{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:01:37Z","timestamp":1781222497935,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819698653","type":"print"},{"value":"9789819698660","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-9866-0_21","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T09:26:09Z","timestamp":1753262769000},"page":"242-253","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["STINet: Spatio-Temporal Interaction Network for Remote Sensing Image Change Detection"],"prefix":"10.1007","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huilin","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaowei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"21_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10661-021-09486-0","volume":"193","author":"E Hawash","year":"2021","unstructured":"Hawash, E., El-Hassanin, A., Amer, W., El-Nahry, A., Effat, H.: Change detection and urban expansion of Port Sudan, Red Sea, using remote sensing and GIS. Environ. Monit. Assess. 193, 1\u201322 (2021)","journal-title":"Environ. Monit. Assess."},{"issue":"2","key":"21_CR2","first-page":"133","volume":"23","author":"PK Mishra","year":"2020","unstructured":"Mishra, P.K., Rai, A., Rai, S.C.: Land use and land cover change detection using geospatial techniques in the Sikkim Himalaya, India. Egypt J. Remote Sens. Spat. Sci. 23(2), 133\u2013143 (2020)","journal-title":"Egypt J. Remote Sens. Spat. Sci."},{"issue":"6","key":"21_CR3","doi-asserted-by":"publisher","first-page":"3677","DOI":"10.1109\/TGRS.2018.2886643","volume":"57","author":"S Saha","year":"2019","unstructured":"Saha, S., Bovolo, F., Bruzzone, L.: Unsupervised deep change vector analysis for multiple-change detection in VHR images. IEEE Trans. Geosci. Remote Sens. 57(6), 3677\u20133693 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"10","key":"21_CR4","doi-asserted-by":"publisher","first-page":"2661","DOI":"10.11834\/jrs.20232658","volume":"28","author":"W Wang","year":"2024","unstructured":"Wang, W., Li, X.J., Wang, X.: ADC-CPANet: a remote sensing image classification method based on local\u2013global feature fusion. Nat. Remote Sens. Bull. 28(10), 2661\u20132672 (2024)","journal-title":"Nat. Remote Sens. Bull."},{"key":"21_CR5","first-page":"1","volume":"19","author":"W Wang","year":"2022","unstructured":"Wang, W., Tang, C., Wang, X., Zheng, B.: A ViT-based multiscale feature fusion approach for remote sensing image segmentation. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2022)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Wang, W., Tan, X., Zhang, P., Wang, X.: A CBAM based multiscale transformer fusion approach for remote sensing image change detection. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 15, 6817\u20136825 (2022)","DOI":"10.1109\/JSTARS.2022.3198517"},{"key":"21_CR7","doi-asserted-by":"crossref","unstructured":"Bandara, W.G.C., Patel, V.M.: A transformer-based siamese network for change detection. In: IGARSS 2022 IEEE Int. Geosci. Remote Sens. Symp., pp. 207\u2013210 (2022)","DOI":"10.1109\/IGARSS46834.2022.9883686"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Han, C., Wu, C., Guo, H., Hu, M., Li, J., Chen, H.: Change guiding network: incorporating change prior to guide change detection in remote sensing imagery. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 16, 8395\u20138407 (2023)","DOI":"10.1109\/JSTARS.2023.3310208"},{"key":"21_CR9","first-page":"1","volume":"62","author":"W Wang","year":"2024","unstructured":"Wang, W., Liu, C., Liu, G., Wang, X.: CF-GCN: graph convolutional network for change detection in remote sensing images. IEEE Trans. Geosci. Remote Sens. 62, 1\u201313 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"21_CR10","first-page":"1","volume":"62","author":"Y Huang","year":"2024","unstructured":"Huang, Y., Li, X., Du, Z., Shen, H.: Spatiotemporal enhancement and interlevel fusion network for remote sensing images change detection. IEEE Trans. Geosci. Remote Sens. 62, 1\u201314 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"21_CR11","first-page":"1","volume":"61","author":"Z Li","year":"2023","unstructured":"Li, Z., et al.: Lightweight remote sensing change detection with progressive feature aggregation and supervised attention. IEEE Trans. Geosci. Remote Sens. 61, 1\u201312 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"21_CR12","first-page":"1","volume":"61","author":"S Fang","year":"2023","unstructured":"Fang, S., Li, K., Li, Z.: Changer: feature interaction is what you need for change detection. IEEE Trans. Geosci. Remote Sens. 61, 1\u201311 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"21_CR13","first-page":"1","volume":"62","author":"Z Li","year":"2024","unstructured":"Li, Z., et al.: STADE-CDNet: spatial\u2013temporal attention with difference enhancement-based network for remote sensing image change detection. IEEE Trans. Geosci. Remote Sens. 62, 1\u201317 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"21_CR14","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1080\/01431161.2018.1516313","volume":"40","author":"Z Sun","year":"2019","unstructured":"Sun, Z., Di, L., Fang, H.: Using long short-term memory recurrent neural network in land cover classification on Landsat and Cropland data layer time series. Int. J. Remote Sens. 40(2), 593\u2013614 (2019)","journal-title":"Int. J. Remote Sens."},{"key":"21_CR15","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556 (2014)"},{"key":"21_CR16","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J.: Coordinate attention for efficient mobile network design. In: Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit., pp. 13713\u201313722 (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"21_CR17","unstructured":"Su, Z., et al.: Pixel difference networks for efficient edge detection. In: Proc. IEEE\/CVF Int. Conf. Comput. Vis., pp. 5117\u20135127 (2021)"},{"key":"21_CR18","first-page":"1","volume":"60","author":"Q Shi","year":"2021","unstructured":"Shi, Q., Liu, M., Li, S., Liu, X., Wang, F., Zhang, L.: A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection. IEEE Trans. Geosci. Remote Sens. 60, 1\u201316 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"21_CR19","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/TGRS.2018.2858817","volume":"57","author":"S Ji","year":"2018","unstructured":"Ji, S., Wei, S., Lu, M.: Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set. IEEE Trans. Geosci. Remote Sens. 57(1), 574\u2013586 (2018)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"10","key":"21_CR20","doi-asserted-by":"publisher","first-page":"1662","DOI":"10.3390\/rs12101662","volume":"12","author":"H Chen","year":"2020","unstructured":"Chen, H., Shi, Z.: A spatial-temporal attention-based method and a new dataset for remote sensing image change detection. Remote Sens. 12(10), 1662 (2020)","journal-title":"Remote Sens."},{"key":"21_CR21","doi-asserted-by":"crossref","unstructured":"Daudt, R.C., Le Saux, B., Boulch, A.: Fully convolutional siamese networks for change detection. In: 25th IEEE Int. Conf. Image Process. (ICIP), pp. 4063\u20134067 (2018)","DOI":"10.1109\/ICIP.2018.8451652"},{"key":"21_CR22","first-page":"1","volume":"19","author":"S Fang","year":"2021","unstructured":"Fang, S., Li, K., Shao, J., Li, Z.: SNUNet-CD: A densely connected Siamese network for change detection of VHR images. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2021)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"21_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2020.3034752","volume":"60","author":"H Chen","year":"2021","unstructured":"Chen, H., Qi, Z., Shi, Z.: Remote sensing image change detection with transformers. IEEE Trans. Geosci. Remote Sens. 60, 1\u201314 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"21_CR24","first-page":"1","volume":"61","author":"Y Feng","year":"2023","unstructured":"Feng, Y., Jiang, J., Xu, H., Zheng, J.: Change detection on remote sensing images using dual-branch multilevel intertemporal network. IEEE Trans. Geosci. Remote Sens. 61, 1\u201315 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"21_CR25","doi-asserted-by":"crossref","unstructured":"Han, C., Wu, C., Du, B.: HCGMNET: a hierarchical change guiding map network for change detection. In: IGARSS 2023 IEEE Int. Geosci. Remote Sens. Symp., pp. 5511\u20135514 (2023)","DOI":"10.1109\/IGARSS52108.2023.10283341"},{"key":"21_CR26","first-page":"1","volume":"62","author":"Z Ying","year":"2024","unstructured":"Ying, Z., et al.: DGMA 2-Net: a difference-guided multiscale aggregation attention network for remote sensing change detection. IEEE Trans. Geosci. Remote Sens. 62, 1\u201316 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9866-0_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T23:01:19Z","timestamp":1781218879000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9866-0_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698653","9789819698660"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9866-0_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}