{"id":"https://openalex.org/W4402262802","doi":"https://doi.org/10.1109/igarss53475.2024.10640595","title":"An Exploration of Voxel/Connection and Image Segmentation Approaches to Derive High Resolution Rasters of Manning\u2019s n","display_name":"An Exploration of Voxel/Connection and Image Segmentation Approaches to Derive High Resolution Rasters of Manning\u2019s n","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402262802","doi":"https://doi.org/10.1109/igarss53475.2024.10640595"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10640595","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10640595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 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/A5028598562","display_name":"Heather McGrath","orcid":"https://orcid.org/0000-0002-6439-3339"},"institutions":[{"id":"https://openalex.org/I1281735042","display_name":"Natural Resources Canada","ror":"https://ror.org/05hepy730","country_code":"CA","type":"government","lineage":["https://openalex.org/I1281735042","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Heather McGrath","raw_affiliation_strings":["Natural Resources,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Natural Resources,Canada","institution_ids":["https://openalex.org/I1281735042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076305705","display_name":"Mathieu Turgeon-Pelchat","orcid":"https://orcid.org/0000-0001-6032-0290"},"institutions":[{"id":"https://openalex.org/I1281735042","display_name":"Natural Resources Canada","ror":"https://ror.org/05hepy730","country_code":"CA","type":"government","lineage":["https://openalex.org/I1281735042","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mathieu Turgeon-Pelchat","raw_affiliation_strings":["Natural Resources,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Natural Resources,Canada","institution_ids":["https://openalex.org/I1281735042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024229484","display_name":"Hospice Houngbo","orcid":null},"institutions":[{"id":"https://openalex.org/I1281735042","display_name":"Natural Resources Canada","ror":"https://ror.org/05hepy730","country_code":"CA","type":"government","lineage":["https://openalex.org/I1281735042","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hospice Houngbo","raw_affiliation_strings":["Natural Resources,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Natural Resources,Canada","institution_ids":["https://openalex.org/I1281735042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102186591","display_name":"Lingjun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I1281735042","display_name":"Natural Resources Canada","ror":"https://ror.org/05hepy730","country_code":"CA","type":"government","lineage":["https://openalex.org/I1281735042","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Lingjun Zhou","raw_affiliation_strings":["Natural Resources,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Natural Resources,Canada","institution_ids":["https://openalex.org/I1281735042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052317110","display_name":"Zarrin Langari","orcid":null},"institutions":[{"id":"https://openalex.org/I1281735042","display_name":"Natural Resources Canada","ror":"https://ror.org/05hepy730","country_code":"CA","type":"government","lineage":["https://openalex.org/I1281735042","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zarrin Langari","raw_affiliation_strings":["Natural Resources,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Natural Resources,Canada","institution_ids":["https://openalex.org/I1281735042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1281735042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24371312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"9883","last_page":"9887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8762999773025513,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8762999773025513,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.8513000011444092,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10862","display_name":"AI in cancer detection","score":0.7940000295639038,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6883963942527771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6849433183670044},{"id":"https://openalex.org/keywords/connection","display_name":"Connection (principal bundle)","score":0.6782569885253906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6312676072120667},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5703974962234497},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5322988033294678},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.46665072441101074},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43743598461151123},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4303388297557831},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.426455020904541},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.42104774713516235},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3896515369415283},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.17145481705665588},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16216391324996948},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.15193980932235718},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.05856531858444214}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6883963942527771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6849433183670044},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.6782569885253906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6312676072120667},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5703974962234497},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5322988033294678},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.46665072441101074},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43743598461151123},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4303388297557831},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.426455020904541},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.42104774713516235},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3896515369415283},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.17145481705665588},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16216391324996948},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.15193980932235718},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.05856531858444214}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10640595","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10640595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1491301354","https://openalex.org/W1901129140","https://openalex.org/W2046427124","https://openalex.org/W2053780847","https://openalex.org/W2135880151","https://openalex.org/W2656741035","https://openalex.org/W2807567802","https://openalex.org/W2980149079","https://openalex.org/W3096947210","https://openalex.org/W3198940810","https://openalex.org/W3205639660","https://openalex.org/W6740348511","https://openalex.org/W6769349878"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W587735977","https://openalex.org/W2892386716","https://openalex.org/W1998563493","https://openalex.org/W4306164210","https://openalex.org/W4313316311","https://openalex.org/W4362608745","https://openalex.org/W1978142926"],"abstract_inverted_index":{"Manning\u2019s":[0,34,89],"roughness":[1,114],"coefficients":[2],"(Manning\u2019s":[3],"n)":[4],"are":[5,28,54],"numerical":[6],"values":[7],"which":[8],"represent":[9],"the":[10,46,71,113,117,139,157,168,172,182,197,202],"resistance":[11],"to":[12,31,68,83,111,137,151,163,184],"flows":[13],"in":[14,70,105],"river":[15],"channels":[16],"and":[17,21,42,52,58,99,129,144],"floodplains.":[18],"Field":[19,37],"surveys":[20,38],"land":[22,24,126],"use":[23,127],"cover":[25,185],"(LULC)":[26],"maps":[27,48],"commonly":[29],"used":[30],"infer":[32],"these":[33,213],"n":[35,149],"values.":[36,115],"can":[39,215],"be":[40,216],"time":[41],"labour":[43],"intensive":[44],"while":[45],"LULC":[47],"derived":[49],"from":[50,73],"Landsat":[51],"RadarSat-2":[53],"often":[55],"too":[56],"coarse":[57],"may":[59],"produce":[60],"inaccurate":[61],"representations":[62],"of":[63,141,212],"true":[64],"surface":[65],"roughness,":[66],"leading":[67],"errors":[69],"outputs":[72],"hydraulic":[74],"models.":[75],"In":[76,116],"this":[77],"work":[78,207],"we":[79,120],"tested":[80],"two":[81],"approaches":[82],"generate":[84],"high":[85],"resolution":[86],"surfaces":[87],"depicting":[88],"n.":[90],"The":[91,178],"first":[92],"is":[93,161,208],"using":[94],"unclassified":[95],"LiDAR":[96,158],"point":[97],"clouds":[98],"a":[100,108,147,186],"voxel/connection":[101],"(VC)":[102],"based":[103,159],"approach":[104,160],"combination":[106],"with":[107],"rule-based":[109],"table":[110,174],"set":[112],"second":[118],"method,":[119],"created":[121],"training":[122,199],"data":[123,204],"for":[124],"several":[125],"categories":[128],"trained":[130],"an":[131],"Image":[132],"Segmentation":[133],"(IS)":[134],"U-Net":[135],"model":[136],"predict":[138],"category":[140],"each":[142,152],"pixel":[143],"then":[145],"applied":[146],"Manning's":[148],"value":[150],"category.":[153],"Our":[154],"results":[155],"indicate":[156],"able":[162],"label":[164],"all":[165],"pixels":[166,193],"within":[167],"study":[169],"region,":[170],"but":[171,191],"reclass":[173],"needs":[175],"more":[176,189],"attention.":[177],"IS":[179],"method":[180],"has":[181],"capability":[183],"larger":[187],"area":[188],"efficiently,":[190],"many":[192],"did":[194],"not":[195],"fit":[196],"existing":[198],"labels,":[200],"leaving":[201],"output":[203],"incomplete.":[205],"Future":[206],"needed":[209],"before":[210],"either":[211],"techniques":[214],"reliably":[217],"implemented.":[218]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}