{"id":"https://openalex.org/W2040913085","doi":"https://doi.org/10.1109/igarss.2013.6721184","title":"ISOMAP-based subspace analysis for the classification of hyperspectral data","display_name":"ISOMAP-based subspace analysis for the classification of hyperspectral data","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2040913085","doi":"https://doi.org/10.1109/igarss.2013.6721184","mag":"2040913085"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2013.6721184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2013.6721184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://zenodo.org/record/1272815","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101555924","display_name":"Ling Ding","orcid":"https://orcid.org/0000-0001-6579-2596"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Ding","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China","Inst. of Remote Sensing & Digital Earth, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"raw_affiliation_string":"Inst. of Remote Sensing & Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101748090","display_name":"Ping Tang","orcid":"https://orcid.org/0000-0002-8721-4209"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Tang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China","Inst. of Remote Sensing & Digital Earth, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"raw_affiliation_string":"Inst. of Remote Sensing & Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100413706","display_name":"Hongyi Li","orcid":"https://orcid.org/0000-0003-3414-7070"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyi Li","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China","Inst. of Remote Sensing & Digital Earth, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"raw_affiliation_string":"Inst. of Remote Sensing & Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0898,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.71913003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"429","last_page":"432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"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":0.9994000196456909,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/isomap","display_name":"Isomap","score":0.8073660135269165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7716410756111145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7715824246406555},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7348753213882446},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7270083427429199},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5664371252059937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.560529887676239},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5056641101837158},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4747075140476227},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4621122479438782},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45550182461738586},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44907644391059875},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40303534269332886},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.33487212657928467},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.31301236152648926}],"concepts":[{"id":"https://openalex.org/C2778626561","wikidata":"https://www.wikidata.org/wiki/Q6086067","display_name":"Isomap","level":4,"score":0.8073660135269165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7716410756111145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7715824246406555},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7348753213882446},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7270083427429199},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5664371252059937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.560529887676239},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5056641101837158},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4747075140476227},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4621122479438782},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45550182461738586},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44907644391059875},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40303534269332886},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.33487212657928467},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.31301236152648926},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2013.6721184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2013.6721184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS","raw_type":"proceedings-article"},{"id":"pmh:oai:zenodo.org:1272815","is_oa":true,"landing_page_url":"https://zenodo.org/record/1272815","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:1272815","is_oa":true,"landing_page_url":"https://zenodo.org/record/1272815","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W84941271","https://openalex.org/W1992961908","https://openalex.org/W2001141328","https://openalex.org/W2104253679","https://openalex.org/W2111282613","https://openalex.org/W2154874087","https://openalex.org/W2303501228"],"related_works":["https://openalex.org/W2375574759","https://openalex.org/W1489327846","https://openalex.org/W4287375746","https://openalex.org/W3124275785","https://openalex.org/W2037225398","https://openalex.org/W2132734978","https://openalex.org/W2166963679","https://openalex.org/W2364555648","https://openalex.org/W2352321395","https://openalex.org/W3193686696"],"abstract_inverted_index":{"A":[0,16],"new":[1],"object-oriented":[2,44,114],"mapping":[3],"approach":[4,20,118],"is":[5],"proposed":[6,106,113],"based":[7],"on":[8],"nonlinear":[9,17,115],"subspace":[10,26,37,55,116,130],"feature":[11,27,38,56,71,91],"analysis":[12,117],"of":[13,29,89,96],"hyperspectral":[14,30],"data.":[15],"manifold":[18],"learning":[19],"ISOMAP":[21],"were":[22,40,99],"utilized":[23,50],"to":[24,51,67,103],"obtain":[25],"representation":[28],"remote":[31],"sensing":[32],"imagery.":[33],"Afterwards,":[34],"the":[35,43,69,86,90,94,105,112,125],"extracted":[36],"images":[39,57,92],"fed":[41],"into":[42],"system.":[45],"Multiresolution":[46],"segmentation":[47],"algorithm":[48],"was":[49,64],"extract":[52],"objects":[53],"from":[54,76],"and":[58,82,128],"support":[59],"vector":[60],"machines":[61],"(SVM)":[62],"classifier":[63,98],"then":[65],"used":[66,100],"classify":[68],"object-based":[70],"images,":[72],"texture":[73],"features":[74],"derived":[75],"gray":[77],"level":[78,88],"co-occurrence":[79],"matrix":[80],"(GLCM)":[81],"wavelet":[83],"filter":[84],"at":[85],"pixel":[87],"with":[93],"use":[95],"SVM":[97],"as":[101],"benchmarks":[102],"evaluate":[104],"algorithm.":[107],"Classification":[108],"results":[109],"show":[110],"that":[111],"can":[119],"give":[120],"significantly":[121],"higher":[122],"accuracies":[123],"than":[124],"traditional":[126],"pixel-based":[127],"texture-based":[129],"classification.":[131]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}