{"id":"https://openalex.org/W7213253152","doi":"https://doi.org/10.48550/arxiv.2609.13453","title":"A Machine Learning API for Earth Observation Data Cubes Based on openEO","display_name":"A Machine Learning API for Earth Observation Data Cubes Based on openEO","publication_year":2026,"publication_date":"2026-09-11","ids":{"openalex":"https://openalex.org/W7213253152","doi":"https://doi.org/10.48550/arxiv.2609.13453"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.13453","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.13453","pdf_url":"https://arxiv.org/pdf/2609.13453","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.13453","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039871149","display_name":"Brian Pondi","orcid":"https://orcid.org/0009-0008-0367-1690","observed_orcids":["https://orcid.org/0009-0008-0367-1690"]},"institutions":[{"id":"https://openalex.org/I22465464","display_name":"University of M\u00fcnster","ror":"https://ror.org/00pd74e08","country_code":"DE","type":"education","lineage":["https://openalex.org/I22465464"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Pondi, Brian","raw_affiliation_strings":["Institute for Geoinformatics , University of M\u00fcnster , Heisenbergstr. 2 , M\u00fcnster , 48149 , North-Rhine Westphalia , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Geoinformatics , University of M\u00fcnster , Heisenbergstr. 2 , M\u00fcnster , 48149 , North-Rhine Westphalia , Germany","institution_ids":["https://openalex.org/I22465464"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077999654","display_name":"J. Hurst","orcid":"https://orcid.org/0009-0000-0004-0051","observed_orcids":["https://orcid.org/0009-0000-0004-0051"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hurst, Jonas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5151736624","display_name":"Rolf Simoes","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I44202434","display_name":"Funda\u00e7\u00e3o Getulio Vargas","ror":"https://ror.org/01evzkn27","country_code":"BR","type":"education","lineage":["https://openalex.org/I44202434"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Simoes, Rolf","raw_affiliation_strings":["FGV Agro -Center for Agribusiness Studies , Funda\u00e7\u00e3o Getulio Vargas , Av. Paulista , 542 , S\u00e3o Paulo , 01310-000 , S\u00e3o Paulo , Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FGV Agro -Center for Agribusiness Studies , Funda\u00e7\u00e3o Getulio Vargas , Av. Paulista , 542 , S\u00e3o Paulo , 01310-000 , S\u00e3o Paulo , Brazil","institution_ids":["https://openalex.org/I44202434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5151708320","display_name":"Jonas Starke","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Starke, Jonas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068355168","display_name":"Marius Appel","orcid":"https://orcid.org/0000-0001-5281-3896","observed_orcids":["https://orcid.org/0000-0001-5281-3896"]},"institutions":[{"id":"https://openalex.org/I4210141069","display_name":"Bochum University of Applied Sciences","ror":"https://ror.org/04x02q560","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210141069"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Appel, Marius","raw_affiliation_strings":["Bochum University of Applied Sciences , Am Hochschulcampus 1 , Bochum , 44801 , North-Rhine Westphalia , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bochum University of Applied Sciences , Am Hochschulcampus 1 , Bochum , 44801 , North-Rhine Westphalia , Germany","institution_ids":["https://openalex.org/I4210141069"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054607061","display_name":"Edzer J Pebesma","orcid":"https://orcid.org/0000-0001-8049-7069","observed_orcids":["https://orcid.org/0000-0001-8049-7069"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pebesma, Edzer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.510699987411499,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.510699987411499,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.0982000008225441,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.06549999862909317,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/openeo","display_name":"openEO","score":0.8690000176429749},{"id":"https://openalex.org/keywords/earth-observation-data-cubes","display_name":"Earth observation data cubes","score":0.9010000228881836},{"id":"https://openalex.org/keywords/reproducibility","display_name":"reproducibility","score":0.7080000042915344},{"id":"https://openalex.org/keywords/model-transportability","display_name":"model portability","score":0.6010000109672546},{"id":"https://openalex.org/keywords/crop-classification","display_name":"crop classification","score":0.8560000061988831}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8205000162124634},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7249000072479248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5837000012397766},{"id":"https://openalex.org/C63000827","wikidata":"https://www.wikidata.org/wiki/Q3080428","display_name":"Software portability","level":2,"score":0.5730999708175659},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5526999831199646},{"id":"https://openalex.org/C52723943","wikidata":"https://www.wikidata.org/wiki/Q1127410","display_name":"Serialization","level":2,"score":0.5088000297546387},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.4921000003814697},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.46799999475479126},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.4666000008583069},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3280999958515167},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.32519999146461487},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C2780416260","wikidata":"https://www.wikidata.org/wiki/Q2063","display_name":"JSON","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C99613125","wikidata":"https://www.wikidata.org/wiki/Q165194","display_name":"Application programming interface","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C56666940","wikidata":"https://www.wikidata.org/wiki/Q788790","display_name":"Documentation","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C145644426","wikidata":"https://www.wikidata.org/wiki/Q169411","display_name":"Unified Modeling Language","level":3,"score":0.25450000166893005},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.13453","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.13453","pdf_url":"https://arxiv.org/pdf/2609.13453","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.13453","doi":"https://doi.org/10.48550/arxiv.2609.13453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.13453","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.13453","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.13453","pdf_url":"https://arxiv.org/pdf/2609.13453","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1923411691","display_name":"Open-Earth-Monitor Cyberinfrastructure","funder_award_id":"101059548","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G3406993767","display_name":"Earth Observation & Weather Data Federation with AI Embeddings","funder_award_id":"101131841","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4184880244","display_name":null,"funder_award_id":"101058386","funder_id":"https://openalex.org/F4320334322","funder_display_name":"HORIZON EUROPE Framework Programme"},{"id":"https://openalex.org/G5782315299","display_name":null,"funder_award_id":"101131841","funder_id":"https://openalex.org/F4320334322","funder_display_name":"HORIZON EUROPE Framework Programme"},{"id":"https://openalex.org/G714015773","display_name":null,"funder_award_id":"101059548","funder_id":"https://openalex.org/F4320334322","funder_display_name":"HORIZON EUROPE Framework Programme"},{"id":"https://openalex.org/G7842645033","display_name":"An interdisciplinary Digital Twin Engine for science","funder_award_id":"101058386","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334322","display_name":"HORIZON EUROPE Framework Programme","ror":null},{"id":"https://openalex.org/F4320335238","display_name":"Staatssekretariat f\u00fcr Bildung, Forschung und Innovation","ror":"https://ror.org/01kw63t33"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7213253152.pdf","grobid_xml":"https://content.openalex.org/works/W7213253152.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1831050183","https://openalex.org/W2157675604","https://openalex.org/W2164777277","https://openalex.org/W2168481151","https://openalex.org/W2261059368","https://openalex.org/W2396656711","https://openalex.org/W2604239613","https://openalex.org/W2764034829","https://openalex.org/W2793927960","https://openalex.org/W2900059511","https://openalex.org/W2900573306","https://openalex.org/W2944951172","https://openalex.org/W2953621601","https://openalex.org/W2955450471","https://openalex.org/W2979826702","https://openalex.org/W2997591727","https://openalex.org/W2998993395","https://openalex.org/W3021798522","https://openalex.org/W3036963153","https://openalex.org/W3110052155","https://openalex.org/W3125914437","https://openalex.org/W3139263896","https://openalex.org/W3173608877","https://openalex.org/W4210284152","https://openalex.org/W4239510810","https://openalex.org/W4391931626","https://openalex.org/W4395055639","https://openalex.org/W4400139198","https://openalex.org/W4403636704","https://openalex.org/W4407051882","https://openalex.org/W4410551352","https://openalex.org/W4411949946","https://openalex.org/W4413267746","https://openalex.org/W4414691205","https://openalex.org/W4416052645","https://openalex.org/W4417248811"],"related_works":["https://openalex.org/W6949321879","https://openalex.org/W3139263896","https://openalex.org/W3177168964","https://openalex.org/W7135221981","https://openalex.org/W6892733958","https://openalex.org/W6930785444","https://openalex.org/W7223093368","https://openalex.org/W4391931626","https://openalex.org/W7042356137","https://openalex.org/W4412720684"],"abstract_inverted_index":{"Earth":[0],"Observation":[1],"(EO)":[2],"data":[3,9,49,241],"are":[4,31],"increasingly":[5],"organized":[6],"as":[7,92,97,99],"spatio-temporal":[8],"cubes,":[10],"while":[11],"machine":[12],"learning":[13,101,164],"(ML)":[14],"methods":[15],"operate":[16],"on":[17,165,174,239],"tabular":[18],"feature":[19],"matrices":[20],"or":[21,35],"structured":[22,72],"tensor":[23],"inputs.":[24],"This":[25],"mismatch":[26],"forces":[27],"platform-specific":[28],"transformations":[29],"that":[30,182],"difficult":[32],"to":[33,146],"reproduce":[34],"transfer":[36],"across":[37,53,127,243],"cloud":[38,244],"infrastructures.":[39],"The":[40,178,228],"openEO":[41,71],"specification":[42,69,229],"provides":[43],"a":[44,58,66,175],"unified":[45],"interface":[46],"for":[47,61,70,103],"EO":[48,240],"access":[50],"and":[51,84,95,105,114,123,149,152,155,168,192,205,234],"processing":[52],"heterogeneous":[54],"backends,":[55],"but":[56],"lacks":[57],"standardized":[59],"approach":[60],"ML":[62,68,237],"integration.":[63],"We":[64],"propose":[65],"process-level":[67],"into":[73],"three":[74],"stages:":[75],"model":[76,78,85,116,170],"initialization,":[77],"actions":[79],"(training,":[80],"tuning,":[81],"inference,":[82,171],"validation),":[83],"management.":[86],"It":[87],"supports":[88],"classical":[89],"algorithms":[90],"such":[91],"Random":[93],"Forest":[94],"SVM,":[96],"well":[98],"deep":[100,163],"architectures":[102],"time-series":[104],"spatial":[106],"patch-based":[107],"modeling,":[108],"including":[109],"TempCNN,":[110],"Temporal":[111],"Attention":[112],"Encoders,":[113],"foundation":[115,169],"inference.":[117],"Three":[118],"prototype":[119],"implementations":[120],"in":[121],"R":[122,148],"Python":[124,150],"demonstrate":[125,162],"feasibility":[126],"diverse":[128],"technology":[129],"stacks.":[130],"A":[131],"crop":[132],"type":[133],"mapping":[134],"use":[135,160],"case":[136],"demonstrates":[137],"cross-backend":[138,184],"interoperability":[139],"by":[140],"submitting":[141],"an":[142],"identical":[143],"process":[144,197],"graph":[145],"independent":[147],"backends":[151],"comparing":[153],"predictions":[154],"evaluation":[156],"metrics.":[157],"Two":[158],"further":[159],"cases":[161],"time":[166],"series":[167],"each":[172],"executed":[173],"dedicated":[176],"backend.":[177],"prototypes":[179],"reveal,":[180],"however,":[181],"full":[183],"portability":[185],"requires":[186],"deeper":[187],"harmonization":[188],"of":[189,236],"serialization":[190],"formats":[191],"execution":[193],"semantics":[194],"than":[195],"the":[196,209,223,231],"level":[198],"alone":[199],"can":[200],"enforce;":[201],"backend":[202,219],"library":[203],"versions":[204],"preprocessing":[206],"conventions":[207],"outside":[208],"specification's":[210],"boundary":[211],"also":[212],"affect":[213],"reproducibility.":[214],"Addressing":[215],"both":[216],"through":[217],"explicit":[218],"conformance":[220],"profiles":[221],"represents":[222],"most":[224],"important":[225],"near-term":[226],"direction.":[227],"advances":[230],"reproducibility,":[232],"portability,":[233],"accessibility":[235],"workflows":[238],"cubes":[242],"platforms.":[245]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-16T00:00:00"}