{"id":"https://openalex.org/W2982894653","doi":"https://doi.org/10.1109/igarss.2019.8899201","title":"Different Modality Based Remote Sensing Data Fusion Approach for Efficient Classification of Agriculture and Urban Subclasses","display_name":"Different Modality Based Remote Sensing Data Fusion Approach for Efficient Classification of Agriculture and Urban Subclasses","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2982894653","doi":"https://doi.org/10.1109/igarss.2019.8899201","mag":"2982894653"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053380193","display_name":"Shiv Nath Chaudhri","orcid":"https://orcid.org/0000-0002-5436-2977"},"institutions":[{"id":"https://openalex.org/I91357014","display_name":"Banaras Hindu University","ror":"https://ror.org/04cdn2797","country_code":"IN","type":"education","lineage":["https://openalex.org/I91357014"]},{"id":"https://openalex.org/I56404289","display_name":"Indian Institute of Technology BHU","ror":"https://ror.org/01kh5gc44","country_code":"IN","type":"education","lineage":["https://openalex.org/I56404289"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"S. N. Chaudhri","raw_affiliation_strings":["Indian Institute of Technology (BHU), Varanasi, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology (BHU), Varanasi, India","institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031973259","display_name":"N. S. Rajput","orcid":"https://orcid.org/0000-0002-1650-011X"},"institutions":[{"id":"https://openalex.org/I56404289","display_name":"Indian Institute of Technology BHU","ror":"https://ror.org/01kh5gc44","country_code":"IN","type":"education","lineage":["https://openalex.org/I56404289"]},{"id":"https://openalex.org/I91357014","display_name":"Banaras Hindu University","ror":"https://ror.org/04cdn2797","country_code":"IN","type":"education","lineage":["https://openalex.org/I91357014"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"N. S. Rajput","raw_affiliation_strings":["Indian Institute of Technology (BHU), Varanasi, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology (BHU), Varanasi, India","institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103212472","display_name":"K. P. Singh","orcid":"https://orcid.org/0009-0006-6767-6314"},"institutions":[{"id":"https://openalex.org/I91357014","display_name":"Banaras Hindu University","ror":"https://ror.org/04cdn2797","country_code":"IN","type":"education","lineage":["https://openalex.org/I91357014"]},{"id":"https://openalex.org/I56404289","display_name":"Indian Institute of Technology BHU","ror":"https://ror.org/01kh5gc44","country_code":"IN","type":"education","lineage":["https://openalex.org/I56404289"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. P. Singh","raw_affiliation_strings":["Indian Institute of Technology (BHU), Varanasi, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology (BHU), Varanasi, India","institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075489586","display_name":"Dharmendra Singh","orcid":"https://orcid.org/0000-0002-0396-1494"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"D. Singh","raw_affiliation_strings":["Indian Institute of Technology, Roorkee, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Roorkee, India","institution_ids":["https://openalex.org/I154851008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053380193"],"corresponding_institution_ids":["https://openalex.org/I56404289","https://openalex.org/I91357014"],"apc_list":null,"apc_paid":null,"fwci":0.6812,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73264482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"5710","last_page":"5713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9991999864578247,"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":0.9991999864578247,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9901999831199646,"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/lidar","display_name":"Lidar","score":0.7816588878631592},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7702945470809937},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6912482976913452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6779945492744446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5843936800956726},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.5605279803276062},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5244948267936707},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5206431746482849},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5068793892860413},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5014562606811523},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.475075900554657},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4545317590236664},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4529884159564972},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19475069642066956},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17890194058418274}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7816588878631592},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7702945470809937},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6912482976913452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6779945492744446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5843936800956726},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.5605279803276062},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5244948267936707},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5206431746482849},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5068793892860413},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5014562606811523},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.475075900554657},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4545317590236664},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4529884159564972},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19475069642066956},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17890194058418274},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8899201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W1980018136","https://openalex.org/W2588167042"],"related_works":["https://openalex.org/W2104177156","https://openalex.org/W2031928588","https://openalex.org/W2030080266","https://openalex.org/W2805400851","https://openalex.org/W2463883205","https://openalex.org/W2140940625","https://openalex.org/W4241000610","https://openalex.org/W2781623059","https://openalex.org/W2912288872","https://openalex.org/W2767651786"],"abstract_inverted_index":{"Subclasses":[0],"classification":[1,28],"is":[2,43,132],"one":[3,44],"of":[4,57,91,138],"the":[5,50,65,88,97,100,113,116,126],"major":[6],"challenges":[7],"in":[8,18],"remote":[9],"sensing":[10],"(RS)":[11],"scene":[12],"classification.":[13],"The":[14],"area":[15],"under":[16],"observation,":[17],"order":[19],"to":[20,48],"classify":[21],"agriculture":[22],"and":[23,83,103,106,115],"urban":[24],"subclasses,":[25],"requires":[26],"efficient":[27],"algorithms.":[29],"Among":[30],"such":[31,45],"algorithms,":[32],"deep":[33],"learning":[34],"algorithm":[35],"based":[36],"on":[37,64,95],"Convolutional":[38],"Neural":[39],"Network":[40,72],"(CNN)":[41],"architecture":[42],"promising":[46],"candidate":[47],"obtain":[49],"classified":[51,130],"map.":[52],"In":[53],"this":[54],"work,":[55],"performance":[56],"a":[58,129],"CNN":[59,92],"network":[60],"has":[61],"been":[62,120],"demonstrated":[63],"data":[66,82,110,118],"obtained":[67,133],"from":[68],"National":[69],"Ecological":[70],"Observatory":[71],"(NEON)":[73],"field":[74],"site":[75],"Domain":[76],"17":[77],"by":[78],"considering":[79],"different":[80],"modality":[81],"its":[84],"subsequent":[85],"fusion":[86],"using":[87],"proposed":[89,127],"model":[90],"as":[93],"applied":[94],"(i)":[96],"Hyperspectral,":[98],"(ii)":[99],"Light":[101],"Detection":[102],"Ranging":[104],"(LiDAR)":[105],"then":[107],"(iii)":[108],"fused":[109,121,142],"respectively.":[111],"Both":[112],"Hyperspectral":[114],"LiDAR":[117],"have":[119],"at":[122],"pixel":[123],"level.":[124],"Using":[125],"methodology,":[128],"map":[131],"with":[134],"an":[135],"overall":[136],"accuracy":[137],"96":[139],"percent":[140],"for":[141],"data.":[143]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
