{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T17:18:20Z","timestamp":1783531100166,"version":"3.55.0"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004004","name":"Universit\u00e0 degli Studi di Trento","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004004","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62376214"],"award-info":[{"award-number":["62376214"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92270117"],"award-info":[{"award-number":["92270117"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.eswa.2026.133390","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:26:00Z","timestamp":1782318360000},"page":"133390","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PD","title":["A spectral-spatial alignment and information disentanglement network for hyperspectral and LiDAR data fusion classification"],"prefix":"10.1016","volume":"331","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3318-8137","authenticated-orcid":false,"given":"Wenqing","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7081-6230","authenticated-orcid":false,"given":"Pingping","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6618-1380","authenticated-orcid":false,"given":"Han","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.133390_bib0001","first-page":"1","article-title":"Deep symmetric fusion transformer for multimodal remote sensing data classification","volume":"62","author":"Chang","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"8","key":"10.1016\/j.eswa.2026.133390_bib0002","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1109\/LGRS.2017.2704625","article-title":"Deep fusion of remote sensing data for accurate classification","volume":"14","author":"Chen","year":"2017","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"issue":"6","key":"10.1016\/j.eswa.2026.133390_bib0003","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1109\/JSTARS.2014.2305441","article-title":"Hyperspectral and LiDAR data fusion: Outcome of the 2013 GRSS data fusion contest","volume":"7","author":"Debes","year":"2014","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125132","article-title":"Multi-level interactive fusion network based on adversarial learning for fusion classification of hyperspectral and LiDAR data","volume":"257","author":"Fan","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133390_bib0005","first-page":"1","article-title":"Fractional fourier-enhanced fusion network based on pareto optimization for hyperspectral and LiDAR data classification","volume":"63","author":"Feng","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0006","first-page":"1","article-title":"Fractional-domain information-enhanced hyperspherical prototype learning method for hyperspectral image open-set classification","volume":"63","author":"Feng","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111190","article-title":"S2EFT: Spectral-spatial-elevation fusion transformer for hyperspectral image and LiDAR classification","volume":"283","author":"Feng","year":"2024","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.eswa.2026.133390_bib0008","first-page":"1","article-title":"MSFMamba: Multiscale feature fusion state space model for multisource remote sensing image classification","volume":"63","author":"Gao","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0009","first-page":"1","article-title":"AMSSE-Net: Adaptive multiscale spatial-spectral enhancement network for classification of hyperspectral and LiDAR data","volume":"61","author":"Gao","year":"2023","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"6","key":"10.1016\/j.eswa.2026.133390_bib0010","doi-asserted-by":"crossref","first-page":"3011","DOI":"10.1109\/JSTARS.2016.2634863","article-title":"Hyperspectral and LiDAR data fusion using extinction profiles and deep convolutional neural network","volume":"10","author":"Ghamisi","year":"2017","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_sbref0011","first-page":"1","article-title":"Representative spectral correlation network for multisource remote sensing image classification","volume":"64","author":"Gong","year":"2026","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"7","key":"10.1016\/j.eswa.2026.133390_bib0012","doi-asserted-by":"crossref","first-page":"4939","DOI":"10.1109\/TGRS.2020.2969024","article-title":"Classification of hyperspectral and LiDAR data using coupled CNNs","volume":"58","author":"Hang","year":"2020","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0013","first-page":"1","article-title":"Foundation model-based multimodal remote sensing data classification","volume":"62","author":"He","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0014","first-page":"1","article-title":"Multilevel attention dynamic-scale network for HSI and LiDAR data fusion classification","volume":"62","author":"He","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0015","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.isprsjprs.2020.06.014","article-title":"X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data","volume":"167","author":"Hong","year":"2020","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.131443","article-title":"A dual-domain mutual compensation network for multi-modality image fusion","volume":"656","author":"Hu","year":"2025","journal-title":"Neurocomputing"},{"issue":"4","key":"10.1016\/j.eswa.2026.133390_bib0017","doi-asserted-by":"crossref","first-page":"7357","DOI":"10.1109\/TNNLS.2024.3406735","article-title":"Global clue-guided cross-memory quaternion transformer network for multisource remote sensing data classification","volume":"36","author":"Hu","year":"2025","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.eswa.2026.133390_bib0018","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2025.3628483","article-title":"Heterogeneous contrastive graph fusion network for classification of hyperspectral and LiDAR data","volume":"63","author":"Jing","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0019","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.arcontrol.2021.03.003","article-title":"A comprehensive review of hyperspectral data fusion with LiDAR and SAR data","volume":"51","author":"Kahraman","year":"2021","journal-title":"Annual Reviews in Control"},{"issue":"2","key":"10.1016\/j.eswa.2026.133390_bib0020","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1109\/TNNLS.2020.3028945","article-title":"A3 CLNN: Spatial, spectral and multiscale attention ConvLSTM neural network for multisource remote sensing data classification","volume":"33","author":"Li","year":"2022","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.eswa.2026.133390_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.jag.2022.102926","article-title":"Deep learning in multimodal remote sensing data fusion: A comprehensive review","volume":"112","author":"Li","year":"2022","journal-title":"International Journal of Applied Earth Observation and Geoinformation"},{"key":"10.1016\/j.eswa.2026.133390_bib0022","first-page":"1","article-title":"CMFNet: Cross mamba fusion network for hyperspectral and LiDAR data classification","volume":"63","author":"Li","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"3","key":"10.1016\/j.eswa.2026.133390_bib0023","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1109\/LGRS.2014.2350263","article-title":"Generalized graph-based fusion of hyperspectral and LiDAR data using morphological features","volume":"12","author":"Liao","year":"2015","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"issue":"2","key":"10.1016\/j.eswa.2026.133390_bib0024","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1109\/TGRS.2017.2758922","article-title":"Remote sensing image classification with large-scale Gaussian processes","volume":"56","author":"Morales-\u00c1lvarez","year":"2018","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"10","key":"10.1016\/j.eswa.2026.133390_bib0025","doi-asserted-by":"crossref","first-page":"1074","DOI":"10.1080\/2150704X.2024.2399864","article-title":"Classification of hyperspectral and LiDAR data by transformer-based enhancement","volume":"15","author":"Pan","year":"2024","journal-title":"Remote Sensing Letters"},{"key":"10.1016\/j.eswa.2026.133390_bib0026","first-page":"1","article-title":"Collaborative classification of hyperspectral and LiDAR data based on dynamic multiple fractional Fourier domains fusion","volume":"63","author":"Qin","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"7","key":"10.1016\/j.eswa.2026.133390_bib0027","doi-asserted-by":"crossref","first-page":"3997","DOI":"10.1109\/TGRS.2017.2686450","article-title":"Hyperspectral and LiDAR fusion using extinction profiles and total variation component analysis","volume":"55","author":"Rasti","year":"2017","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0028","first-page":"1","article-title":"Multimodal fusion transformer for remote sensing image classification","volume":"61","author":"Roy","year":"2023","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0029","first-page":"1","article-title":"TBi-Mamba: Rethinking joint classification of hyperspectral and LiDAR data with bidirectional mamba","volume":"63","author":"Shi","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0030","first-page":"1","article-title":"Joint classification of hyperspectral and LiDAR data using height information guided hierarchical fusion-and-separation network","volume":"62","author":"Song","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.133390_bib0031","doi-asserted-by":"crossref","first-page":"5396","DOI":"10.1109\/TIP.2020.2983560","article-title":"Multi-granularity canonical appearance pooling for remote sensing scene classification","volume":"29","author":"Wang","year":"2020","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.133390_bib0032","first-page":"1","article-title":"Dual-branch feature fusion network based cross-modal enhanced CNN and transformer for hyperspectral and LiDAR classification","volume":"21","author":"Wang","year":"2024","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"10.1016\/j.eswa.2026.133390_bib0033","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2021.12.008","article-title":"Multi-attentive hierarchical dense fusion net for fusion classification of hyperspectral and LiDAR data","volume":"82","author":"Wang","year":"2022","journal-title":"Information Fusion"},{"issue":"5","key":"10.1016\/j.eswa.2026.133390_bib0034","doi-asserted-by":"crossref","first-page":"4801","DOI":"10.1109\/TCSVT.2025.3525734","article-title":"S3F2Net: Spatial-spectral-structural feature fusion network for hyperspectral image and LiDAR data classification","volume":"35","author":"Wang","year":"2025","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.eswa.2026.133390_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128110","article-title":"Pseudo-label generation guided semi-supervised network for hyperspectral image and LiDAR data classification","volume":"286","author":"Wang","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133390_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113972","article-title":"Domain adaptation network based on multi-level feature alignment constraints for cross scene hyperspectral image classification","volume":"325","author":"Wu","year":"2025","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.eswa.2026.133390_bib0037","first-page":"1","article-title":"LiDAR-guided cross-attention fusion for hyperspectral band selection and image classification","volume":"62","author":"Yang","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"1","key":"10.1016\/j.eswa.2026.133390_bib0038","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TCYB.2018.2864670","article-title":"Feature extraction for classification of hyperspectral and LiDAR data using patch- to-patch CNN","volume":"50","author":"Zhang","year":"2020","journal-title":"IEEE Transactions on Cybernetics"},{"key":"10.1016\/j.eswa.2026.133390_sbref0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2025.103649","article-title":"E-Mamba: Efficient mamba network for hyperspectral and LiDAR joint classification","volume":"126","author":"Zhang","year":"2026","journal-title":"Information Fusion"},{"key":"10.1016\/j.eswa.2026.133390_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125145","article-title":"A cross-modal feature aggregation and enhancement network for hyperspectral and LiDAR joint classification","volume":"258","author":"Zhang","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133390_bib0041","first-page":"1","article-title":"Joint classification of hyperspectral and LiDAR data using a hierarchical CNN and transformer","volume":"61","author":"Zhao","year":"2023","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"10","key":"10.1016\/j.eswa.2026.133390_bib0042","doi-asserted-by":"crossref","first-page":"7355","DOI":"10.1109\/TGRS.2020.2982064","article-title":"Joint classification of hyperspectral and LiDAR data using hierarchical random walk and deep CNN architecture","volume":"58","author":"Zhao","year":"2020","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426022992?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426022992?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T16:42:43Z","timestamp":1783528963000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426022992"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":42,"alternative-id":["S0957417426022992"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.133390","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A spectral-spatial alignment and information disentanglement network for hyperspectral and LiDAR data fusion classification","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.133390","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"133390"}}