Abstract
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Zinat Ara Noor, Sheikh Mohammed Rabiul Alam, A. B. M. Kamal Pasha, Mohammad Shawkat Hossain
Abstract
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Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review
10.1007/s11273-009-9169-z · 2010
Supervised multi-regional segmentation machine learning architecture for digital twin applications in coastal regions
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A rule-based classification method for mapping saltmarsh land-cover in south-eastern Bangladesh from Landsat-8 OLI
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Scoping studies: towards a methodological framework
10.1080/1364557032000119616 · 2005
Random forest in remote sensing: a review of applications and future directions
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Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing
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Digital twin development towards integration into blue economy: a bibliometric analysis
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Corrigendum to “A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States”
10.1016/j.isprsjprs.2020.05.005 · 2020
A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States
crossref
Confidence 100%
ror
Confidence 99%
ror
Confidence 99%
openalex
Confidence 95%
datacite
Confidence 0%
10.1016/j.isprsjprs.2018.03.019 · 2018
Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation
10.1016/j.rse.2014.04.003 · 2014
Global hotspots of salt marsh change and carbon emissions
10.1038/s41586-022-05355-z · 2022
Aboveground biomass of salt-marsh vegetation in coastal wetlands: sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network
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Tracking annual dynamics of carbon storage of salt marsh plants in the Yellow River Delta National Nature Reserve of China based on Sentinel-2 imagery during 2017-2022
2024
Global carbon sequestration in tidal, saline wetland soils
10.1029/2002gb001917 · 2003
Unresolved referenced work
Kept as external metadata until matched
Enhancing salt marshes monitoring: estimating biomass with drone-derived habitat-specific models
2024
Mapping coastal wetland biomass from high resolution unmanned aerial vehicle imagery
10.3390/rs11050540 · 2019
The role of coastal plant communities for climate change mitigation and adaptation
10.1038/nclimate1970 · 2013
Unresolved referenced work
Kept as external metadata until matched
Numerical models of salt marsh evolution: ecological, geomorphic, and climatic factors
10.1029/2011rg000359 · 2012
Application of remote sensing methods for monitoring extent, condition and blue carbon storage in salt marshes
2024
Google Earth Engine: planetary-scale geospatial analysis for everyone
10.1016/j.rse.2017.06.031 · 2017
Radar detection of wetland ecosystems: a review
10.1080/01431160801958405 · 2008
Accuracy assessment and correction of a LiDAR-derived salt marsh digital elevation model
10.1016/j.rse.2012.01.018 · 2012
Accuracy and precision of tidal wetland soil carbon mapping in the conterminous United States
10.1038/s41598-018-26948-7 · 2018
Species-based mapping of carbon stocks in salt marsh: Tianjin coastal zone as a case study
2023
Multisensor data fusion: a review of the state-of-the-art
10.1016/j.inffus.2011.08.001 · 2013
Deep learning of high-resolution unmanned aerial vehicle imagery for classifying halophyte species: a comparative study for small patches and mixed vegetation
10.3390/rs15112723 · 2023
Response of salt-marsh carbon accumulation to climate change
10.1038/nature11440 · 2012
Potential uses of TerraSAR-X for mapping herbaceous halophytes over salt marsh and tidal flats
10.1016/j.ecss.2012.10.003 · 2012
Salt marsh carbon stock estimation using deep learning with Sentinel-1 SAR of the Yangtze River estuary, China
2024
Exploring the concept of digital twins of wetlands for supporting ecosystem monitoring and management
10.1080/20964471.2025.2480446 · 2026
The future of blue carbon science
10.1038/s41467-019-11693-w · 2019
Remote sensing for wetland classification: a comprehensive review
10.1080/15481603.2017.1419602 · 2018
A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2
10.1890/110004 · 2011
Relationship of salt marsh vegetation zonation to spatial patterns in soil moisture, salinity, and topography
10.1007/s10021-010-9385-7 · 2010
Support vector machines in remote sensing: a review
10.1016/j.isprsjprs.2010.11.001 · 2011
InSAR-based mapping of tidal inundation extent and amplitude in Louisiana coastal wetlands
10.3390/rs8050393 · 2016
Review and evaluation of deep learning architectures for efficient land cover mapping with UAS hyper-spatial imagery: a case study over a wetland
10.3390/rs12060959 · 2020
Guidance for conducting systematic scoping reviews
10.1097/xeb.0000000000000050 · 2015
PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation
10.7326/m18-0850 · doi-reference
Blue carbon mapping using temporally optimized satellite remote sensing imagery: a regional study of Northeast US salt marshes
10.1029/2024jg008254 · doi-reference
Future response of global coastal wetlands to sea-level rise
10.1038/s41586-018-0476-5 · doi-reference
Use of LiDAR to study changes associated with Spartina invasion in San Francisco Bay marshes
10.1016/j.rse.2005.10.012 · doi-reference
Multisensor image fusion in remote sensing: concepts, methods and applications
10.1080/014311698215748 · doi-reference
A review of remote sensing approaches for monitoring blue carbon ecosystems: mangroves, seagrasses and salt marshes during 2010-2018
10.3390/s19081933 · doi-reference
Guidance for conducting systematic scoping reviews
10.1097/xeb.0000000000000050 · doi-reference
Review and evaluation of deep learning architectures for efficient land cover mapping with UAS hyper-spatial imagery: a case study over a wetland
10.3390/rs12060959 · doi-reference
InSAR-based mapping of tidal inundation extent and amplitude in Louisiana coastal wetlands
10.3390/rs8050393 · doi-reference
Support vector machines in remote sensing: a review
10.1016/j.isprsjprs.2010.11.001 · doi-reference
Relationship of salt marsh vegetation zonation to spatial patterns in soil moisture, salinity, and topography
10.1007/s10021-010-9385-7 · doi-reference
A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2
10.1890/110004 · doi-reference
Remote sensing for wetland classification: a comprehensive review
10.1080/15481603.2017.1419602 · doi-reference
The future of blue carbon science
10.1038/s41467-019-11693-w · doi-reference
Exploring the concept of digital twins of wetlands for supporting ecosystem monitoring and management
10.1080/20964471.2025.2480446 · doi-reference
Potential uses of TerraSAR-X for mapping herbaceous halophytes over salt marsh and tidal flats
10.1016/j.ecss.2012.10.003 · doi-reference
Response of salt-marsh carbon accumulation to climate change
10.1038/nature11440 · doi-reference
Deep learning of high-resolution unmanned aerial vehicle imagery for classifying halophyte species: a comparative study for small patches and mixed vegetation
10.3390/rs15112723 · doi-reference
Multisensor data fusion: a review of the state-of-the-art
10.1016/j.inffus.2011.08.001 · doi-reference
Accuracy and precision of tidal wetland soil carbon mapping in the conterminous United States
10.1038/s41598-018-26948-7 · doi-reference
Accuracy assessment and correction of a LiDAR-derived salt marsh digital elevation model
10.1016/j.rse.2012.01.018 · doi-reference
Radar detection of wetland ecosystems: a review
10.1080/01431160801958405 · doi-reference
Google Earth Engine: planetary-scale geospatial analysis for everyone
10.1016/j.rse.2017.06.031 · doi-reference
Numerical models of salt marsh evolution: ecological, geomorphic, and climatic factors
10.1029/2011rg000359 · doi-reference
The role of coastal plant communities for climate change mitigation and adaptation
10.1038/nclimate1970 · doi-reference
Mapping coastal wetland biomass from high resolution unmanned aerial vehicle imagery
10.3390/rs11050540 · doi-reference
Global carbon sequestration in tidal, saline wetland soils
10.1029/2002gb001917 · doi-reference
Aboveground biomass of salt-marsh vegetation in coastal wetlands: sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network
10.1016/j.rse.2021.112885 · doi-reference
Global hotspots of salt marsh change and carbon emissions
10.1038/s41586-022-05355-z · doi-reference
Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation
10.1016/j.rse.2014.04.003 · doi-reference
A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States
10.1016/j.isprsjprs.2018.03.019 · doi-reference
Corrigendum to “A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States”
10.1016/j.isprsjprs.2020.05.005 · doi-reference
Digital twin development towards integration into blue economy: a bibliometric analysis
10.1016/j.oceaneng.2024.119781 · doi-reference
Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing
10.1016/j.rse.2006.06.006 · doi-reference
Random forest in remote sensing: a review of applications and future directions
10.1016/j.isprsjprs.2016.01.011 · doi-reference
Scoping studies: towards a methodological framework
10.1080/1364557032000119616 · doi-reference
A rule-based classification method for mapping saltmarsh land-cover in south-eastern Bangladesh from Landsat-8 OLI
10.1080/07038992.2020.1789852 · doi-reference
Supervised multi-regional segmentation machine learning architecture for digital twin applications in coastal regions
10.1007/s11852-024-01038-1 · doi-reference
Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review
10.1007/s11273-009-9169-z · doi-reference