{"id":"https://openalex.org/W7152438672","doi":"https://doi.org/10.48550/arxiv.2604.07092","title":"Location Is All You Need: Continuous Spatiotemporal Neural Representations of Earth Observation Data","display_name":"Location Is All You Need: Continuous Spatiotemporal Neural Representations of Earth Observation Data","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152438672","doi":"https://doi.org/10.48550/arxiv.2604.07092"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.07092","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07092","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.07092","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041915439","display_name":"Mojgan Madadikhaljan","orcid":"https://orcid.org/0000-0001-9846-9867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Madadikhaljan, Mojgan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063734590","display_name":"Jonathan Prexl","orcid":"https://orcid.org/0009-0006-2560-5817"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prexl, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116641702","display_name":"Isabelle Wittmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wittmann, Isabelle","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133267542","display_name":"Conrad M Albrecht","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albrecht, Conrad M","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133251745","display_name":"Michael Schmitt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmitt, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.5541999936103821,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.5541999936103821,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.1453000009059906,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.11980000138282776,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6200000047683716},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.579800009727478},{"id":"https://openalex.org/keywords/earth-observation","display_name":"Earth observation","score":0.5608000159263611},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.5587000250816345},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5390999913215637},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5109000205993652},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.44190001487731934},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4104999899864197},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4027999937534332}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7570000290870667},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6200000047683716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.579800009727478},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.5608000159263611},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.5587000250816345},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5023999810218811},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.44190001487731934},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4104999899864197},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4027999937534332},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3718999922275543},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.34610000252723694},{"id":"https://openalex.org/C120938966","wikidata":"https://www.wikidata.org/wiki/Q5275845","display_name":"Digital Earth","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C2987528665","wikidata":"https://www.wikidata.org/wiki/Q854845","display_name":"Earth observation satellite","level":3,"score":0.28679999709129333},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.07092","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07092","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.07092","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07092","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1,50],"work,":[2],"we":[3],"present":[4],"LIANet":[5,42,77,113],"(Location":[6],"Is":[7],"All":[8],"You":[9],"Need":[10],"Network),":[11],"a":[12,25,31,82],"coordinate-based":[13],"neural":[14,34,51],"representation":[15,52],"that":[16,122],"models":[17],"multi-temporal":[18],"spaceborne":[19],"Earth":[20],"observation":[21],"(EO)":[22],"data":[23,95],"for":[24,99,125],"given":[26],"region":[27],"of":[28,94,112,117],"interest":[29],"as":[30,62,81],"continuous":[32],"spatiotemporal":[33],"field.":[35],"Given":[36],"only":[37],"spatial":[38],"and":[39,97,101,120,143],"temporal":[40],"coordinates,":[41],"reconstructs":[43],"the":[44,73,92,110],"corresponding":[45],"satellite":[46,75],"imagery.":[47],"Once":[48],"pretrained,":[49],"can":[53],"be":[54],"adapted":[55],"to":[56,72,79,85,132],"various":[57],"EO":[58],"downstream":[59,126],"tasks,":[60],"such":[61],"semantic":[63],"segmentation":[64],"or":[65,136],"pixel-wise":[66],"regression,":[67],"importantly,":[68],"without":[69],"requiring":[70],"access":[71,96],"original":[74],"data.":[76],"intends":[78],"serve":[80],"user-friendly":[83],"alternative":[84],"Geospatial":[86],"Foundation":[87],"Models":[88],"(GFMs)":[89],"by":[90],"eliminating":[91],"overhead":[93],"preprocessing":[98],"end-users":[100],"enabling":[102],"fine-tuning":[103,123],"solely":[104],"based":[105],"on":[106],"labels.":[107],"We":[108],"demonstrate":[109],"pretraining":[111],"across":[114],"target":[115],"areas":[116],"varying":[118],"sizes":[119],"show":[121],"it":[124],"tasks":[127],"achieves":[128],"competitive":[129],"performance":[130],"compared":[131],"training":[133],"from":[134],"scratch":[135],"using":[137],"established":[138],"GFMs.":[139],"The":[140],"source":[141],"code":[142],"datasets":[144],"are":[145],"publicly":[146],"available":[147],"at":[148],"https://github.com/mojganmadadi/LIANet/tree/v1.0.1.":[149]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-10T00:00:00"}