{"id":"https://openalex.org/W4384202925","doi":"https://doi.org/10.3390/rs15143511","title":"Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis","display_name":"Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis","publication_year":2023,"publication_date":"2023-07-12","ids":{"openalex":"https://openalex.org/W4384202925","doi":"https://doi.org/10.3390/rs15143511"},"language":"en","primary_location":{"id":"doi:10.3390/rs15143511","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/rs15143511","pdf_url":"https://www.mdpi.com/2072-4292/15/14/3511/pdf?version=1689158699","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/14/3511/pdf?version=1689158699","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075047616","display_name":"Connor J. Anderson","orcid":"https://orcid.org/0000-0003-1769-1293"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I1322780083","display_name":"Minnesota Department of Natural Resources","ror":"https://ror.org/056vcnr65","country_code":"US","type":"government","lineage":["https://openalex.org/I1322780083"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Connor J. Anderson","raw_affiliation_strings":["Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"],"affiliations":[{"raw_affiliation_string":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA","institution_ids":["https://openalex.org/I1322780083","https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076896913","display_name":"Daniel Heins","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I1322780083","display_name":"Minnesota Department of Natural Resources","ror":"https://ror.org/056vcnr65","country_code":"US","type":"government","lineage":["https://openalex.org/I1322780083"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Heins","raw_affiliation_strings":["Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"],"affiliations":[{"raw_affiliation_string":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA","institution_ids":["https://openalex.org/I1322780083","https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078478026","display_name":"Keith C. Pelletier","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I1322780083","display_name":"Minnesota Department of Natural Resources","ror":"https://ror.org/056vcnr65","country_code":"US","type":"government","lineage":["https://openalex.org/I1322780083"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keith C. Pelletier","raw_affiliation_strings":["Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"],"affiliations":[{"raw_affiliation_string":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA","institution_ids":["https://openalex.org/I1322780083","https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068564619","display_name":"Joseph Knight","orcid":"https://orcid.org/0000-0001-5846-9416"},"institutions":[{"id":"https://openalex.org/I1322780083","display_name":"Minnesota Department of Natural Resources","ror":"https://ror.org/056vcnr65","country_code":"US","type":"government","lineage":["https://openalex.org/I1322780083"]},{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph F. Knight","raw_affiliation_strings":["Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA"],"affiliations":[{"raw_affiliation_string":"Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA","institution_ids":["https://openalex.org/I1322780083","https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075047616"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I1322780083"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.7543,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66919338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"15","issue":"14","first_page":"3511","last_page":"3511"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10779","display_name":"Coastal wetland ecosystem dynamics","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/phragmites","display_name":"Phragmites","score":0.7685043811798096},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7412612438201904},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7171894311904907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6649396419525146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6250325441360474},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5699678659439087},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5335650444030762},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4618571996688843},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4158492982387543},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.4115701913833618},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3972904086112976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34317272901535034},{"id":"https://openalex.org/keywords/wetland","display_name":"Wetland","score":0.22629502415657043},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1923752725124359},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.17383918166160583},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.12387546896934509}],"concepts":[{"id":"https://openalex.org/C2781178838","wikidata":"https://www.wikidata.org/wiki/Q1976487","display_name":"Phragmites","level":3,"score":0.7685043811798096},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7412612438201904},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7171894311904907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6649396419525146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6250325441360474},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5699678659439087},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5335650444030762},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4618571996688843},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4158492982387543},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.4115701913833618},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3972904086112976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34317272901535034},{"id":"https://openalex.org/C67715294","wikidata":"https://www.wikidata.org/wiki/Q170321","display_name":"Wetland","level":2,"score":0.22629502415657043},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1923752725124359},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.17383918166160583},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.12387546896934509},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15143511","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/rs15143511","pdf_url":"https://www.mdpi.com/2072-4292/15/14/3511/pdf?version=1689158699","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:074d6fdc6caa4787ace9c1f2593ebb3c","is_oa":true,"landing_page_url":"https://doaj.org/article/074d6fdc6caa4787ace9c1f2593ebb3c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 14, p 3511 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/14/3511/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15143511","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 14; Pages: 3511","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15143511","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/rs15143511","pdf_url":"https://www.mdpi.com/2072-4292/15/14/3511/pdf?version=1689158699","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4384202925.pdf"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W324639438","https://openalex.org/W828662481","https://openalex.org/W1569008196","https://openalex.org/W1766560712","https://openalex.org/W1909740415","https://openalex.org/W1981556642","https://openalex.org/W1984792953","https://openalex.org/W2018622407","https://openalex.org/W2043351131","https://openalex.org/W2044086710","https://openalex.org/W2044465660","https://openalex.org/W2050039725","https://openalex.org/W2050858980","https://openalex.org/W2055616033","https://openalex.org/W2059921885","https://openalex.org/W2061240006","https://openalex.org/W2063564951","https://openalex.org/W2083930074","https://openalex.org/W2101234009","https://openalex.org/W2102128253","https://openalex.org/W2113818227","https://openalex.org/W2115523836","https://openalex.org/W2116964561","https://openalex.org/W2121958618","https://openalex.org/W2123314391","https://openalex.org/W2123580386","https://openalex.org/W2147789044","https://openalex.org/W2149861467","https://openalex.org/W2163271349","https://openalex.org/W2167895849","https://openalex.org/W2168851529","https://openalex.org/W2261059368","https://openalex.org/W2470436150","https://openalex.org/W2516578291","https://openalex.org/W2528004483","https://openalex.org/W2533705865","https://openalex.org/W2567495574","https://openalex.org/W2586169538","https://openalex.org/W2604870469","https://openalex.org/W2700626536","https://openalex.org/W2746485780","https://openalex.org/W2776146695","https://openalex.org/W2803051956","https://openalex.org/W2911311508","https://openalex.org/W2951680932","https://openalex.org/W2968103542","https://openalex.org/W2969832320","https://openalex.org/W2971162270","https://openalex.org/W2999309192","https://openalex.org/W3091826287","https://openalex.org/W3111224674","https://openalex.org/W3118281808","https://openalex.org/W3122622298","https://openalex.org/W3148355839","https://openalex.org/W3161841436","https://openalex.org/W3179296859","https://openalex.org/W3187443852","https://openalex.org/W4210699701","https://openalex.org/W4210754462","https://openalex.org/W4285793953","https://openalex.org/W4286697091","https://openalex.org/W4293526428","https://openalex.org/W4296163995","https://openalex.org/W4319967897","https://openalex.org/W6631190155","https://openalex.org/W6637909036","https://openalex.org/W6675354045","https://openalex.org/W6713854444"],"related_works":["https://openalex.org/W2061854569","https://openalex.org/W2011346835","https://openalex.org/W2805647008","https://openalex.org/W2356677996","https://openalex.org/W3176113198","https://openalex.org/W2366601368","https://openalex.org/W2186831007","https://openalex.org/W2792279927","https://openalex.org/W4385497869","https://openalex.org/W283587633"],"abstract_inverted_index":{"Machine":[0],"learning":[1,23,115],"is":[2,31],"frequently":[3],"combined":[4],"with":[5,103],"imagery":[6,65,96],"acquired":[7,66],"from":[8,48,91,107,124,139],"uncrewed":[9],"aircraft":[10],"systems":[11],"(UASs)":[12],"to":[13,43],"detect":[14],"invasive":[15,45,136],"plants.":[16],"Having":[17],"prior":[18],"knowledge":[19],"of":[20,38,195],"which":[21],"machine":[22],"algorithm":[24],"will":[25],"produce":[26],"the":[27,36,86,92,151,157,170,186,192],"most":[28],"accurate":[29,193],"results":[30],"difficult.":[32],"This":[33],"study":[34,126,184],"examines":[35],"efficacy":[37],"a":[39,129,173,178],"voting-based":[40,87,130,152],"ensemble":[41,88,131,153],"classifier":[42,132,154],"identify":[44,135],"Phragmites":[46,137,196],"australis":[47,138,197],"three-band":[49],"(red,":[50,56],"green,":[51,57],"blue;":[52],"RGB)":[53],"and":[54,78,94,104,141,159,177],"five-band":[55],"blue,":[58],"red":[59],"edge,":[60],"near-infrared;":[61],"multispectral;":[62],"MS)":[63],"UAS":[64],"over":[67],"multiple":[68],"Minnesota":[69],"wetlands.":[70],"A":[71],"Random":[72],"Forest,":[73],"histogram-based":[74],"gradient-boosting":[75],"classification":[76],"tree,":[77],"two":[79],"artificial":[80],"neural":[81],"networks":[82],"were":[83,97,148],"used":[84],"within":[85],"classifier.":[89],"Classifications":[90],"RGB":[93,140,158],"multispectral":[95,142,160,171],"compared":[98],"across":[99],"validation":[100],"sites":[101],"both":[102,156],"without":[105],"post-processing":[106],"an":[108],"object-based":[109],"image":[110],"analysis":[111],"(OBIA)":[112],"workflow":[113],"(post-machine":[114],"OBIA":[116,120,180],"rule":[117,121,181],"set;":[118],"post-ML":[119,179],"set).":[122],"Results":[123],"this":[125],"suggest":[127],"that":[128],"can":[133],"accurately":[134],"imagery.":[143,161],"Accuracies":[144],"greater":[145],"than":[146],"80%":[147],"attained":[149],"by":[150],"for":[155,188],"The":[162,183],"highest":[163],"accuracy,":[164],"91%,":[165],"was":[166],"achieved":[167],"when":[168],"using":[169],"imagery,":[172],"canopy":[174],"height":[175],"model,":[176],"set.":[182],"emphasizes":[185],"need":[187],"further":[189],"research":[190],"regarding":[191],"identification":[194],"at":[198],"low":[199],"stem":[200],"densities.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2026-01-20T17:24:06.736184","created_date":"2023-07-14T00:00:00"}