{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T01:53:37Z","timestamp":1776131617946,"version":"3.50.1"},"reference-count":94,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,20]],"date-time":"2021-08-20T00:00:00Z","timestamp":1629417600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100015233","name":"Minnesota Invasive Terrestrial Plants and Pests Center, University of Minnesota","doi-asserted-by":"publisher","award":["ML2018 Ch214 Art.4 Sec.2 Sub.06a E818ITP"],"award-info":[{"award-number":["ML2018 Ch214 Art.4 Sec.2 Sub.06a E818ITP"]}],"id":[{"id":"10.13039\/100015233","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Invasive plant species are an increasing worldwide threat both ecologically and financially. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for invasive Phragmites australis is particularly challenging due to limited accessibility in wetland environments. Unoccupied aircraft systems (UAS) are a popular choice for invasive species management due to their ability to survey challenging environments and their high spatial and temporal resolution. This study tested the utility of three-band (i.e., red, green, and blue; RGB) UAS imagery for mapping Phragmites in the St. Louis River Estuary in Minnesota, U.S.A. and Saginaw Bay in Michigan, U.S.A. Iterative object-based image analysis techniques were used to identify two classes, Phragmites and Not Phragmites. Additionally, the effectiveness of canopy height models (CHMs) created from two data types, UAS imagery and commercial satellite stereo retrievals, and the RADARSAT-2 horizontal-horizontal (HH) polarization were tested for Phragmites identification. The highest overall classification accuracy of 90% was achieved when pairing the UAS imagery with a UAS-derived CHM. Producer\u2019s accuracy for the Phragmites class ranged from 3 to 76%, and the user\u2019s accuracies were above 90%. The Not Phragmites class had user\u2019s and producer\u2019s accuracies above 88%. Inclusion of the RADARSAT-2 HH polarization caused a slight reduction in classification accuracy. Commercial satellite stereo retrievals increased commission errors due to decreased spatial resolution and vertical accuracy. The lowest classification accuracy was seen when using only the RGB UAS imagery. UAS are promising for Phragmites identification, but the imagery should be used in conjunction with a CHM.<\/jats:p>","DOI":"10.3390\/rs13163303","type":"journal-article","created":{"date-parts":[[2021,8,22]],"date-time":"2021-08-22T22:59:27Z","timestamp":1629673167000},"page":"3303","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Mapping Invasive Phragmites australis Using Unoccupied Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar"],"prefix":"10.3390","volume":"13","author":[{"given":"Connor J.","family":"Anderson","sequence":"first","affiliation":[{"name":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"}]},{"given":"Daniel","family":"Heins","sequence":"additional","affiliation":[{"name":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"}]},{"given":"Keith C.","family":"Pelletier","sequence":"additional","affiliation":[{"name":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"}]},{"given":"Julia L.","family":"Bohnen","sequence":"additional","affiliation":[{"name":"Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, 2003 Upper Buford Circle, St. Paul, MN 55108, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5846-9416","authenticated-orcid":false,"given":"Joseph F.","family":"Knight","sequence":"additional","affiliation":[{"name":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.ecolecon.2004.10.002","article-title":"Update on the environmental and economic costs associated with alien-invasive species in the United States","volume":"52","author":"Pimentel","year":"2005","journal-title":"Ecol. Econ."},{"key":"ref_2","unstructured":"Saltonstall, K., Burdick, D., Miller, S., and Smith, B. (2021, June 30). Native and Non-native Phragmites: Challenges in Identification, Research, and Management of the Common Reed. National Estuarine Research Reserve Technical Report Series, Available online: https:\/\/coast.noaa.gov\/data\/docs\/nerrs\/Research_TechSeries_Phrag_Final_2009.pdf."},{"key":"ref_3","unstructured":"Michigan Department of Agriculture and Rural Development (2021, June 30). Prohibited and Restricted Weeds, Available online: https:\/\/www.michigan.gov\/documents\/mdard\/Michigan_Prohibited_and_Restricted_Weeds_641413_7.pdf."},{"key":"ref_4","unstructured":"Minnesota Department of Agriculture (2021, June 30). Noxious Weed List. Available online: https:\/\/www.mda.state.mn.us\/sites\/default\/files\/docs\/2021-02\/2021NoxiousWeedListFactsheetV2.pdf."},{"key":"ref_5","first-page":"123","article-title":"The biology of Australian weeds. 12. Phragmites australis (Cav.) Trin. Ex Steud","volume":"49","author":"Hocking","year":"1983","journal-title":"J. Aust. Inst. Agric. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1007\/BF03161781","article-title":"Invasiveness in wetland plants in temperate North America","volume":"19","author":"Galatowitsch","year":"1999","journal-title":"Wetlands"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1007\/BF02823716","article-title":"Phragmites australis invasion and expansion in tidal interactions among salinity, sulfide, and hydrology","volume":"26","author":"Chambers","year":"2003","journal-title":"Estuaries"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"793","DOI":"10.2307\/1353112","article-title":"Does the common reed, Phragmites australis, affect essential fish habitat","volume":"22","author":"Weinstein","year":"1999","journal-title":"Estuaries"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2104","DOI":"10.1111\/gcb.13539","article-title":"An invasive wetland grass primes deep soil carbon pools","volume":"23","author":"Bernal","year":"2017","journal-title":"Glob. Chang. Biol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1672\/0277-5212(2002)022[0616:MGANRI]2.0.CO;2","article-title":"Microbial growth and nitrogen retention in litter of phragmites australis compared to typha angustifolia, wetlands","volume":"22","author":"Findlay","year":"2002","journal-title":"Wetlands"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1023\/A:1008432200133","article-title":"A comparison of Phragmites australis in freshwater and brackish marsh environments in North America","volume":"8","author":"Meyerson","year":"2000","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/S0304-3770(99)00055-8","article-title":"Expansion of Phragmites australis into tidal wetlands of North America","volume":"64","author":"Chambers","year":"1999","journal-title":"Aquat. Bot."},{"key":"ref_13","first-page":"285","article-title":"Phragmites australis (P. communis): Threats, management, and monitoring","volume":"14","author":"Marks","year":"1994","journal-title":"Source Nat. Areas J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1007\/s13157-010-0054-6","article-title":"Environmental conditions promoting non-native phragmites australis expansion in great lakes coastal wetlands","volume":"30","author":"Tulbure","year":"2010","journal-title":"Wetlands"},{"key":"ref_15","unstructured":"Center for Invasive Species and Ecosystem Health, University of Georgia (2019, September 01). Early Detection and Distribution Mapping System. Available online: https:\/\/www.eddmaps.org\/."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5676","DOI":"10.1080\/01431161.2018.1500072","article-title":"Very high resolution mapping of coral reef state using airborne bathymetric lidar surface-intensity and drone imagery","volume":"39","author":"Collin","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5472","DOI":"10.1080\/01431161.2018.1465616","article-title":"Multi-depth suspended sediment estimation using high-resolution remote-sensing UAV in Maumee River, Ohio","volume":"39","author":"Larson","year":"2018","journal-title":"Int. J. Remote. Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.isprsjprs.2017.03.011","article-title":"Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland","volume":"128","author":"Lu","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1370","DOI":"10.1016\/j.rse.2008.06.020","article-title":"Selecting and conserving lands for biodiversity: The role of remote sensing","volume":"113","author":"Wiens","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.biocon.2014.12.006","article-title":"Remote sensing change detection for ecological monitoring in United States protected areas","volume":"182","author":"Willis","year":"2015","journal-title":"Biol. Conserv."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"887","DOI":"10.3389\/fpls.2017.00887","article-title":"Timing is important: Unmanned aircraft vs. Satellite imagery in plant invasion monitoring","volume":"8","year":"2017","journal-title":"Front. Plant. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3609","DOI":"10.1080\/01431160701469099","article-title":"Mapping an inland wetland complex using hyperspectral imagery","volume":"29","author":"Jollineau","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"167","DOI":"10.5589\/m05-003","article-title":"Classification of Iowa wetlands using an airborne hyperspectral image: A comparison of the spectral angle mapper classifier and an object-oriented approach","volume":"31","author":"Harken","year":"2005","journal-title":"Can. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/S0034-4257(03)00096-8","article-title":"Mapping nonnative plants using hyperspectral imagery","volume":"86","author":"Underwood","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.rse.2006.11.002","article-title":"Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor","volume":"108","author":"Pengra","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.jglr.2012.11.001","article-title":"Mapping invasive Phragmites australis in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support","volume":"39","author":"Kowalski","year":"2013","journal-title":"J. Great Lakes Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.rse.2014.04.010","article-title":"Random forest classification of salt marsh vegetation habitats using quad-polarimetric airborne SAR, elevation and optical RS data","volume":"149","author":"Comber","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_28","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_29","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1080\/15481603.2017.1331510","article-title":"Wetland classification in Newfoundland and Labrador using multi-source SAR and optical data integration","volume":"54","author":"Amani","year":"2017","journal-title":"GIScience Remote Sens."},{"key":"ref_30","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_31","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_32","doi-asserted-by":"crossref","first-page":"1","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_33","unstructured":"Woodhouse, I.H. (2006). Introduction to Microwave Remote Sensing, CRC Press."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1080\/14498596.2008.9635137","article-title":"Mangrove species and stand mapping in Gazi Bay (Kenya) using quickbird satellite imagery","volume":"53","author":"Neukermans","year":"2008","journal-title":"J. Spat. Sci."},{"key":"ref_35","first-page":"81","article-title":"Remote sensing of giant reed with quickbird satellite imagery","volume":"43","author":"Everitt","year":"2005","journal-title":"J. Aquat. Plant. Manag."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1080\/10106040408542323","article-title":"Using aerial color-infrared photography and QuickBird satellite imagery for mapping wetland vegetation","volume":"19","author":"Everitt","year":"2004","journal-title":"Geocarto Int."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1672\/08-34.1","article-title":"Assessing the use of multiseason quickbird imagery for mapping invasive species in a Lake Erie coastal marsh","volume":"28","author":"Johnston","year":"2008","journal-title":"Wetlands"},{"key":"ref_38","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_39","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.rse.2007.05.003","article-title":"Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using quickbird satellite imagery","volume":"112","author":"Laba","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_40","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. J."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"885","DOI":"10.14358\/PERS.80.9.885","article-title":"WorldView-2 high spatial resolution improves desert invasive plant detection","volume":"80","author":"Sankey","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.rse.2016.04.025","article-title":"Mapping Solanum mauritianum plant invasions using WorldView-2 imagery and unsupervised random forests","volume":"182","author":"Peerbhay","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_43","first-page":"23","article-title":"Testing the discrimination and detection limits of WorldView-2 imagery on a challenging invasive plant target","volume":"44","author":"Robinson","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_44","first-page":"55","article-title":"Remote sensing as a tool for monitoring plant invasions: Testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed)","volume":"25","author":"Pergl","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_45","first-page":"903","article-title":"Does the data resolution\/origin matter? Satellite, airborne and UAV imagery to tackle plant invasions","volume":"41","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2199","DOI":"10.1080\/01431161.2016.1239288","article-title":"Using unmanned aerial vehicles for high-resolution remote sensing to map invasive Phragmites australis in coastal wetlands","volume":"38","author":"Samiappan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Abeysinghe, T., Milas, A.S., Arend, K., Hohman, B., Reil, P., Gregory, A., and V\u00e1zquez-Ortega, A. (2019). Mapping invasive Phragmites australis in the Old Woman Creek estuary using UAV remote sensing and machine learning classifiers. Remote Sens., 11.","DOI":"10.3390\/rs11111380"},{"key":"ref_48","first-page":"9","article-title":"Monitoring spatial variability and temporal dynamics of phragmites using unmanned aerial vehicles","volume":"9","year":"2018","journal-title":"Front. Plant Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"9632","DOI":"10.3390\/rs70809632","article-title":"Inventory of small forest areas using an unmanned aerial system","volume":"7","author":"Puliti","year":"2015","journal-title":"Remote Sens."},{"key":"ref_50","unstructured":"Minnesota Department of Natural Resources (2019, September 01). Kingsbury Bay-Grassy Point Habitat Restoration Project. Available online: http:\/\/files.dnr.state.mn.us\/input\/environmentalreview\/kingsbury\/eaw.pdf."},{"key":"ref_51","unstructured":"Pix4D (2019, September 01). Pix4Dmapper (Version 4.2.27). Available online: http:\/\/www.pix4d.com."},{"key":"ref_52","unstructured":"Isenberg, M. (2019, September 01). LAStools\u2014Efficient LiDAR Processing Software (Version 170313, Academic). Available online: http:\/\/rapidlasso.com\/LAStools."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1109\/TPAMI.1980.4766994","article-title":"Digital image enhancement and noise filtering by use of local statistics","volume":"2","author":"Lee","year":"1980","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2238","DOI":"10.1109\/TGRS.2005.855067","article-title":"Modeling temporal evolution of junco marshes radar signatures","volume":"43","author":"Grings","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1109\/TGRS.2005.863482","article-title":"Monitoring flood condition in marshes using em models and envisat ASAR observations","volume":"44","author":"Grings","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_56","unstructured":"(2019, September 01). S1TBX\u2014ESA Sentinel-1 Toolbox (Version 6.0.7). Available online: http:\/\/step.esa.int."},{"key":"ref_57","unstructured":"(2019, September 01). SNAP\u2014ESA Sentinel Application Platform (Version 6.0.6). Available online: http:\/\/step.esa.int."},{"key":"ref_58","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_59","unstructured":"GDAL\/OGR Contributors (2019) Contributors (2019, September 01). GDAL\/OGR Geospatial Data Abstraction Software Library 2019. Available online: https:\/\/github.com\/OSGeo\/gdal\/blob\/master\/CITATION."},{"key":"ref_60","unstructured":"Environmental Systems Research Institute (2019, September 01). ArcMap (Version 10.7). Available online: http:\/\/www.esri.com."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Chabot, D., Dillon, C., Shemrock, A., Weissflog, N., and Sager, E.P.S. (2018). An object-based image analysis workflow for monitoring shallow-water aquatic vegetation in multispectral drone imagery. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7080294"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1080\/22797254.2017.1373602","article-title":"Object-based classification of wetland vegetation using very high-resolution unmanned air system imagery","volume":"50","author":"Liu","year":"2017","journal-title":"Eur. J. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.ecolind.2016.09.029","article-title":"Comparison of object-based and pixel-based Random Forest algorithm for wetland vegetation mapping using high spatial resolution GF-1 and SAR data","volume":"73","author":"Fu","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Halabisky, M., Babcock, C., and Moskal, L.M. (2018). Harnessing the temporal dimension to improve object-based image analysis classification of wetlands. Remote Sens., 10.","DOI":"10.3390\/rs10091467"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"319","DOI":"10.3390\/rs3020319","article-title":"Object-based image analysis for detection of Japanese Knotweed s.l. taxa (polygonaceae) in Wales (UK)","volume":"3","author":"Jones","year":"2011","journal-title":"Remote Sens."},{"key":"ref_66","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_67","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.isprsjprs.2003.10.002","article-title":"Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information","volume":"58","author":"Benz","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2013.10.005","article-title":"Evaluation of data fusion and image segmentation in earth observation based rapid mapping workflows","volume":"87","author":"Witharana","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_70","unstructured":"Trimble (2019, September 01). eCognition Developer (Version 9.4). Available online: https:\/\/geospatial.trimble.com\/products-and-solutions\/ecognition."},{"key":"ref_71","first-page":"152","article-title":"Extraction of vegetation information from visible unmanned aerial vehicle images","volume":"31","author":"Wang","year":"2015","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Alvarez-Taboada, F., Paredes, C., and Juli\u00e1n-Pelaz, J. (2017). Mapping of the invasive species hakea sericea using unmanned aerial vehicle (UAV) and WorldView-2 imagery and an object-oriented approach. Remote Sens., 9.","DOI":"10.3390\/rs9090913"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.rse.2019.03.025","article-title":"UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data","volume":"227","author":"Kattenborn","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1411","DOI":"10.1007\/s10530-013-0578-9","article-title":"Remote detection of invasive plants: A review of spectral, textural and phenological approaches","volume":"16","author":"Bradley","year":"2014","journal-title":"Biol. Invasions"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.13031\/2013.17244","article-title":"Textural imaging and discriminant analysis for distinguishing weeds for spot spraying","volume":"41","author":"Meyer","year":"1998","journal-title":"Trans. Am. Soc. Agric. Eng."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"6","author":"Haralick","year":"1973","journal-title":"IEE Trans. Syst. Man Cybern."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (2019). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, CRC Press. [3rd ed.].","DOI":"10.1201\/9780429052729"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"807","DOI":"10.5194\/esurf-7-807-2019","article-title":"Evaluating the potential of post-processing kinematic (PPK) georeferencing for UAV-based structure-from-motion (SfM) photogrammetry and surface change detection ETH Library Evaluating the potential of post-processing kinematic (PPK) georeferencing for UAV-based structure-from-motion (SfM) photogrammetry and surface change detection","volume":"7","author":"Zhang","year":"2019","journal-title":"Earth Surf. Dynam."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Toma\u0161t\u00edk, J., Mokro\u0161, M., Surov\u00fd, P., Grzn\u00e1rov\u00e1, A., and Mergani\u010d, J. (2019). UAV RTK\/PPK method-An optimal solution for mapping inaccessible forested areas?. Remote Sens., 11.","DOI":"10.3390\/rs11060721"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"221","DOI":"10.5194\/isprs-archives-XLI-B6-221-2016","article-title":"Evaluating the potential of RTK-UAV for automatic point cloud generation in 3D rapid mapping","volume":"41","author":"Fazeli","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.isprsjprs.2012.08.006","article-title":"Forest variable estimation using a high-resolution digital surface model","volume":"74","author":"Pekkarinen","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"15933","DOI":"10.3390\/rs71215809","article-title":"Comparison of laser and stereo optical, SAR and InSAR point clouds from air- and space-borne sources in the retrieval of forest inventory attributes","volume":"7","author":"Yu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"518","DOI":"10.3390\/f4030518","article-title":"The utility of image-based point clouds for forest inventory: A comparison with airborne laser scanning","volume":"4","author":"White","year":"2013","journal-title":"Forests"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"90","DOI":"10.2307\/1352816","article-title":"Rates, Patterns, and impacts of Phragmites australis expansion and effects of experimental Phragmites control on vegetation, macroinvertebrates, and fish within tidelands of the lower connecticut river","volume":"24","author":"Warren","year":"2001","journal-title":"Estuaries"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/S0034-4257(02)00196-7","article-title":"Spectral discrimination of vegetation types in a coastal wetland","volume":"85","author":"Schmidt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"290","DOI":"10.5589\/m13-038","article-title":"Wetland mapping with LiDAR derivatives, SAR polarimetric decompositions, and LiDAR-SAR fusion using a random forest classifier","volume":"39","author":"Millard","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_88","unstructured":"Bourgeau-Chavez, L.L., Riordan, K., Powell, R.B., Miller, N., and Nowels, M. (2009). Improving wetland characterization with multi-sensor, multi-Improving wetland characterization with multi-sensor, multi-temporal SAR and optical\/infrared data fusion. Advances in Geoscience and Remote Sensing, IntechOpen."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1023\/A:1010005724468","article-title":"The effects of Phragmites removal on nutrient pools in a freshwater tidal marsh ecosystem","volume":"1","author":"Meyerson","year":"1999","journal-title":"Biol. Invasions"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1023\/A:1011453003168","article-title":"Modification of sediments and macrofauna by an invasive marsh plant","volume":"3","author":"Talley","year":"2001","journal-title":"Biol. Invasions"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"3212","DOI":"10.3390\/rs5073212","article-title":"Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota","volume":"5","author":"Corcoran","year":"2013","journal-title":"Remote Sens."},{"key":"ref_92","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_93","doi-asserted-by":"crossref","first-page":"8563","DOI":"10.3390\/rs70708563","article-title":"Evaluation of polarimetric SAR decomposition for classifying wetland vegetation types","volume":"7","author":"Hong","year":"2015","journal-title":"Remote Sens."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1109\/36.485127","article-title":"A review of target decomposition theorems in radar polarimetry","volume":"34","author":"Cloude","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3303\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:48:26Z","timestamp":1760165306000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3303"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,20]]},"references-count":94,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13163303"],"URL":"https:\/\/doi.org\/10.3390\/rs13163303","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,20]]}}}