{"id":"https://openalex.org/W7160639636","doi":"https://doi.org/10.48550/arxiv.2605.05549","title":"A Novel Graph-Regulated Disentangling Mamba Model with Sparse Tokens for Enhanced Tree Species Classification from MODIS Time Series","display_name":"A Novel Graph-Regulated Disentangling Mamba Model with Sparse Tokens for Enhanced Tree Species Classification from MODIS Time Series","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160639636","doi":"https://doi.org/10.48550/arxiv.2605.05549"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05549","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05549","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":"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.05549","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5118889303","display_name":"Motasem Alkayid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alkayid, Motasem","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135673515","display_name":"Zhengsen Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zhengsen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080506977","display_name":"Saeid Taleghanidoozdoozan","orcid":"https://orcid.org/0000-0002-9586-0016"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taleghanidoozdoozan, Saeid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135667546","display_name":"Yimin Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yimin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123640805","display_name":"Megan Greenwood","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Greenwood, Megan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120031503","display_name":"Quinn Ledingham","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ledingham, Quinn","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135672109","display_name":"Zack Dewis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dewis, Zack","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118889304","display_name":"Mabel Heffring","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heffring, Mabel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135647709","display_name":"Naser El-Sheimy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"El-Sheimy, Naser","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135653517","display_name":"Lincoln Linlin Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Lincoln Linlin","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/T10111","display_name":"Remote Sensing in Agriculture","score":0.7972999811172485,"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":0.7972999811172485,"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":0.09880000352859497,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.052799999713897705,"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/context","display_name":"Context (archaeology)","score":0.6028000116348267},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.576200008392334},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5192000269889832},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4848000109195709},{"id":"https://openalex.org/keywords/moderate-resolution-imaging-spectroradiometer","display_name":"Moderate-resolution imaging spectroradiometer","score":0.4555000066757202},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.38850000500679016},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.3668000102043152},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.35690000653266907}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6028000116348267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5873000025749207},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.576200008392334},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5192000269889832},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4618000090122223},{"id":"https://openalex.org/C2777007095","wikidata":"https://www.wikidata.org/wiki/Q676840","display_name":"Moderate-resolution imaging spectroradiometer","level":3,"score":0.4555000066757202},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3621000051498413},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.27309998869895935},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.25429999828338623},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05549","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05549","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.05549","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05549","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":"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"},"sustainable_development_goals":[{"score":0.6094812154769897,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Although":[0],"tree":[1,35,68],"species":[2,69],"classification":[3,199],"from":[4],"Moderate":[5],"Resolution":[6],"Imaging":[7],"Spectroradiometer":[8],"(MODIS)":[9],"time":[10,131],"series":[11],"data":[12,174],"is":[13,21],"critical":[14],"for":[15,66,106,118],"supporting":[16],"various":[17],"environmental":[18],"applications,":[19],"it":[20],"a":[22,58,84,112],"challenging":[23],"task":[24],"due":[25],"to":[26,77,99,135,156],"several":[27],"key":[28],"difficulties:":[29],"the":[30,42,72,101,151,159],"subtle":[31,139],"signature":[32],"differences":[33],"among":[34,94],"species,":[36],"strong":[37],"spatial-spectral-temporal":[38,103],"information":[39,104],"coupling,":[40],"and":[41,125,138,181,191],"difficulty":[43],"of":[44,154,187],"modeling":[45],"large-scale":[46,79,171],"topological":[47,91],"context":[48,80],"information.":[49],"To":[50],"better":[51,157],"address":[52,158],"these":[53],"challenges,":[54],"this":[55],"paper":[56],"presents":[57],"novel":[59,113,144],"Graph-regulated":[60],"Disentangled":[61],"Sparse":[62],"Mamba":[63,115,166],"model":[64],"(GDS-Mamba)":[65],"enhanced":[67],"classification,":[70],"with":[71],"following":[73],"contributions.":[74],"(1)":[75],"First,":[76],"improve":[78,136],"modeling,":[81],"we":[82,110,142],"design":[83,143],"mini-batch":[85],"graph-regulated":[86],"approach":[87],"that":[88,148,163],"explicitly":[89],"explores":[90],"correlation":[92,160],"effects":[93],"input":[95],"images.":[96],"(2)":[97],"Second,":[98],"disentangle":[100],"high-dimensional":[102],"coupling":[105],"improved":[107],"feature":[108,140],"extraction,":[109],"propose":[111],"disentangling":[114],"architecture":[116],"tailored":[117],"capturing":[119],"independent":[120],"spatial":[121],"patterns,":[122],"spectral":[123],"signatures,":[124],"temporal":[126],"phenology":[127],"behaviors":[128],"in":[129,189,193],"MODIS":[130],"series.":[132],"(3)":[133],"Third,":[134],"efficiency":[137],"learning,":[141],"sparse":[145],"token":[146],"approaches":[147],"adaptively":[149],"learn":[150],"optimum":[152],"subset":[153],"tokens":[155],"decay":[161],"problem":[162],"bottlenecks":[164],"standard":[165],"models.":[167,200],"Extensive":[168],"experiments":[169],"using":[170],"annual":[172],"MOD13Q1":[173],"across":[175],"two":[176],"Canadian":[177],"provinces":[178],"(i.e.,":[179],"Alberta":[180,190],"Saskatchewan)":[182],"achieved":[183],"an":[184],"overall":[185],"accuracy":[186],"93.94\\%":[188],"80.19\\%":[192],"cross-provincial":[194],"evaluations,":[195],"outperforming":[196],"twelve":[197],"state-of-the-art":[198]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-09T00:00:00"}