{"id":"https://openalex.org/W4312655820","doi":"https://doi.org/10.1109/lgrs.2022.3216274","title":"An Improved Method for Estimating Clumping Index by Digital Hemispheric Photography With Field Measurements","display_name":"An Improved Method for Estimating Clumping Index by Digital Hemispheric Photography With Field Measurements","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312655820","doi":"https://doi.org/10.1109/lgrs.2022.3216274"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3216274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3216274","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5009547740","display_name":"Yidong Tong","orcid":"https://orcid.org/0000-0001-5033-2511"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yidong Tong","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5033-2511","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004770935","display_name":"Ziti Jiao","orcid":"https://orcid.org/0000-0002-3701-0830"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziti Jiao","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3701-0830","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017154983","display_name":"Xiaoning Zhang","orcid":"https://orcid.org/0000-0002-1352-5143"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoning Zhang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112884934","display_name":"Siyang Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyang Yin","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100765886","display_name":"Jing Guo","orcid":"https://orcid.org/0000-0003-1962-6559"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Guo","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.153,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55457911,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998000264167786,"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":0.9998000264167786,"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/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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":0.9987999796867371,"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/logarithm","display_name":"Logarithm","score":0.6408055424690247},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.599247395992279},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.5385817885398865},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5300611853599548},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.506693422794342},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.47181761264801025},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.45675477385520935},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.4560908377170563},{"id":"https://openalex.org/keywords/fraction","display_name":"Fraction (chemistry)","score":0.4325808882713318},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4138805866241455},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4127802550792694},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39933300018310547},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3392457067966461},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17311668395996094},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11956402659416199},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1175251305103302},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1132047176361084}],"concepts":[{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.6408055424690247},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.599247395992279},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.5385817885398865},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5300611853599548},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.506693422794342},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.47181761264801025},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.45675477385520935},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.4560908377170563},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.4325808882713318},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4138805866241455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4127802550792694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39933300018310547},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3392457067966461},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17311668395996094},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11956402659416199},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1175251305103302},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1132047176361084},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3216274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3216274","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1997735444","display_name":"\u690d\u88ab\u805a\u96c6\u6307\u6570\u7684\u9065\u611f\u53cd\u6f14\u3001\u5c3a\u5ea6\u6548\u5e94\u53ca\u4ea7\u54c1\u9a8c\u8bc1\u65b9\u6cd5\u7814\u7a76","funder_award_id":"41971288","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3224897918","display_name":null,"funder_award_id":"42090013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W52417668","https://openalex.org/W1500576594","https://openalex.org/W1966963755","https://openalex.org/W1971116548","https://openalex.org/W1974902368","https://openalex.org/W1980976193","https://openalex.org/W1982818815","https://openalex.org/W1988775509","https://openalex.org/W1995103915","https://openalex.org/W1995993053","https://openalex.org/W2007167499","https://openalex.org/W2019248281","https://openalex.org/W2026200869","https://openalex.org/W2044624560","https://openalex.org/W2083031250","https://openalex.org/W2090626095","https://openalex.org/W2095958845","https://openalex.org/W2108743255","https://openalex.org/W2130546556","https://openalex.org/W2165503062","https://openalex.org/W2167248655","https://openalex.org/W2557136359","https://openalex.org/W2789657632","https://openalex.org/W2905511257","https://openalex.org/W3133771980"],"related_works":["https://openalex.org/W2387409199","https://openalex.org/W2040547031","https://openalex.org/W2000800911","https://openalex.org/W3160845651","https://openalex.org/W2364209969","https://openalex.org/W1977422739","https://openalex.org/W2071765897","https://openalex.org/W2083031250","https://openalex.org/W2021493386","https://openalex.org/W842158673"],"abstract_inverted_index":{"Clumping":[0],"index":[1,122],"(CI)":[2],"field":[3,48,133,196],"measurements":[4,193],"based":[5,98],"on":[6,99],"the":[7,33,67,71,74,80,84,107,119,159,164,175,179,184,191],"logarithmic":[8],"gap":[9,64],"fraction":[10],"averaging":[11],"(LX)":[12],"method":[13,22,60,140,157,171],"are":[14],"widely":[15],"used.":[16],"However,":[17],"some":[18],"challenges":[19],"regarding":[20],"this":[21,52,90],"have":[23],"been":[24],"recognized;":[25],"e.g.,":[26],"CI":[27,47,192],"overestimation":[28,144],"or":[29],"underestimation":[30],"occurs":[31],"in":[32,46,73,190],"sampling":[34],"units":[35,65],"where":[36],"there":[37],"is":[38],"no":[39],"measurement":[40],"gap,":[41],"which":[42],"creates":[43],"major":[44],"uncertainties":[45],"measurements.":[49,134],"To":[50,88],"address":[51],"issue,":[53],"we":[54,92],"proposed":[55],"an":[56],"improved":[57],"eight-connected":[58],"LX":[59],"that":[61,138],"replaces":[62],"null":[63],"with":[66,131],"arithmetic":[68],"mean":[69],"of":[70,83,155,178,194],"gaps":[72],"eight":[75],"connected":[76],"neighbouring":[77,81],"units,":[78],"considering":[79,118],"connections":[82],"natural":[85],"foliage":[86],"extension.":[87],"validate":[89],"method,":[91],"designed":[93],"two":[94],"controlled":[95],"experimental":[96],"schemes":[97],"simulated":[100],"digital":[101],"hemispheric":[102],"photography":[103],"(DHP)":[104],"images":[105],"through":[106],"LargE-Scale":[108],"Remote":[109],"Sensing":[110],"Data":[111],"and":[112,124,145,187],"Image":[113],"Simulation":[114],"Framework":[115],"(LESS)":[116],"model":[117],"leaf":[120,125],"area":[121],"(LAI)":[123],"angle":[126],"distribution":[127],"(LAD),":[128],"respectively,":[129],"together":[130],"collected":[132],"The":[135],"results":[136,181],"showed":[137],"our":[139,156,170],"could":[141],"almost":[142],"prevent":[143],"improve":[146,174],"underestimated":[147],"CIs":[148,154,166],"by":[149],"nearly":[150],"20%.":[151],"In":[152,168],"addition,":[153],"had":[158],"smallest":[160],"error":[161],"compared":[162],"to":[163,183],"\u201ctrue\u201d":[165],"(error<0.1).":[167],"conclusion,":[169],"can":[172],"significantly":[173],"data":[176],"quality":[177],"simulation":[180],"relative":[182],"existing":[185],"methods":[186],"present":[188],"potentials":[189],"upcoming":[195],"campaigns.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
