The Sundarbans mangrove forest is an important resource for the people of the Ganges Delta. It plays an important role in the local as well as global ecosystem by absorbing carbon dioxide and other pollutants from air and water, offering protection to millions of people in the Ganges Delta against cyclone and water surges, stabilizing the shore line, trapping sediment and nutrients, purifying water, and providing services for human beings, such as fuel wood, medicine, food, and construction materials. However, this mangrove ecosystem is under threat, mainly due to climate change and anthropogenic factors. Anthropogenic and climate change-induced degradation, such as over-exploitation of timber and pollution, sea level rise, coastal erosion, increasing salinity, effects of increasing number of cyclones and higher levels of storm surges function as recurrent threats to mangroves in the Sundarbans. In this situation, regular and detailed information on mangrove species composition, their spatial distribution and the changes taking place over time is very important for a thorough understanding of mangrove biodiversity, and this information can also lead to the adoption of management practices designed for the maximum sustainable yield of the Sundarbans forest resources. We employed a maximum likelihood classifier technique to classify images recorded by the Landsat satellite series and used post classification comparison techniques to detect changes at the species level. The image classification resulted in overall accuracies of 72%, 83%, 79% and 89% for the images of 1977, 1989, 2000 and 2015, respectively. We identified five major mangrove species and detected changes over the 38-year (1977-2015) study period. During this period, both Heritiera fomes and Excoecaria agallocha decreased by 9.9%, while Ceriops decandra, Sonneratia apelatala, and Xylocarpus mekongensis increased by 12.9%, 380.4% and 57.3%, respectively.

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Mapping wetlands of the Sundaban Delta and it's environs using ERS-1 SAR data

Cited by 64 publications

References 6 publications

Remote Sensing of Mangrove Ecosystems: A Review

Remote Sensing of Mangrove Ecosystems: A Review

Ethnobiology, socio-economics and management of mangrove forests: A review

Mapping Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans

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