{"id":"https://openalex.org/W3207734956","doi":"https://doi.org/10.1109/igarss47720.2021.9553463","title":"Investigating the Performance of Hyperspectral and Simulated Sentinel-2 Data for Soybean Canopy Nitrogen Estimation","display_name":"Investigating the Performance of Hyperspectral and Simulated Sentinel-2 Data for Soybean Canopy Nitrogen Estimation","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3207734956","doi":"https://doi.org/10.1109/igarss47720.2021.9553463","mag":"3207734956"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9553463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},"type":"conference-paper","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/A5084404480","display_name":"Jayantrao Mohite","orcid":"https://orcid.org/0000-0003-1289-8797"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jayantrao Mohite","raw_affiliation_strings":["TCS Innovation Labs, Tata Consultancy Services, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TCS Innovation Labs, Tata Consultancy Services, Mumbai, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041057249","display_name":"Suryakant Sawant","orcid":"https://orcid.org/0000-0001-5982-4432"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suryakant Sawant","raw_affiliation_strings":["TCS Innovation Labs, Tata Consultancy Services, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TCS Innovation Labs, Tata Consultancy Services, Mumbai, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056268401","display_name":"Ankur Pandit","orcid":"https://orcid.org/0000-0002-5299-7047"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankur Pandit","raw_affiliation_strings":["TCS Innovation Labs, Tata Consultancy Services, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TCS Innovation Labs, Tata Consultancy Services, Mumbai, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108018625","display_name":"Swati Mittal","orcid":"https://orcid.org/0000-0001-5255-1056"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ajay Mittal","raw_affiliation_strings":["Tata Consultancy Services, Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tata Consultancy Services, Pune, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103866503","display_name":"Srinivasu Pappula","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Srinivasu Pappula","raw_affiliation_strings":["Tata Consultancy Services, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tata Consultancy Services, Hyderabad, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.8448,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73308365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"7059","last_page":"7062"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.995199978351593,"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"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9753000140190125,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Waste Management and Disposal"},"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.827623724937439},{"id":"https://openalex.org/keywords/red-edge","display_name":"Red edge","score":0.5509105920791626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4825812876224518},{"id":"https://openalex.org/keywords/spectroradiometer","display_name":"Spectroradiometer","score":0.46730753779411316},{"id":"https://openalex.org/keywords/canopy","display_name":"Canopy","score":0.44304850697517395},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3914479613304138},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.35152584314346313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33236733078956604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3232966661453247},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.2227174937725067},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.16566914319992065},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13115233182907104},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12437927722930908}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.827623724937439},{"id":"https://openalex.org/C2776388979","wikidata":"https://www.wikidata.org/wiki/Q3422640","display_name":"Red edge","level":3,"score":0.5509105920791626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4825812876224518},{"id":"https://openalex.org/C130066347","wikidata":"https://www.wikidata.org/wiki/Q680509","display_name":"Spectroradiometer","level":3,"score":0.46730753779411316},{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.44304850697517395},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3914479613304138},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.35152584314346313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33236733078956604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3232966661453247},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.2227174937725067},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.16566914319992065},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13115233182907104},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12437927722930908},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9553463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1583261134","https://openalex.org/W1991602809","https://openalex.org/W2019300375","https://openalex.org/W2056435747","https://openalex.org/W2061063014","https://openalex.org/W2084192167","https://openalex.org/W2086314176","https://openalex.org/W2095939249","https://openalex.org/W2384822809","https://openalex.org/W2548132453","https://openalex.org/W2792890061","https://openalex.org/W2793597616","https://openalex.org/W2889742210","https://openalex.org/W2943150678","https://openalex.org/W2992086439","https://openalex.org/W6634849348","https://openalex.org/W7051997766"],"related_works":["https://openalex.org/W2385371209","https://openalex.org/W2318124497","https://openalex.org/W1970217081","https://openalex.org/W3208231720","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W1991437568","https://openalex.org/W2157744011","https://openalex.org/W2098065523","https://openalex.org/W1991776856"],"abstract_inverted_index":{"Nitrogen":[0],"(N)":[1],"is":[2,47,50,259],"one":[3],"of":[4,17,45,58,86,105,195],"the":[5,42,55,61,78,94,102,151,159,179,211,247],"key":[6],"nutrient":[7],"element":[8],"needed":[9,48],"for":[10,237,261],"optimum":[11,43],"crop":[12,24],"growth":[13,32],"and":[14,26,33,80,108,134,139,161,170,206,215,228,255],"production.":[15],"Deficiency":[16],"N":[18,46,59,73,238,263],"leads":[19],"to":[20,71,197],"a":[21,193],"decrease":[22],"in":[23,29,60,74,101,111,178],"production":[25],"excess":[27],"results":[28,202],"poor":[30],"root":[31],"leaching":[34],"into":[35],"groundwater":[36],"thereby":[37],"causing":[38],"environmental":[39],"issues.":[40],"Hence":[41],"application":[44],"which":[49],"possible":[51],"by":[52],"exactly":[53],"estimating":[54],"available":[56],"quantities":[57],"plant.":[62],"In":[63],"this":[64],"study,":[65],"an":[66],"attempt":[67],"has":[68],"been":[69],"made":[70],"estimate":[72],"Soybean":[75,262],"leaves":[76],"using":[77,93,121,145,150],"hyperspectral":[79,128,153],"simulated":[81,136],"Sentinel-2":[82,137,199],"observations.":[83],"Spectral":[84],"observations":[85,248],"fifteen":[87],"soybean":[88],"leaf":[89],"samples":[90],"were":[91,119],"collected":[92],"EKO":[95],"MS-720":[96],"Spectroradiometer.":[97],"The":[98],"instrument":[99],"operates":[100],"spectral":[103,200],"range":[104],"350\u20131050":[106],"nm.":[107],"collects":[109],"data":[110],"contiguous":[112],"213":[113],"bands.":[114],"Support":[115],"Vector":[116],"Regression-based":[117],"models":[118],"evaluated":[120,144],"three":[122],"feature":[123],"selection":[124],"methods,":[125],"1)":[126],"individual":[127,152],"bands,":[129,201],"2)":[130],"Normalized":[131],"band":[132,176],"ratio's":[133],"3)":[135],"bands":[138,154,157,209],"indices.":[140],"Model":[141],"performance":[142],"was":[143],"R2.":[146],"Analysis":[147],"carried":[148],"out":[149],"showed":[155,203],"that":[156,204,219,252],"from":[158,175],"red":[160],"red-edge":[162,180,205,254],"region":[163,181,258],"are":[164,182,234],"performing":[165,183,235],"best":[166,184],"with":[167,185,240],"R2between":[168,186,213],"0.872":[169],"0.876.":[171],"However,":[172],"NBR's":[173],"estimated":[174],"combinations":[177],"0.938":[187],"-":[188],"0.956.":[189],"Further,":[190],"we":[191,249],"identified":[192],"subset":[194],"wavelengths":[196],"simulate":[198],"narrow":[207,256],"NIR":[208,257],"provide":[210],"highest":[212],"0.878":[214],"0.893.":[216],"We":[217],"observed":[218],"indices":[220],"such":[221],"as":[222],"Canopy":[223],"Chlorophyll":[224,229],"Content":[225],"Index":[226,230],"(CCCI)":[227],"Red":[231],"Edge":[232],"(CIRE)":[233],"better":[236],"estimation":[239],"R2of":[241],"0.946,":[242],"0.923,":[243],"respectively.":[244],"Based":[245],"on":[246],"can":[250],"conclude":[251],"red,":[253],"useful":[260],"estimation.":[264]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}