Monitoring the spatial extent of coastal wetlands using ERS-1 SAR data

Rao, B. R. M.; Dwivedi, R. S.; Kushwaha, S. P. S.; Bhattacharya, S. D.; Anand, Jatin; Dasgupta, Swarvanu

doi:10.1080/014311699211903

Cited by 58 publications

(25 citation statements)

References 2 publications

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“…Because of persistent cloud cover in the tropical and subtropical regions, radar imagery is an appropriate option compared with optical remotely sensed data. Radar data deliver information that is useful for characterizing the cover extent of mangrove surfaces [146], structural parameters [9,[81][82][83]85,87,102,147,148], flooding boundaries [84], health status [88,149], deforestation status [150], and the amount of total biomass [81][82][83]85]. Studies were performed at different locations in various countries based on different radar data (Mexico: RADARSAT-1 SAR, [149] Several investigations were carried out to examine and describe the effects and relationships among mangrove canopy, stand structures, and the backscattering response of a SAR system, exemplified by the NASA/JPL airborne SAR (AIRSAR) system at different frequencies (C-, L-, P-band) and polarization modes (HH, VV, HV).…”

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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“…Several researchers have evaluated the utility of SAR for wetland mapping using single and multi-date single channel SAR data [16][17][18], and others have evaluated polarimetric SAR [19][20][21][22][23]. The horizontal send and horizontal receive (HH) polarization of SAR systems have long been known to improve distinction of swamp from other wetland classes and uplands [9,10,19,24,25] due to an enhanced double bounce effect from the water surface to the tree trunks and back to the sensor (or vice versa).…”

Section: Introductionmentioning

confidence: 99%

Development of a Bi-National Great Lakes Coastal Wetland and Land Use Map Using Three-Season PALSAR and Landsat Imagery

et al. 2015

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Methods using extensive field data and three-season Landsat TM and PALSAR imagery were developed to map wetland type and identify potential wetland stressors (i.e., adjacent land use) for the United States and Canadian Laurentian coastal Great Lakes. The mapped area included the coastline to 10 km inland to capture the region hydrologically connected to the Great Lakes. Maps were developed in cooperation with the overarching Great Lakes Consortium plan to provide a comprehensive regional baseline map suitable for coastal wetland assessment and management by agencies at the local, tribal, state, and federal levels. The goal was to provide not only land use and land cover (LULC) baseline data at moderate spatial resolution (20-30 m), but a repeatable methodology to monitor change into the future. The prime focus was on mapping wetland ecosystem types, such as emergent wetland and forested wetland, as well as to delineate wetland monocultures (Typha, OPEN ACCESSRemote Sens. 2015, 7 8656Phragmites, Schoenoplectus) and differentiate peatlands (fens and bogs) from other wetland types. The overall accuracy for the coastal Great Lakes map of all five lake basins was 94%, with a range of 86% to 96% by individual lake basin (Huron, Ontario, Michigan, Erie and Superior).

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“…Increasingly, remotely sensed imagery and related techniques have been used to support this work. Studies have focused on delineating the extent of wetland areas (Baghdadi et al 2001;Dwivedi et al 1999;Rao et al 1999), classifying wetland vegetation (Harvey and Hill 2001;Johnston and Barson 1993;Ringrose et al 2003) and monitoring ecological processes such as vegetation change (Haack 1996;Munyati 2000;Shuman and Ambrose 2003) and environmental flows (Shaikh et al 2001). Remote sensing has also been used to monitor how different forms of land and resource use have affected wetlands (Chopra et al 2001;Sajeev and Subramanian 2003).…”

Section: Remote Sensing Of Marshy Wetlandsmentioning

confidence: 98%

Mapping the annual area burned in the wetlands of the Okavango panhandle using a hierarchical classification approach

Cassidy

2007

Wetlands Ecol Manage

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This paper documents the methodology developed to identify burned areas accurately, and to quantify the spatial extent of the areas burned, in the wetlands of Botswana's Okavango panhandle in 2001. Physical identification of burned areas in marshy wetlands is extremely difficult. Burned areas are short-lived, limiting opportunities for ground-based measurement, which is often further hampered by extreme inaccessibility, and the unpredictable nature of the location and timing of burning. Given these challenges, satellite imagery has the potential to provide an excellent alternative for such analyses. However, burned areas can be spectrally confused with non-vegetated wetland areas such as open water and muddy flats, particularly when relying predominantly on the near-infrared band. This study addresses these constraints by using a hierarchical classification of Landsat 7 ETM+ imagery to remove wet and well-vegetated areas prior to burned-area identification, and by using the thermal band data to improve the separation between wet and burned areas. These techniques resulted in good designation of burned areas, a reduction in the misclassification of unburned areas, and a refinement of the spatial distribution of areas burned in 2001. The approach should prove useful to practitioners seeking to manage fire in wetlands.

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Monitoring the spatial extent of coastal wetlands using ERS-1 SAR data

Cited by 58 publications

References 2 publications

Remote Sensing of Mangrove Ecosystems: A Review

Remote Sensing of Mangrove Ecosystems: A Review

Development of a Bi-National Great Lakes Coastal Wetland and Land Use Map Using Three-Season PALSAR and Landsat Imagery

Mapping the annual area burned in the wetlands of the Okavango panhandle using a hierarchical classification approach

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