{"id":"https://openalex.org/W4386380322","doi":"https://doi.org/10.3390/ijgi12090361","title":"Evaluation of Machine Learning Algorithms in the Classification of Multispectral Images from the Sentinel-2A/2B Orbital Sensor for Mapping the Environmental Dynamics of Ria Formosa (Algarve, Portugal)","display_name":"Evaluation of Machine Learning Algorithms in the Classification of Multispectral Images from the Sentinel-2A/2B Orbital Sensor for Mapping the Environmental Dynamics of Ria Formosa (Algarve, Portugal)","publication_year":2023,"publication_date":"2023-09-01","ids":{"openalex":"https://openalex.org/W4386380322","doi":"https://doi.org/10.3390/ijgi12090361"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi12090361","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi12090361","pdf_url":"https://www.mdpi.com/2220-9964/12/9/361/pdf?version=1693556511","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"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":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/12/9/361/pdf?version=1693556511","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089872408","display_name":"Flavo Elano Soares de Souza","orcid":"https://orcid.org/0000-0003-4996-0371"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Flavo Elano Soares de Souza","raw_affiliation_strings":["Agricultural School of Jundia\u00ed, Federal University of Rio Grande do Norte, POB 7, Maca\u00edba 59280-000, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-4996-0371","affiliations":[{"raw_affiliation_string":"Agricultural School of Jundia\u00ed, Federal University of Rio Grande do Norte, POB 7, Maca\u00edba 59280-000, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074169797","display_name":"Jos\u00e9 Rodrigues","orcid":"https://orcid.org/0000-0002-2793-8192"},"institutions":[{"id":"https://openalex.org/I71503853","display_name":"University of Algarve","ror":"https://ror.org/014g34x36","country_code":"PT","type":"education","lineage":["https://openalex.org/I71503853"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 In\u00e1cio de Jesus Rodrigues","raw_affiliation_strings":["Department of Civil Engineering, Algarve University, 8005-139 Faro, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Algarve University, 8005-139 Faro, Portugal","institution_ids":["https://openalex.org/I71503853"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089872408"],"corresponding_institution_ids":["https://openalex.org/I35046152"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.0065,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79206358,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"12","issue":"9","first_page":"361","last_page":"361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9478999972343445,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.730344295501709},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7179679870605469},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.689942479133606},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6439181566238403},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6159267425537109},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5871191620826721},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5440226793289185},{"id":"https://openalex.org/keywords/toolbox","display_name":"Toolbox","score":0.536590576171875},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5119258165359497},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.46513456106185913},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.44482359290122986},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4278448820114136},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.42094963788986206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37021762132644653},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3248017430305481},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.15038108825683594},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12810474634170532}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.730344295501709},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7179679870605469},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689942479133606},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6439181566238403},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6159267425537109},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5871191620826721},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5440226793289185},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.536590576171875},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5119258165359497},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.46513456106185913},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.44482359290122986},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4278448820114136},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42094963788986206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37021762132644653},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3248017430305481},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.15038108825683594},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12810474634170532},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/ijgi12090361","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi12090361","pdf_url":"https://www.mdpi.com/2220-9964/12/9/361/pdf?version=1693556511","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"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":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c1f68610560f4e88ac39d3dd7b12c1d8","is_oa":true,"landing_page_url":"https://doaj.org/article/c1f68610560f4e88ac39d3dd7b12c1d8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information, Vol 12, Iss 9, p 361 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2220-9964/12/9/361/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/ijgi12090361","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":"ISPRS International Journal of Geo-Information","raw_type":"Text"},{"id":"pmh:oai:sapientia.ualg.pt:10400.1/20050","is_oa":true,"landing_page_url":"http://hdl.handle.net/10400.1/20050","pdf_url":null,"source":{"id":"https://openalex.org/S4306402433","display_name":"Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.3390/ijgi12090361","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi12090361","pdf_url":"https://www.mdpi.com/2220-9964/12/9/361/pdf?version=1693556511","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"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":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321178","display_name":"Governo Brasil","ror":"https://ror.org/00n0s9w57"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320325185","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386380322.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1964748722","https://openalex.org/W2069358561","https://openalex.org/W2114401841","https://openalex.org/W2161548576","https://openalex.org/W2164777277","https://openalex.org/W2617818785","https://openalex.org/W2732720900","https://openalex.org/W2776146695","https://openalex.org/W2888728157","https://openalex.org/W2938239749","https://openalex.org/W3007546903","https://openalex.org/W3035067580","https://openalex.org/W3046906002","https://openalex.org/W3120751115","https://openalex.org/W3166082850","https://openalex.org/W4310177400","https://openalex.org/W4312084665","https://openalex.org/W6677173349"],"related_works":["https://openalex.org/W4224262160","https://openalex.org/W4205206396","https://openalex.org/W1618196697","https://openalex.org/W2965693718","https://openalex.org/W2155850863","https://openalex.org/W4210628983","https://openalex.org/W2368866852","https://openalex.org/W2623725391","https://openalex.org/W2385238472","https://openalex.org/W2756012949"],"abstract_inverted_index":{"With":[0],"the":[1,10,20,34,42,74,97,107,115,132,139,145,151,160,187,192],"growing":[2],"availability":[3],"of":[4,12,22,38,44,51,69,106,208],"remote":[5],"sensing":[6],"orbital":[7],"spatial":[8],"data,":[9],"applications":[11],"machine":[13],"learning":[14],"(ML)":[15],"algorithms":[16,40,71,98,164,210],"have":[17],"been":[18],"leveraging":[19],"field":[21],"process":[23],"automation":[24],"in":[25,41,114],"image":[26],"classification.":[27,133],"The":[28,61,89,134,156],"present":[29],"work":[30],"aimed":[31],"to":[32,65,198,205,212],"evaluate":[33],"precision":[35],"and":[36,85,111,128,150,162,174,217],"accuracy":[37],"ML":[39,70,209],"classification":[43,66,193],"Sentinel":[45],"2A/2B":[46],"images":[47,62,189],"from":[48,196],"an":[49],"area":[50],"high":[52],"environmental":[53],"dynamics,":[54],"such":[55,72],"as":[56,73],"Ria":[57,116],"Formosa":[58,117],"(Algarve,":[59],"Portugal).":[60],"were":[63,102,125,138],"submitted":[64],"by":[67],"groups":[68],"Support":[75],"Vector":[76],"Machine":[77],"(SVM),":[78],"Random":[79],"Forest":[80],"(RF),":[81],"K-Nearest":[82],"Neighbors":[83],"(KNN),":[84],"Decision":[86],"Tree":[87],"(DT).":[88],"Orfeo":[90],"Toolbox":[91],"(OTB)":[92],"open-source":[93],"programming":[94],"package":[95],"made":[96,202],"available.":[99],"Ten":[100],"samples":[101,183],"collected":[103],"for":[104,126,130,170,184,215],"each":[105],"14":[108],"land":[109],"use":[110],"cover":[112],"classes":[113],"area,":[118],"totaling":[119],"140":[120],"samples.":[121],"Of":[122],"these,":[123],"70%":[124],"training":[127],"30%":[129],"validating":[131],"evaluation":[135,201],"metrics":[136],"used":[137],"class":[140,178],"discrimination":[141,168,179],"measures:":[142],"Recall":[143],"(R),":[144],"Global":[146],"Kappa":[147],"Index":[148,154],"(k),":[149],"General":[152],"Accuracy":[153],"(OA).":[155],"results":[157],"showed":[158],"that":[159],"KNN":[161],"DT":[163],"demonstrated":[165],"a":[166],"greater":[167],"capacity":[169],"most":[171],"classes.":[172],"SVM":[173],"RF":[175],"significantly":[176,190],"improved":[177,191],"when":[180],"using":[181],"larger":[182],"training.":[185],"Merging":[186],"classified":[188],"accuracy,":[194],"ranging":[195],"71%":[197],"81%.":[199],"This":[200],"it":[203],"possible":[204],"define":[206],"sets":[207],"sensitive":[211],"change":[213],"detection":[214],"mapping":[216],"monitoring":[218],"dynamic":[219],"environments.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}