{"id":"https://openalex.org/W2997171867","doi":"https://doi.org/10.3390/rs12010039","title":"The t-SNE Algorithm as a Tool to Improve the Quality of Reference Data Used in Accurate Mapping of Heterogeneous Non-Forest Vegetation","display_name":"The t-SNE Algorithm as a Tool to Improve the Quality of Reference Data Used in Accurate Mapping of Heterogeneous Non-Forest Vegetation","publication_year":2019,"publication_date":"2019-12-20","ids":{"openalex":"https://openalex.org/W2997171867","doi":"https://doi.org/10.3390/rs12010039","mag":"2997171867"},"language":"en","primary_location":{"id":"doi:10.3390/rs12010039","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12010039","pdf_url":"https://www.mdpi.com/2072-4292/12/1/39/pdf?version=1576835634","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/2072-4292/12/1/39/pdf?version=1576835634","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075832715","display_name":"Anna Halladin-D\u0105browska","orcid":"https://orcid.org/0000-0002-8040-7833"},"institutions":[{"id":"https://openalex.org/I4210087548","display_name":"MGGP Aero (Poland)","ror":"https://ror.org/0055ya375","country_code":"PL","type":"company","lineage":["https://openalex.org/I4210087548"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Anna Halladin-D\u0105browska","raw_affiliation_strings":["MGGP Aero sp. z o.o., 33-100 Tarn\u00f3w, Poland"],"raw_orcid":"https://orcid.org/0000-0002-8040-7833","affiliations":[{"raw_affiliation_string":"MGGP Aero sp. z o.o., 33-100 Tarn\u00f3w, Poland","institution_ids":["https://openalex.org/I4210087548"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102760561","display_name":"Adam Kania","orcid":"https://orcid.org/0000-0002-2516-4867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adam Kania","raw_affiliation_strings":["Definity Sp. z o.o., 52-116 Wroc\u0142aw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Definity Sp. z o.o., 52-116 Wroc\u0142aw, Poland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021649500","display_name":"Dominik Kope\u0107","orcid":"https://orcid.org/0000-0003-0831-2992"},"institutions":[{"id":"https://openalex.org/I34250744","display_name":"University of \u0141\u00f3d\u017a","ror":"https://ror.org/05cq64r17","country_code":"PL","type":"education","lineage":["https://openalex.org/I34250744"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Dominik Kope\u0107","raw_affiliation_strings":["Department of Geobotany and Plant Ecology, Faculty of Biology and Environmental, University of Lodz, 90-237 \u0141\u00f3d\u017a, Poland"],"raw_orcid":"https://orcid.org/0000-0003-0831-2992","affiliations":[{"raw_affiliation_string":"Department of Geobotany and Plant Ecology, Faculty of Biology and Environmental, University of Lodz, 90-237 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I34250744"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021649500"],"corresponding_institution_ids":["https://openalex.org/I34250744"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.0813,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.87104326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"12","issue":"1","first_page":"39","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6695498824119568},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.648378312587738},{"id":"https://openalex.org/keywords/reference-data","display_name":"Reference data","score":0.5958635210990906},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.587441623210907},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.48654690384864807},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4755120873451233},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.4749372601509094},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.4444632828235626},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4228469729423523},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.42236852645874023},{"id":"https://openalex.org/keywords/natura-2000","display_name":"Natura 2000","score":0.4105243384838104},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.32606375217437744},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2819157838821411},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2052341103553772},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.17881441116333008},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.09703770279884338},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09398594498634338}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6695498824119568},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.648378312587738},{"id":"https://openalex.org/C60478076","wikidata":"https://www.wikidata.org/wiki/Q3036835","display_name":"Reference data","level":2,"score":0.5958635210990906},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.587441623210907},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.48654690384864807},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4755120873451233},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.4749372601509094},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.4444632828235626},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4228469729423523},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.42236852645874023},{"id":"https://openalex.org/C2780815956","wikidata":"https://www.wikidata.org/wiki/Q503021","display_name":"Natura 2000","level":3,"score":0.4105243384838104},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.32606375217437744},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2819157838821411},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2052341103553772},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.17881441116333008},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.09703770279884338},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09398594498634338},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C130217890","wikidata":"https://www.wikidata.org/wiki/Q47041","display_name":"Biodiversity","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs12010039","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12010039","pdf_url":"https://www.mdpi.com/2072-4292/12/1/39/pdf?version=1576835634","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:mdpi.com:/2072-4292/12/1/39/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12010039","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 12; Issue 1; Pages: 39","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12010039","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12010039","pdf_url":"https://www.mdpi.com/2072-4292/12/1/39/pdf?version=1576835634","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":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G3645671516","display_name":null,"funder_award_id":"DZP/BIOSTRATEG-II/390/2015","funder_id":"https://openalex.org/F4320335039","funder_display_name":"Narodowe Centrum Bada\u0144 i Rozwoju"}],"funders":[{"id":"https://openalex.org/F4320322637","display_name":"Politechnika Warszawska","ror":"https://ror.org/00y0xnp53"},{"id":"https://openalex.org/F4320323344","display_name":"Uniwersytet \u0141\u00f3dzki","ror":"https://ror.org/05cq64r17"},{"id":"https://openalex.org/F4320323873","display_name":"Uniwersytet Warszawski","ror":"https://ror.org/039bjqg32"},{"id":"https://openalex.org/F4320327752","display_name":"Szkola Gl\u00f3wna Gospodarstwa Wiejskiego w Warszawie","ror":"https://ror.org/05srvzs48"},{"id":"https://openalex.org/F4320328948","display_name":"Uniwersytet \u015al\u0105ski w Katowicach","ror":"https://ror.org/0104rcc94"},{"id":"https://openalex.org/F4320335039","display_name":"Narodowe Centrum Bada\u0144 i Rozwoju","ror":"https://ror.org/05pwfyy15"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2997171867.pdf","grobid_xml":"https://content.openalex.org/works/W2997171867.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1605688901","https://openalex.org/W1875842236","https://openalex.org/W1980146641","https://openalex.org/W1995443851","https://openalex.org/W1998979050","https://openalex.org/W2036347658","https://openalex.org/W2053154970","https://openalex.org/W2076524499","https://openalex.org/W2083213691","https://openalex.org/W2087556827","https://openalex.org/W2089564362","https://openalex.org/W2090881403","https://openalex.org/W2110644663","https://openalex.org/W2117085409","https://openalex.org/W2132424470","https://openalex.org/W2135758523","https://openalex.org/W2139741891","https://openalex.org/W2142814220","https://openalex.org/W2174158349","https://openalex.org/W2187089797","https://openalex.org/W2221967077","https://openalex.org/W2318752590","https://openalex.org/W2539651710","https://openalex.org/W2589453516","https://openalex.org/W2724349216","https://openalex.org/W2745252301","https://openalex.org/W2789525945","https://openalex.org/W2791978127","https://openalex.org/W2911964244","https://openalex.org/W2942074968","https://openalex.org/W3152294918","https://openalex.org/W4245539475","https://openalex.org/W4253461361","https://openalex.org/W4254182148","https://openalex.org/W6645190923","https://openalex.org/W6670979182","https://openalex.org/W6681168425"],"related_works":["https://openalex.org/W2886494294","https://openalex.org/W4251326655","https://openalex.org/W2082596517","https://openalex.org/W2492661387","https://openalex.org/W2139541082","https://openalex.org/W3115801774","https://openalex.org/W2582300422","https://openalex.org/W4321387504","https://openalex.org/W1987289672","https://openalex.org/W2268445639"],"abstract_inverted_index":{"Supervised":[0],"classification":[1,42,89,221,329],"methods,":[2],"used":[3,35,86,169,208,218],"for":[4,21,36,81,87,108],"many":[5],"applications,":[6],"including":[7],"vegetation":[8],"mapping":[9],"require":[10],"accurate":[11],"\u201cground":[12],"truth\u201d":[13],"to":[14,27,32,69,77,95,121,179,186,277,326],"be":[15,28],"effective.":[16],"Nevertheless,":[17],"it":[18,33],"is":[19,58,127],"common":[20],"the":[22,37,52,62,79,83,88,101,109,132,180,194,210,220,227,290,293,299,327,335],"quality":[23,291],"of":[24,41,51,66,73,90,112,131,137,236,243,266,271,282,292,334,338],"this":[25,74,138],"data":[26,114,118,217],"poorly":[29],"verified":[30],"prior":[31],"being":[34],"training":[38],"and":[39,94,161,174,201,247,301],"validation":[40],"models.":[43],"The":[44,71,124,135,214,251,314],"fact":[45],"that":[46],"noisy":[47],"or":[48],"erroneous":[49],"parts":[50],"reference":[53,84,113,189,197,212,253,283,339],"dataset":[54,85,254],"are":[55],"not":[56],"removed":[57],"usually":[59],"explained":[60],"by":[61,142,231,258,263,298,308,319],"relatively":[63],"high":[64],"resistance":[65,185],"some":[67],"algorithms":[68],"errors.":[70,279],"objective":[72],"study":[75],"was":[76,140,255,311],"demonstrate":[78],"rationale":[80],"cleaning":[82],"heterogeneous":[91,145],"non-forest":[92,146],"vegetation,":[93],"present":[96],"a":[97,128,232,288],"workflow":[98,139],"based":[99],"on":[100],"t-distributed":[102],"stochastic":[103],"neighbor":[104],"embedding":[105],"(t-SNE)":[106],"algorithm":[107],"better":[110],"integration":[111],"with":[115],"remote":[116,215],"sensing":[117,216],"in":[119,183,188,193,199,219,224],"order":[120],"improve":[122],"outcomes.":[123],"proposed":[125],"analysis":[126],"new":[129],"application":[130],"t-SNE":[133,267],"algorithm.":[134],"effectiveness":[136],"tested":[141],"classifying":[143],"three":[144],"Natura":[147],"2000":[148],"habitats:":[149],"Molinia":[150],"meadows":[151],"(Molinion":[152],"caeruleae;":[153],"code":[154],"6410),":[155],"species-rich":[156],"Nardus":[157],"grassland":[158],"(code":[159,164],"6230)":[160],"dry":[162],"heaths":[163],"4030),":[165],"employing":[166],"two":[167,237],"commonly":[168],"algorithms:":[170],"random":[171,332],"forest":[172],"(RF)":[173],"AdaBoost":[175],"(AB),":[176],"which,":[177],"according":[178],"literature,":[181],"differ":[182],"their":[184],"errors":[187],"datasets.":[190],"Polygons":[191],"collected":[192],"field":[195],"(on-ground":[196],"data)":[198],"2016":[200],"2017,":[202],"containing":[203],"no":[204],"intentional":[205],"errors,":[206],"were":[207,222,274,285],"as":[209,296,305,307],"on-ground":[211,252],"dataset.":[213],"obtained":[223,330],"2017":[225],"during":[226],"peak":[228],"growing":[229],"season":[230],"HySpex":[233],"sensor":[234],"consisting":[235],"imaging":[238],"spectrometers":[239],"covering":[240],"spectral":[241],"ranges":[242],"0.4\u20130.9":[244],"\u03bcm":[245,249],"(VNIR-1800)":[246],"0.9\u20132.5":[248],"(SWIR-384).":[250],"gradually":[256],"cleaned":[257],"verifying":[259],"candidate":[260,272],"polygons":[261,273,284],"selected":[262],"visual":[264,309],"interpretation":[265],"plots.":[268],"Around":[269],"40\u201350%":[270],"ultimately":[275],"found":[276],"contain":[278],"Altogether,":[280],"15%":[281],"removed.":[286],"As":[287],"result,":[289],"final":[294],"map,":[295],"assessed":[297],"Kappa":[300,323],"F1":[302],"accuracy":[303,317],"measures":[304],"well":[306],"evaluation,":[310],"significantly":[312],"improved.":[313],"global":[315],"map":[316],"increased":[318],"about":[320],"6%":[321],"(in":[322],"coefficient),":[324],"relative":[325],"baseline":[328],"using":[331],"removal":[333],"same":[336],"number":[337],"polygons.":[340]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}