{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T22:38:49Z","timestamp":1769121529106,"version":"3.49.0"},"reference-count":66,"publisher":"Informa UK Limited","issue":"2","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42471467"],"award-info":[{"award-number":["42471467"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Geographical Information Science"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1080\/13658816.2025.2526041","type":"journal-article","created":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T02:38:33Z","timestamp":1751423913000},"page":"414-438","update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":0,"title":["Scalable spatio-temporal autoregressive modeling by designing equivalent graph convolutional neural networks"],"prefix":"10.1080","volume":"40","author":[{"given":"Hang","family":"Zhang","sequence":"first","affiliation":[{"name":"Faculty of Geographical Science and Engineering, Henan University","place":["Zhengzhou, China"]},{"name":"Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University","place":["Kaifeng, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanpeng","family":"Dong","sequence":"additional","affiliation":[{"name":"Faculty of Geographical Science and Engineering, Henan University","place":["Zhengzhou, China"]},{"name":"Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University","place":["Kaifeng, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"301","published-online":{"date-parts":[[2025,7]]},"reference":[{"key":"e_1_3_5_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-015-7799-1"},{"key":"e_1_3_5_3_1","doi-asserted-by":"publisher","DOI":"10.1177\/0160017602250972"},{"key":"e_1_3_5_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10109-023-00411-2"},{"key":"e_1_3_5_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/gean.12311"},{"key":"e_1_3_5_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610926.2017.1301476"},{"key":"e_1_3_5_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.regsciurbeco.2019.01.006"},{"key":"e_1_3_5_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/0199245282.001.0001"},{"key":"e_1_3_5_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/restud\/rdad089"},{"key":"e_1_3_5_10_1","doi-asserted-by":"publisher","DOI":"10.1201\/b17115"},{"issue":"4","key":"e_1_3_5_11_1","first-page":"43","article-title":"Demystifying parallel and distributed deep learning: an in-depth concurrency analysis","volume":"52","author":"Ben-Nun T.","year":"2019","unstructured":"Ben-Nun, T., and Hoefler, T., 2019. Demystifying parallel and distributed deep learning: an in-depth concurrency analysis. ACM Computing Surveys, 52 (4), 43.","journal-title":"ACM Computing Surveys"},{"key":"e_1_3_5_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/gean.12008"},{"key":"e_1_3_5_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"e_1_3_5_14_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312"},{"key":"e_1_3_5_15_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-economics-080614-115430"},{"key":"e_1_3_5_16_1","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.add3726"},{"key":"e_1_3_5_17_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1017031108"},{"key":"e_1_3_5_18_1","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2024.2426067"},{"key":"e_1_3_5_19_1","volume-title":"Statistics for spatio-temporal data","author":"Cressie N.","year":"2011","unstructured":"Cressie, N., and Wikle, C.K., 2011. Statistics for spatio-temporal data. Hoboken, NJ: John Wiley & Sons."},{"key":"e_1_3_5_20_1","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2022.2100892"},{"key":"e_1_3_5_21_1","unstructured":"Defferrard M. et\u00a0al. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. Advances in Neural Information Processing Systems 29. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2016\/file\/04df4d434d481c5bb723be1b6df1ee65-Paper.pdf"},{"key":"e_1_3_5_22_1","doi-asserted-by":"publisher","DOI":"10.1111\/gean.12049"},{"key":"e_1_3_5_23_1","doi-asserted-by":"publisher","DOI":"10.1080\/24694452.2019.1644990"},{"key":"e_1_3_5_24_1","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2019.1707834"},{"key":"e_1_3_5_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40340-8"},{"key":"e_1_3_5_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10037-021-00163-w"},{"key":"e_1_3_5_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10109-024-00440-5"},{"key":"e_1_3_5_28_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1435-5957.2006.00074.x"},{"key":"e_1_3_5_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/9780470973394"},{"key":"e_1_3_5_30_1","doi-asserted-by":"publisher","DOI":"10.3390\/math9172044"},{"key":"e_1_3_5_31_1","volume-title":"Deep learning","author":"Goodfellow I.","year":"2016","unstructured":"Goodfellow, I., 2016. Deep learning. Cambridge, MA: MIT press."},{"key":"e_1_3_5_32_1","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2015.1068318"},{"key":"e_1_3_5_33_1","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2021.1871618"},{"key":"e_1_3_5_34_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511754944"},{"key":"e_1_3_5_35_1","volume-title":"The elements of statistical learning","author":"Hastie T.","year":"2017","unstructured":"Hastie, T., et\u00a0al., 2017. The elements of statistical learning. Berlin, Germany: Springer."},{"key":"e_1_3_5_36_1","doi-asserted-by":"publisher","DOI":"10.1093\/qje\/qjx030"},{"key":"e_1_3_5_37_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-resource-100815-095343"},{"key":"e_1_3_5_38_1","volume-title":"Climate change 2023: synthesis report. Contribution of working groups I, II and III to the sixth assessment report of the intergovernmental panel on climate change","author":"IPCC","year":"2023","unstructured":"IPCC. 2023. Climate change 2023: synthesis report. Contribution of working groups I, II and III to the sixth assessment report of the intergovernmental panel on climate change. Geneva, Switzerland: IPCC."},{"key":"e_1_3_5_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeem.2020.102360"},{"key":"e_1_3_5_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2009.10.025"},{"key":"e_1_3_5_41_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07219-0"},{"key":"e_1_3_5_42_1","doi-asserted-by":"publisher","DOI":"10.1201\/9781420064254"},{"key":"e_1_3_5_43_1","doi-asserted-by":"publisher","DOI":"10.1080\/24694452.2023.2206476"},{"key":"e_1_3_5_44_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41612-024-00613-5"},{"key":"e_1_3_5_45_1","doi-asserted-by":"publisher","DOI":"10.2307\/1913646"},{"key":"e_1_3_5_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rinp.2022.105374"},{"key":"e_1_3_5_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(02)00321-3"},{"key":"e_1_3_5_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/36.406684"},{"key":"e_1_3_5_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2020.3027517"},{"key":"e_1_3_5_50_1","volume-title":"33rd Conference on Neural Information Processing Systems (NeurIPS),","author":"Paszke A.","year":"2019","unstructured":"Paszke, A., et\u00a0al., 2019. PyTorch: an imperative style, high-performance deep learning library. In: 33rd Conference on Neural Information Processing Systems (NeurIPS), 8\u201314 December 2019. Vancouver, Canada: Advances in Neural Information Processing Systems."},{"key":"e_1_3_5_51_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-16970-7"},{"key":"e_1_3_5_52_1","first-page":"175","volume-title":"Handbook of applied spatial analysis: software tools, methods and applications","author":"Rey S.J.","year":"2009","unstructured":"Rey, S.J., and Anselin, L., 2009. PySAL: A Python library of spatial analytical methods. In: Handbook of applied spatial analysis: software tools, methods and applications. Berlin, Heidelberg: Springer, 175\u2013193."},{"key":"e_1_3_5_53_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2024.104184"},{"key":"e_1_3_5_54_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"e_1_3_5_55_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(00)00018-9"},{"key":"e_1_3_5_56_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001420520138"},{"key":"e_1_3_5_57_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07147-z"},{"key":"e_1_3_5_58_1","doi-asserted-by":"publisher","DOI":"10.1111\/gean.12369"},{"key":"e_1_3_5_59_1","doi-asserted-by":"publisher","DOI":"10.2307\/143141"},{"key":"e_1_3_5_60_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-023-02323-8"},{"key":"e_1_3_5_61_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.spasta.2023.100766"},{"key":"e_1_3_5_62_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2008.08.002"},{"key":"e_1_3_5_63_1","first-page":"572","article-title":"Spatial interpolation based on spatial auto-regressive neural network","volume":"47","author":"Zeng J.","year":"2020","unstructured":"Zeng, J., et\u00a0al., 2020. Spatial interpolation based on spatial auto-regressive neural network. Journal of Zhejiang University (Science Edition), 47, 572\u2013581.","journal-title":"Journal of Zhejiang University (Science Edition)"},{"key":"e_1_3_5_64_1","doi-asserted-by":"publisher","DOI":"10.5194\/gmd-16-2777-2023"},{"key":"e_1_3_5_65_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2024.104086"},{"key":"e_1_3_5_66_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"e_1_3_5_67_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10707-021-00454-x"}],"container-title":["International Journal of Geographical Information Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/13658816.2025.2526041","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T06:18:20Z","timestamp":1769062700000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/13658816.2025.2526041"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":66,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1080\/13658816.2025.2526041"],"URL":"https:\/\/doi.org\/10.1080\/13658816.2025.2526041","relation":{},"ISSN":["1365-8816","1362-3087"],"issn-type":[{"value":"1365-8816","type":"print"},{"value":"1362-3087","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=tgis20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=tgis20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2025-02-06","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-06-23","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-06-23","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}