{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T00:11:54Z","timestamp":1778285514288,"version":"3.51.4"},"reference-count":60,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100006785","name":"Google","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006785","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012542","name":"Sichuan Province Science and Technology Support Program","doi-asserted-by":"publisher","award":["2024YFTX0004"],"award-info":[{"award-number":["2024YFTX0004"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.engappai.2026.114773","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T07:50:33Z","timestamp":1775721033000},"page":"114773","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["A pretrained self-supervised model with lightweight spatial feature distillation for wetland mapping via satellite imagery"],"prefix":"10.1016","volume":"176","author":[{"given":"Bingqian","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3880-2394","authenticated-orcid":false,"given":"Jianhua","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huajun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shixiang","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yipeng","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiongling","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuqiang","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.114773_bib2","author":"Astruc"},{"key":"10.1016\/j.engappai.2026.114773_bib3","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1080\/01431160412331291297","article-title":"GLC2000: a new approach to global land cover mapping from Earth observation data","volume":"26","author":"Bartholom\u00e9","year":"2005","journal-title":"Int. J. Rem. Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib4","doi-asserted-by":"crossref","first-page":"580","DOI":"10.3390\/rs10040580","article-title":"Decision-tree, rule-based, and random forest classification of high-resolution multispectral imagery for wetland mapping and inventory","volume":"10","author":"Berhane","year":"2018","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib5","article-title":"Development of a 10 m daily seamless surface reflectance data cube based on Sentinel-2 constellation for generating the reference true-value products at Wanglang mountain area, China","volume":"13","author":"Bian","year":"2026","journal-title":"Sci. Remote Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib6","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2244672","article-title":"Hyperspectral remote sensing data analysis and future challenges","volume":"1","author":"Bioucas-Dias","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"10.1016\/j.engappai.2026.114773_bib7","series-title":"Computer Vision \u2013 ECCV 2022 Workshops, Lecture Notes in Computer Science","first-page":"205","article-title":"Swin-unet: unet-like pure transformer for medical image segmentation","author":"Cao","year":"2023"},{"key":"10.1016\/j.engappai.2026.114773_bib8","article-title":"Identification of outcropping strata from UAV oblique photogrammetric data using a spatial case-based reasoning model","volume":"103","author":"Chen","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"10.1016\/j.engappai.2026.114773_bib9","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1080\/13658816.2023.2273877","article-title":"A cellular automaton integrating spatial case-based reasoning for predicting local landslide hazards","volume":"38","author":"Chen","year":"2024","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"10.1016\/j.engappai.2026.114773_bib10","first-page":"22243","article-title":"Big self-supervised models are strong semi-supervised learners","volume":"33","author":"Chen","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114773_bib11","series-title":"Improved Baselines with Momentum Contrastive Learning","author":"Chen","year":"2020"},{"key":"10.1016\/j.engappai.2026.114773_bib12","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"801","article-title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","author":"Chen","year":"2018"},{"key":"10.1016\/j.engappai.2026.114773_bib13","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"336","article-title":"Deep feature factorization for concept discovery","author":"Collins","year":"2018"},{"key":"10.1016\/j.engappai.2026.114773_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2024.105012","article-title":"Comparison of fine-tuning strategies for transfer learning in medical image classification","volume":"146","author":"Davila","year":"2024","journal-title":"Image Vis Comput."},{"key":"10.1016\/j.engappai.2026.114773_bib15","first-page":"441","article-title":"Recurrence plots of dynamical systems","volume":"16","author":"Eckmann","year":"1995","journal-title":"World Sci. Ser. Nonlinear Sci. Ser. A"},{"key":"10.1016\/j.engappai.2026.114773_bib16","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1002\/nav.20056","article-title":"On Kuhn's Hungarian method\u2014A tribute from Hungary","volume":"52","author":"Frank","year":"2005","journal-title":"Nav. Res. Logist. NRL"},{"key":"10.1016\/j.engappai.2026.114773_bib17","article-title":"Comparison of optimized object-based RF-DT algorithm and SegNet algorithm for classifying karst wetland vegetation communities using ultra-high spatial resolution UAV data","volume":"104","author":"Fu","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"10.1016\/j.engappai.2026.114773_bib18","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1080\/07038992.2021.1872374","article-title":"Object-based wetland classification using multi-feature combination of ultra-high spatial resolution multispectral images","volume":"46","author":"Geng","year":"2020","journal-title":"Can. J. Rem. Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib19","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.rse.2015.11.015","article-title":"Long-term monitoring of biophysical characteristics of tidal wetlands in the northern gulf of Mexico\u2014A methodological approach using MODIS","volume":"173","author":"Ghosh","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114773_bib20","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.scib.2019.03.002","article-title":"Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Gong","year":"2019","journal-title":"Sci. Bull."},{"key":"10.1016\/j.engappai.2026.114773_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecolind.2021.107559","article-title":"Dynamic simulation of coastal wetlands for Guangdong-Hong Kong-Macao Greater Bay area based on multi-temporal Landsat images and FLUS model","volume":"125","author":"Guo","year":"2021","journal-title":"Ecol. Indic."},{"key":"10.1016\/j.engappai.2026.114773_bib22","doi-asserted-by":"crossref","first-page":"76","DOI":"10.3390\/f12010076","article-title":"Spatial and temporal changes in vegetation in the Ruoergai Region, China","volume":"12","author":"Guo","year":"2021","journal-title":"Forests"},{"key":"10.1016\/j.engappai.2026.114773_bib23","doi-asserted-by":"crossref","first-page":"4190","DOI":"10.3390\/rs12244190","article-title":"Multispectral remote sensing of wetlands in semi-arid and arid areas: a review on applications, challenges and possible future research directions","volume":"12","author":"Gxokwe","year":"2020","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib24","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2021.150139","article-title":"Leveraging Google Earth engine platform to characterize and map small seasonal wetlands in the semi-arid environments of South Africa","volume":"803","author":"Gxokwe","year":"2022","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.engappai.2026.114773_bib25","series-title":"Model-Agnostic Explainability for Visual Search","author":"Hamilton","year":"2021"},{"key":"10.1016\/j.engappai.2026.114773_bib26","series-title":"Unsupervised Semantic Segmentation by Distilling Feature Correspondences","author":"Hamilton","year":"2022"},{"key":"10.1016\/j.engappai.2026.114773_bib27","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.engappai.2026.114773_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2021.112757","article-title":"Utilizing unsupervised learning, multi-view imaging, and CNN-based attention facilitates cost-effective wetland mapping","volume":"267","author":"Hu","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114773_bib29","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.isprsjprs.2023.07.009","article-title":"Cross-scene wetland mapping on hyperspectral remote sensing images using adversarial domain adaptation network","volume":"203","author":"Huang","year":"2023","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib30","article-title":"A deep learning framework based on generative adversarial networks and vision transformer for complex wetland classification using limited training samples","volume":"115","author":"Jamali","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"10.1016\/j.engappai.2026.114773_bib31","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"9865","article-title":"Invariant information clustering for unsupervised image classification and segmentation","author":"Ji","year":"2019"},{"key":"10.1016\/j.engappai.2026.114773_bib32","author":"Jocher"},{"key":"10.1016\/j.engappai.2026.114773_bib33","series-title":"Ultralytics YOLO","author":"Jocher","year":"2023"},{"key":"10.1016\/j.engappai.2026.114773_bib34","series-title":"Adam: a Method for Stochastic Optimization","author":"Kingma","year":"2014"},{"key":"10.1016\/j.engappai.2026.114773_bib35","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"4015","article-title":"Segment anything","author":"Kirillov","year":"2023"},{"key":"10.1016\/j.engappai.2026.114773_bib36","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2024.175058","article-title":"Advancements in mapping areas suitable for wetland habitats across the conterminous United States","volume":"949","author":"Krohmer","year":"2024","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.engappai.2026.114773_bib37","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"LeCun","year":"1998","journal-title":"Proc. IEEE"},{"key":"10.1016\/j.engappai.2026.114773_bib38","first-page":"1","article-title":"Mapping the world's inland surface waters: an update to the Global Lakes and Wetlands Database (GLWD v2)","volume":"2024","author":"Lehner","year":"2024","journal-title":"Earth Syst. Sci. Data Discuss."},{"key":"10.1016\/j.engappai.2026.114773_bib39","series-title":"Encoding Temporal Markov Dynamics in Graph for Time Series Visualization","author":"Liu","year":"2016"},{"key":"10.1016\/j.engappai.2026.114773_bib40","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"10012","article-title":"Swin transformer: hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.engappai.2026.114773_bib41","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2023.113969","article-title":"Mapping multi-decadal wetland loss: comparative analysis of linear and nonlinear spatiotemporal characterization","volume":"302","author":"Mattson","year":"2024","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114773_bib42","article-title":"A comparative performance analysis of popular deep learning models and segment anything model (SAM) for river water segmentation in close-range remote sensing imagery","volume":"99","author":"Moghimi","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.114773_bib43","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1080\/0035919X.2024.2322946","article-title":"A systematic review on remote sensing of wetland environments","volume":"79","author":"Mupepi","year":"2024","journal-title":"Trans. Roy. Soc. S. Afr."},{"key":"10.1016\/j.engappai.2026.114773_bib44","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2024.175734","article-title":"Microbiology of wetlands and the carbon cycle in coastal wetland mediated by microorganisms","author":"Mustafa","year":"2024","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.engappai.2026.114773_bib45","doi-asserted-by":"crossref","first-page":"27073","DOI":"10.1109\/ACCESS.2024.3365356","article-title":"A novel transfer learning approach for detection of pomegranates growth stages","volume":"12","author":"Naseer","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.114773_bib46","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1109\/TAI.2021.3054609","article-title":"A decade survey of transfer learning (2010\u20132020)","volume":"1","author":"Niu","year":"2020","journal-title":"IEEE Trans. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114773_bib47","series-title":"Representation Learning with Contrastive Predictive Coding","author":"Oord","year":"2019"},{"key":"10.1016\/j.engappai.2026.114773_bib48","series-title":"Dinov2: Learning Robust Visual Features Without Supervision","author":"Oquab","year":"2023"},{"key":"10.1016\/j.engappai.2026.114773_bib49","series-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","first-page":"23947","article-title":"TSAM: temporal SAM augmented with multimodal prompts for referring audio-visual segmentation","author":"Radman","year":"2025"},{"key":"10.1016\/j.engappai.2026.114773_bib50","article-title":"Rapid expansion of coastal aquaculture ponds in China from landsat observations during 1984\u20132016","volume":"82","author":"Ren","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"10.1016\/j.engappai.2026.114773_bib51","author":"Sim\u00e9oni"},{"key":"10.1016\/j.engappai.2026.114773_bib52","doi-asserted-by":"crossref","DOI":"10.3389\/frsen.2025.1531097","article-title":"Choosing blocks for spatial cross-validation: lessons from a marine remote sensing case study","volume":"6","author":"Stock","year":"2025","journal-title":"Front. Remote Sens."},{"key":"10.1016\/j.engappai.2026.114773_bib53","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2022.101557","article-title":"Identifying wetland areas in historical maps using deep convolutional neural networks","volume":"68","author":"St\u00e5hl","year":"2022","journal-title":"Ecol. Inform."},{"key":"10.1016\/j.engappai.2026.114773_bib55","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114773_bib56","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s10661-013-3360-7","article-title":"An object-based image analysis approach for aquaculture ponds precise mapping and monitoring: a case study of Tam Giang-Cau Hai Lagoon, Vietnam","volume":"186","author":"Virdis","year":"2014","journal-title":"Environ. Monit. Assess."},{"key":"10.1016\/j.engappai.2026.114773_bib57","article-title":"A spectral and spatial transformer for hyperspectral remote sensing image super-resolution","volume":"17","author":"Wang","year":"2024","journal-title":"Int. J. Digit. Earth"},{"key":"10.1016\/j.engappai.2026.114773_bib58","series-title":"Imaging Time-Series to Improve Classification and Imputation","author":"Wang","year":"2015"},{"key":"10.1016\/j.engappai.2026.114773_bib59","article-title":"How transferable are features in deep neural networks?","volume":"27","author":"Yosinski","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114773_bib60","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2024.142496","article-title":"Variable climatic conditions dominate decreased wetland vulnerability on the Qinghai\u2013Tibet Plateau: insights from the ecosystem pattern-process-function framework","volume":"458","author":"Zhao","year":"2024","journal-title":"J. Clean. Prod."},{"key":"10.1016\/j.engappai.2026.114773_bib61","series-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Lecture Notes in Computer Science","first-page":"3","article-title":"UNet++: a nested U-Net architecture for medical image segmentation","author":"Zhou","year":"2018"},{"key":"10.1016\/j.engappai.2026.114773_bib62","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/JPROC.2020.3004555","article-title":"A comprehensive survey on transfer learning","volume":"109","author":"Zhuang","year":"2020","journal-title":"Proc. IEEE"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626010559?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626010559?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T23:26:16Z","timestamp":1778282776000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626010559"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":60,"alternative-id":["S0952197626010559"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114773","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A pretrained self-supervised model with lightweight spatial feature distillation for wetland mapping via satellite imagery","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114773","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":"114773"}}