{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T23:28:32Z","timestamp":1774222112790,"version":"3.50.1"},"reference-count":91,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T00:00:00Z","timestamp":1612742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000202","name":"U.S. Fish and Wildlife Service","doi-asserted-by":"publisher","award":["F18AC00039"],"award-info":[{"award-number":["F18AC00039"]}],"id":[{"id":"10.13039\/100000202","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Wetland managers, citizens and government leaders are observing rapid changes in coastal wetlands and associated habitats around the Great Lakes Basin due to human activity and climate variability. SAR and optical satellite sensors offer cost effective management tools that can be used to monitor wetlands over time, covering large areas like the Great Lakes and providing information to those making management and policy decisions. In this paper we describe ongoing efforts to monitor dynamic changes in wetland vegetation, surface water extent, and water level change. Included are assessments of simulated Radarsat Constellation Mission data to determine feasibility of continued monitoring into the future. Results show that integration of data from multiple sensors is most effective for monitoring coastal wetlands in the Great Lakes region. While products developed using methods described in this article provide valuable management tools, more effort is needed to reach the goal of establishing a dynamic, near-real-time, remote sensing-based monitoring program for the basin.<\/jats:p>","DOI":"10.3390\/rs13040599","type":"journal-article","created":{"date-parts":[[2021,2,10]],"date-time":"2021-02-10T04:33:46Z","timestamp":1612931626000},"page":"599","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Multi-Source EO for Dynamic Wetland Mapping and Monitoring in the Great Lakes Basin"],"prefix":"10.3390","volume":"13","author":[{"given":"Michael J.","family":"Battaglia","sequence":"first","affiliation":[{"name":"Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI 48105, USA"}]},{"given":"Sarah","family":"Banks","sequence":"additional","affiliation":[{"name":"Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada"}]},{"given":"Amir","family":"Behnamian","sequence":"additional","affiliation":[{"name":"Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7127-279X","authenticated-orcid":false,"given":"Laura","family":"Bourgeau-Chavez","sequence":"additional","affiliation":[{"name":"Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI 48105, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8439-362X","authenticated-orcid":false,"given":"Brian","family":"Brisco","sequence":"additional","affiliation":[{"name":"Natural Resources Canada, Ottawa, ON K1S 5K2, Canada"}]},{"given":"Jennifer","family":"Corcoran","sequence":"additional","affiliation":[{"name":"Minnesota Department of Natural Resources, St. Paul, MN 55155, USA"}]},{"given":"Zhaohua","family":"Chen","sequence":"additional","affiliation":[{"name":"Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada"}]},{"given":"Brian","family":"Huberty","sequence":"additional","affiliation":[{"name":"SharedGEO, St. Paul, MN 55104, USA"}]},{"given":"James","family":"Klassen","sequence":"additional","affiliation":[{"name":"SharedGEO, St. Paul, MN 55104, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5846-9416","authenticated-orcid":false,"given":"Joseph","family":"Knight","sequence":"additional","affiliation":[{"name":"Department of Forest Resources, University of Minnesota, St. Paul, MN 55108, USA"}]},{"given":"Paul","family":"Morin","sequence":"additional","affiliation":[{"name":"Polar Geospatial Center, University of Minnesota, St. Paul, MN 55108, USA"}]},{"given":"Kevin","family":"Murnaghan","sequence":"additional","affiliation":[{"name":"Natural Resources Canada, Ottawa, ON K1S 5K2, Canada"}]},{"given":"Keith","family":"Pelletier","sequence":"additional","affiliation":[{"name":"Department of Forest Resources, University of Minnesota, St. Paul, MN 55108, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9720-5349","authenticated-orcid":false,"given":"Lori","family":"White","sequence":"additional","affiliation":[{"name":"Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,8]]},"reference":[{"key":"ref_1","unstructured":"Maynard, L., and Wilcox, D.A. (2021, January 18). Coastal Wetlands. State of the Lakes Ecosystem Conference Background Paper. Available online: https:\/\/greatlakesresilience.org\/sites\/default\/files\/library_reference_1997_SOLEC_CoastalWetlandsoftheGreatLakes.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/S0380-1330(05)70294-X","article-title":"Hydrogeomorphic classification for Great Lakes coastal wetlands","volume":"31","author":"Albert","year":"2005","journal-title":"J. Great Lakes Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1016\/S0380-1330(92)71327-6","article-title":"The Ecology of Invertebrates in Great Lakes Coastal Wetlands: Current Knowledge and Research Needs","volume":"18","author":"Krieger","year":"1992","journal-title":"J. Great Lakes Res."},{"key":"ref_4","unstructured":"Dahl, T.E. (1990). Wetlands: Losses in the United States, U.S. Fish and Wildlife Service. [1st ed.]."},{"key":"ref_5","unstructured":"(2020, April 18). Great Lakes Restoration Initiative. Great Lakes Restoration Initiative Action Plan III, Available online: https:\/\/www.epa.gov\/sites\/production\/files\/2019-10\/documents\/glri-action-plan-3-201910-30pp.pdf."},{"key":"ref_6","unstructured":"(2020, April 18). Great Lakes Protection Initiative, Available online: https:\/\/www.canada.ca\/en\/environment-climate-change\/services\/greatlakes-protection\/funding\/2018-2019.html."},{"key":"ref_7","unstructured":"(2020, April 18). Great Lakes Water Quality Protocol of 2012 (GLWQA). Available online: https:\/\/binational.net\/glwqa-aqegl\/."},{"key":"ref_8","unstructured":"Ingram, J., Holmes, K., Grabas, G., Watton, P., Potter, B., Gomer, T., and Stow, N. (2004). Development of a Coastal Wetlands Database for the Great Lakes Canadian Shoreline, United States Environmental Protection Agency. Wetlands2-EPA-03 Final Report to the Great Lakes Commission."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jglr.2018.10.012","article-title":"Recent water level changes across Earth\u2019s largest lake system and implications for future variability","volume":"45","author":"Gronewold","year":"2019","journal-title":"J. Great Lakes Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1007\/s10584-013-0840-2","article-title":"Coasts, water levels, and climate change: A Great Lakes perspective","volume":"120","author":"Gronewold","year":"2013","journal-title":"Clim. Chang."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.ecolmodel.2014.01.010","article-title":"Emergence of nutrient-cycling feedbacks related to plant size and invasion success in a wetland community- ecosystem model","volume":"282","author":"Currie","year":"2014","journal-title":"Ecol. Model"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/BF00045196","article-title":"US Fish and Wildlife Service 1979 wetland classification: A review","volume":"118","author":"Cowardin","year":"1995","journal-title":"Vegetation"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"S1","DOI":"10.5589\/m07-051","article-title":"Towards a strategy to implement the Canadian Wetland Inventory using satellite remote sensing","volume":"33","author":"Fournier","year":"2007","journal-title":"Can. J. Remote Sens."},{"key":"ref_14","unstructured":"National Oceanic and Atmospheric Administration, Office for Coastal Management (2020, April 19). Coastal Change Analysis Program (C-CAP) Regional Land Cover, Available online: www.coast.noaa.gov\/htdata\/raster1\/landcover\/bulkdownload\/30m_lc\/."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"8655","DOI":"10.3390\/rs70708655","article-title":"Development of a bi-national Great Lakes coastal wetland and land use map using three-season PALSAR and Landsat imagery","volume":"7","author":"Endres","year":"2015","journal-title":"Remote Sens."},{"key":"ref_16","unstructured":"Bourgeau-Chavez, L.L., Kowalski, K.P., Battaglia, M.J., and Poley, A.F. (2019). Land cover map including wetlands and invasive Phragmites circa 2017. U.S. Geol. Surv. Data Release."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"White, L., Ryerson, R.A., Pasher, J., and Duffe, J. (2020). State of Science Assessment of Remote Sensing of Great Lakes Coastal Wetlands: Responding to an Operational Requirement. Remote Sens., 12.","DOI":"10.3390\/rs12183024"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1023\/A:1020908432489","article-title":"Satellite remote sensing of wetlands","volume":"10","author":"Ozesmi","year":"2002","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"27","DOI":"10.2528\/PIERB07110101","article-title":"An introduction to synthetic aperture radar (SAR)","volume":"2","author":"Chan","year":"2008","journal-title":"Prog. Electromagn. Res. B"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1080\/07038992.2015.1104634","article-title":"Change detection with compact polarimetric SAR for monitoring wetlands","volume":"41","author":"Dabboor","year":"2015","journal-title":"Can. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7615","DOI":"10.3390\/rs70607615","article-title":"A collection of SAR methodologies for monitoring wetlands","volume":"7","author":"White","year":"2015","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1080\/07038992.2017.1342206","article-title":"Object-based classification of wetlands in Newfoundland and Labrador using multi-temporal PolSAR data","volume":"43","author":"Mahdavi","year":"2017","journal-title":"Can. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"679","DOI":"10.5589\/m02-064","article-title":"Classification of wetland habitat and vegetation communities using multi-temporal IKONOS imagery in southern Saskatchewan","volume":"28","author":"Dechka","year":"2002","journal-title":"Can. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1109\/JSTARS.2019.2909437","article-title":"Comparison of Compact and Fully Polarimetric SAR for Multitemporal Wetland Monitoring","volume":"12","author":"Dabboor","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Mahdianpari, M., Granger, J.E., Mohammadimanesh, F., Salehi, B., Brisco, B., Homayouni, S., Gill, E., Huberty, B., and Lang, M. (2020). Meta-Analysis of Wetland Classification Using Remote Sensing: A Systematic Review of a 40-Year Trend in North America. Remote Sens., 12.","DOI":"10.3390\/rs12111882"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"328","DOI":"10.5589\/m13-041","article-title":"Object-based classification of Worldview-2 imagery for mapping invasive common reed, Phragmites australis","volume":"39","author":"Lantz","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4698","DOI":"10.1080\/01431161.2014.919685","article-title":"Mapping freshwater marsh species distributions using WorldView-2 high-resolution multispectral satellite imagery","volume":"35","author":"Carle","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"White, L., Millard, K., Banks, S., Richardson, M., Pasher, J., and Duffe, J. (2017). Moving to the RADARSAT constellation mission: Comparing synthesized compact polarimetry and dual polarimetry data with fully polarimetric RADARSAT-2 data for image classification of peatlands. Remote Sens., 9.","DOI":"10.3390\/rs9060573"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"13528","DOI":"10.3390\/rs71013528","article-title":"Assessing the potential to operationalize shoreline sensitivity mapping: Classifying multiple Wide Fine Quadrature Polarized RADARSAT-2 and Landsat 5 scenes with a single Random Forest model","volume":"7","author":"Banks","year":"2015","journal-title":"Remote Sens."},{"key":"ref_30","unstructured":"Stocker, T.F., Qin, D., Plattner, G.K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, B., and Midgley, B.M. (2013). Climate Change 2013: The Physical Science Basis, IPCC."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s10661-005-9087-3","article-title":"Modelling wetland bird response to water level changes in the Lake Ontario\u2014St. Lawrence River hydrosystem","volume":"113","author":"Desgranges","year":"2006","journal-title":"Environ. Monit. Assess."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"5698","DOI":"10.1002\/2014WR015595","article-title":"Global-scale assessment of groundwater depletion and related groundwater abstractions: Combining hydrological modeling with information from well observations and GRACE satellites","volume":"50","author":"Doll","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1007\/s11160-007-9059-5","article-title":"Potential impacts of global climate change on freshwater fisheries","volume":"17","author":"Ficke","year":"2007","journal-title":"Rev. Fish Biol. Fish"},{"key":"ref_34","first-page":"135","article-title":"Technical Note: A semi-automated tool for surface water mapping with RADARSAT-1","volume":"40","author":"Brisco","year":"2009","journal-title":"Can. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.pce.2010.12.009","article-title":"Towards an automated SAR-based flood monitoring system: Lessons learned from two case studies","volume":"36","author":"Matgen","year":"2011","journal-title":"Phys. Chem. Earth"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1080\/01431161.2015.1009653","article-title":"An automatic method for mapping inland surface waterbodies with Radarsat-2 imagery","volume":"36","author":"Li","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Bolanos, S., Stiff, D., Brisco, B., and Pietroniro, A. (2016). Technical Note: Operational Surface Water Detection and Monitoring Using Radarsat 2. Remote Sens., 8.","DOI":"10.3390\/rs8040285"},{"key":"ref_38","first-page":"135","article-title":"Research Note: RADARSAT-2 Beam Mode Selection for Surface Water and Flooded Vegetation Mapping","volume":"40","author":"White","year":"2014","journal-title":"Can. J. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"S298","DOI":"10.5589\/m10-062","article-title":"Compact polarimetry overview and applications assessment","volume":"36","author":"Charbonneau","year":"2010","journal-title":"Can. J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Behnamian, A., Banks, S., White, L., Brisco, B., Millard, K., Pasher, J., Chen, Z., Duffe, J., Bourgeau-Chavez, L., and Battaglia, M. (2017). Semi-Automated Surface Water Detection with Synthetic Aperture Radar Data: A Wetland Case Study. Remote Sens., 9.","DOI":"10.3390\/rs9121209"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","article-title":"SLIC Superpixels Compared to State-of-the-art Superpixel Methods","volume":"34","author":"Achanta","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.1109\/JPROC.2009.2017107","article-title":"A characterization of shannon entropy and bhattacharyya measure of contrast in polarimetric and interferometric SAR image","volume":"97","author":"Morio","year":"2009","journal-title":"Proc. IEEE"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1080\/07038992.2020.1726736","article-title":"Exploring Polarimetric Phase of Microwave Backscatter from Typha Wetlands","volume":"46","author":"Atwood","year":"2020","journal-title":"Can. J. Remote Sens."},{"key":"ref_44","unstructured":"Environment and Climate Change Canada (2018). Canadian Climate Normals 1981\u20132010, Environment and Climate Change Canada."},{"key":"ref_45","unstructured":"Ontario Ministry of Natural Resources and Forestry (2018). Ontario Regulation 230\/08, Species at Risk in Ontario List, OMNRF."},{"key":"ref_46","unstructured":"(2021, January 21). Prince Edward County Official Plan Natural Environment Addendum. Available online: https:\/\/www.thecounty.ca\/wp-content\/uploads\/2020\/09\/Natural-Environment-Addendum-1.pdf."},{"key":"ref_47","unstructured":"Olthof, I. Personal communication."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1007\/s12237-013-9593-4","article-title":"The Runaway Weed: Costs and Failures of Phragmites australis Management in the USA","volume":"36","author":"Martin","year":"2013","journal-title":"Estuaries Coasts"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_50","first-page":"545","article-title":"Mapping boreal peatland ecosystem types from a fusion of multi-temporal radar and optical satellite imagery","volume":"559","author":"Endres","year":"2017","journal-title":"Can. J. For. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1007\/s13157-019-01134-1","article-title":"Mapping Mountain Peatlands and Wet Meadows Using Multi-Date, Multi-Sensor Remote Sensing in the Cordillera Blanca, Peru","volume":"39","author":"Chimner","year":"2019","journal-title":"Wetlands"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Spagnuolo, O.S., Jarvey, J.C., Battaglia, M.J., Laubach, Z.M., Miller, M.E., Holekamp, K.E., and Bourgeau-Chavez, L.L. (2020). Mapping Kenyan Grassland Heights Across Large Spatial Scales with Combined Optical and Radar Satellite Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12071086"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1109\/LGRS.2013.2254465","article-title":"An Object-Based Workflow to Extract Landforms at Multiple Scales from Two Distinct Data Types","volume":"10","author":"Eisank","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"063567","DOI":"10.1117\/1.JRS.6.063567","article-title":"High-Resolution Tree Canopy Mapping for New York City Using LIDAR and Object-Based Image Analysis","volume":"6","author":"MacFaden","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"439","DOI":"10.14358\/PERS.80.5.439","article-title":"Wetland Mapping in the Upper Midwest United States: An Object-Based Approach Integrating Lidar and Imagery Data","volume":"80","author":"Rampi","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.1002\/esp.3425","article-title":"Improvement of Streams Hydro-Geomorphological Assessment Using LiDAR DEMs","volume":"38","author":"Biron","year":"2013","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Banks, S., White, L., Behnamian, A., Chen, Z., Montpetit, B., Brisco, B., Pasher, J., and Duffe, J. (2019). Wetland Classification with Multi-Angle\/Temporal SAR Using Random Forests. Remote Sens., 11.","DOI":"10.3390\/rs11060670"},{"key":"ref_58","unstructured":"Lunetta, R.S., and Elvidge, C.D. (1999). Remote Sensing Change Detection, Taylor & Francis."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3898","DOI":"10.1016\/j.rse.2008.06.013","article-title":"Influence of incidence angle on detecting flooded forests using C-HH synthetic aperture radar data","volume":"112","author":"Lang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"5809","DOI":"10.1080\/01431160801958405","article-title":"Radar detection of wetland ecosystems: A review","volume":"29","author":"Henderson","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_61","unstructured":"Provincial Mapping Unit, Mapping and Information Resources Branch, Corporate Management and Information Division, Ontario Ministry of Natural Resources and Forestry (2017). SCOOP 2013 Vertical Accuracy Assessment, Queen\u2019s Printer for Ontario."},{"key":"ref_62","unstructured":"R Core Team (2013). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_63","first-page":"18","article-title":"Classification and Regression by Random Forest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Banks, S., Millard, K., Behnamian, A., White, L., Ullmann, T., Charbonneau, F., Chen, Z., Wang, H., Pasher, J., and Duffe, J. (2017). Contributions of Actual and Simulated Satellite SAR Data for Substrate Type Differentiation and Shoreline Mapping in the Canadian Arctic. Remote Sens., 9.","DOI":"10.3390\/rs9121206"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"627","DOI":"10.14358\/PERS.70.5.627","article-title":"Thematic map comparison","volume":"70","author":"Foody","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_66","unstructured":"(2018, July 01). SARDocker. Available online: https:\/\/mortcanty.github.io\/SARDocker\/."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.rse.2017.11.005","article-title":"Fisher linear discriminant analysis of coherency matrix for wetland classification using polsar imagery","volume":"206","author":"Mahdianpari","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_68","unstructured":"Wang, Y. (2017). Remote Sensing of Coastal Environments, CRC Press."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.isprsjprs.2017.04.019","article-title":"The surface extraction from TIN based search-space minimization (SETSM) algorithm","volume":"129","author":"Noh","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.isprsjprs.2016.03.012","article-title":"An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery","volume":"116","author":"Shean","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_71","unstructured":"Porter, C., Morin, P., Howat, I., Noh, M.-J., Bates, B., Peterman, K., Keesey, S., Schlenk, M., Gardiner, J., and Tomko, K. (2021, January 21). ArcticDEM. Harvard Dataverse, V1. Available online: https:\/\/www.pgc.umn.edu\/data\/arcticdem\/."},{"key":"ref_72","unstructured":"Bode, B., Butler, M., Dunning, T., Hoeer, T., Kramer, W., Gropp, W., and Wen-Mei, H. (2013). The Blue Waters super-system for super-science. Contemporary High Performance Computing: From Petascale toward Exascale, CRC Press."},{"key":"ref_73","unstructured":"(2020, April 22). Great Lakes Consortium for Petascale Computation. Available online: https:\/\/www.greatlakesconsortium.org\/bluewaters.html."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"111750","DOI":"10.1016\/j.rse.2020.111750","article-title":"Characterizing marsh wetlands in the Great Lakes Basin with C-band InSAR observations","volume":"242","author":"Chen","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"2436","DOI":"10.1016\/j.rse.2010.05.019","article-title":"Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR)","volume":"114","author":"Hong","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","article-title":"A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms","volume":"40","author":"Berardino","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1109\/36.673674","article-title":"A novel phase unwrapping method based on network programming","volume":"36","author":"Costantini","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"DeVries, B., Huang, C., Lang, M.W., Jones, J.W., Huang, W., Creed, I.F., and Carroll, M.L. (2017). Automated Quantification of Surface Water Inundation in Wetlands Using Optical Satellite Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9080807"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Jones, J.W. (2019). Improved Automated Detection of Subpixel-Scale Inundation\u2014Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests. Remote Sens., 11.","DOI":"10.3390\/rs11040374"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2019.04.015","article-title":"Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine","volume":"228","author":"Wu","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1109\/36.406675","article-title":"Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radar","volume":"33","author":"Hess","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"4120","DOI":"10.1016\/j.rse.2007.08.026","article-title":"Assessment of C-band synthetic aperture radar data for mapping and monitoring Coastal Plain forested wetlands in the Mid-Atlantic Region, USA","volume":"112","author":"Lang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"2167","DOI":"10.1109\/TGRS.2008.917271","article-title":"Radarsat-1 and ERS InSAR analysis over southeastern coastal Louisiana: Implications for mapping water-level changes beneath swamp forests","volume":"46","author":"Lu","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Brisco, B., Homayouni, S., Gill, E., DeLancey, E.R., and Bourgeau-Chavez, L. (2020). Big Data for a Big Country: The First Generation of Canadian Wetland Inventory Map at a Spatial Resolution of 10-m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform. Can. J. Remote Sens., 1\u201319.","DOI":"10.1080\/07038992.2019.1711366"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.isprsjprs.2017.05.010","article-title":"Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery","volume":"130","author":"Mahdianpari","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Adeli, S., Salehi, B., Mahdianpari, M., Quackenbush, L.J., Brisco, B., Tamiminia, H., and Shaw, S. (2020). Wetland Monitoring Using SAR Data: A Meta-Analysis and Comprehensive Review. Remote Sens., 12.","DOI":"10.3390\/rs12142190"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"6380","DOI":"10.3390\/rs70506380","article-title":"Object-Based Image Analysis in Wetland Research: A Review","volume":"7","author":"Dronova","year":"2015","journal-title":"Remote Sens."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1080\/15481603.2017.1419602","article-title":"Remote sensing for wetland classification: A comprehensive review","volume":"55","author":"Mahdavi","year":"2018","journal-title":"GISci. Remote Sens."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1016\/j.rse.2007.06.008","article-title":"Space-based detection of wetlands\u2019 surface water level changes from L band SAR interferometry","volume":"112","author":"Wdowinski","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.rse.2017.06.009","article-title":"Characterizing hydrologic changes of the Great Dismal Swamp using SAR\/InSAR","volume":"198","author":"Kim","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Cao, N., Lee, H., Jung, H.C., and Yu, H. (2018). Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry. Remote Sens., 10.","DOI":"10.3390\/rs10060966"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/4\/599\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:21:13Z","timestamp":1760160073000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/4\/599"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,8]]},"references-count":91,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2021,2]]}},"alternative-id":["rs13040599"],"URL":"https:\/\/doi.org\/10.3390\/rs13040599","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,8]]}}}