{"id":"https://openalex.org/W4390100494","doi":"https://doi.org/10.1145/3589132.3629974","title":"Geo-knowledge-informed Deep Learning for Auto-identification of Supraglacial Lakes on the Greenland Ice Sheet from Satellite Imagery","display_name":"Geo-knowledge-informed Deep Learning for Auto-identification of Supraglacial Lakes on the Greenland Ice Sheet from Satellite Imagery","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4390100494","doi":"https://doi.org/10.1145/3589132.3629974"},"language":"en","primary_location":{"id":"doi:10.1145/3589132.3629974","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3629974","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3629974","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3629974","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100651653","display_name":"Chen Wei","orcid":"https://orcid.org/0000-0002-4636-2862"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Wei","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101938899","display_name":"Song Gao","orcid":"https://orcid.org/0000-0003-4359-6302"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song Gao","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103247961","display_name":"Feng Zhang","orcid":"https://orcid.org/0000-0002-8642-5637"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100651653"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.2197,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57004909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10644","display_name":"Cryospheric studies and observations","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10644","display_name":"Cryospheric studies and observations","score":0.9998999834060669,"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/T10535","display_name":"Landslides and related hazards","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/T11459","display_name":"Arctic and Antarctic ice dynamics","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/glacier","display_name":"Glacier","score":0.6506237983703613},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.563930332660675},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.5537776947021484},{"id":"https://openalex.org/keywords/greenland-ice-sheet","display_name":"Greenland ice sheet","score":0.5529918670654297},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5248196721076965},{"id":"https://openalex.org/keywords/ice-sheet","display_name":"Ice sheet","score":0.5091568827629089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4804903566837311},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4644792973995209},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.4300692677497864},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.42793920636177063},{"id":"https://openalex.org/keywords/cryosphere","display_name":"Cryosphere","score":0.4129171073436737},{"id":"https://openalex.org/keywords/physical-geography","display_name":"Physical geography","score":0.4038563668727875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4026627540588379},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3697790503501892},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.31194695830345154},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.18715128302574158},{"id":"https://openalex.org/keywords/sea-ice","display_name":"Sea ice","score":0.16314977407455444},{"id":"https://openalex.org/keywords/geomorphology","display_name":"Geomorphology","score":0.1485668420791626}],"concepts":[{"id":"https://openalex.org/C100834320","wikidata":"https://www.wikidata.org/wiki/Q35666","display_name":"Glacier","level":2,"score":0.6506237983703613},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.563930332660675},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.5537776947021484},{"id":"https://openalex.org/C2780021526","wikidata":"https://www.wikidata.org/wiki/Q1542432","display_name":"Greenland ice sheet","level":3,"score":0.5529918670654297},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5248196721076965},{"id":"https://openalex.org/C123750103","wikidata":"https://www.wikidata.org/wiki/Q12599","display_name":"Ice sheet","level":2,"score":0.5091568827629089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4804903566837311},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4644792973995209},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.4300692677497864},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.42793920636177063},{"id":"https://openalex.org/C197435368","wikidata":"https://www.wikidata.org/wiki/Q493109","display_name":"Cryosphere","level":3,"score":0.4129171073436737},{"id":"https://openalex.org/C100970517","wikidata":"https://www.wikidata.org/wiki/Q52107","display_name":"Physical geography","level":1,"score":0.4038563668727875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4026627540588379},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3697790503501892},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.31194695830345154},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.18715128302574158},{"id":"https://openalex.org/C136894858","wikidata":"https://www.wikidata.org/wiki/Q213926","display_name":"Sea ice","level":2,"score":0.16314977407455444},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.1485668420791626},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589132.3629974","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3629974","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3629974","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589132.3629974","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3629974","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3629974","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390100494.pdf","grobid_xml":"https://content.openalex.org/works/W4390100494.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1999809169","https://openalex.org/W2974383887","https://openalex.org/W2985457958","https://openalex.org/W3118807321","https://openalex.org/W4220760059"],"related_works":["https://openalex.org/W1721371904","https://openalex.org/W2955521286","https://openalex.org/W2924911452","https://openalex.org/W3004634341","https://openalex.org/W2995424433","https://openalex.org/W2276037845","https://openalex.org/W598752169","https://openalex.org/W2981524799","https://openalex.org/W3044184688","https://openalex.org/W3137213481"],"abstract_inverted_index":{"Melting":[0],"glaciers":[1],"are":[2,27],"indicators":[3],"of":[4,12,28,56,97,103,111,118],"global":[5],"climate":[6],"change.":[7],"The":[8,63,90],"formation":[9],"and":[10,83,115],"dynamics":[11,114],"supraglacial":[13,57,112],"lakes":[14,40,58,74],"on":[15,35],"the":[16,23,94,109,116],"Greenland's":[17],"ice":[18,36],"sheet,":[19],"which":[20],"appear":[21],"during":[22],"summer":[24],"melt":[25],"season,":[26],"particular":[29],"interest":[30],"due":[31],"to":[32,87,108],"their":[33],"impact":[34],"dynamics.":[37],"Detecting":[38],"these":[39],"is":[41,68],"essential,":[42],"yet":[43],"challenging.":[44],"This":[45,105],"paper":[46],"presents":[47],"a":[48],"comprehensive":[49],"geo-knowledge-informed":[50],"deep":[51,65],"leaning":[52],"workflow":[53],"for":[54,70],"auto-identification":[55],"from":[59,75],"Sentinel-2":[60],"satellite":[61],"images.":[62],"U-Net":[64],"neural":[66],"network":[67],"employed":[69],"pixel-level":[71],"segmentation,":[72],"distinguishing":[73],"other":[76],"features.":[77],"Post-processing":[78],"techniques":[79],"filter":[80],"false":[81],"positives":[82],"incorporate":[84],"geographical":[85],"knowledge":[86],"re-fine":[88],"results.":[89],"experiment":[91],"results":[92],"demonstrate":[93],"superior":[95],"performance":[96],"our":[98],"proposed":[99],"method":[100],"with":[101],"F1-score":[102],"0.78.":[104],"research":[106],"contributes":[107],"understanding":[110],"lake":[113],"development":[117],"robust":[119],"automated":[120],"detection":[121],"methods.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
