[1] Huang X, Zhu T T, Zhang L P et al. A novel building change index for automatic building change detection from high-resolution remote sensing imagery[J]. Remote Sensing Letters, 5, 713-722(2014).

[2] Du P J, Wang X, Meng Y P et al. Effective change detection approaches for geographic national condition monitoring and land cover map updating[J]. Journal of Geo-Information Science, 22, 857-866(2020).

[3] Lu L L, Guo H D, Corbane C et al. Urban sprawl in provincial capital cities in China: evidence from multi-temporal urban land products using landsat data[J]. Science Bulletin, 64, 955-957(2019).

[4] Shi W Z, Zhang P L. State-of-the-art remotely sensed images-based change detection methods[J]. Geomatics and Information Science of Wuhan University, 43, 1832-1837(2018).

[5] Zhang Z X, Jiang H W, Pang S Y et al. Review and prospect in change detection of multi-temporal remote sensing images[J]. Acta Geodaetica et Cartographica Sinica, 51, 1091-1107(2022).

[6] Wen D W, Huang X, Bovolo F et al. Change detection from very-high-spatial-resolution optical remote sensing images: methods, applications, and future directions[J]. IEEE Geoscience and Remote Sensing Magazine, 9, 68-101(2021).

[7] Liu T, Yang L X, Lunga D. Change detection using deep learning approach with object-based image analysis[J]. Remote Sensing of Environment, 256, 112308(2021).

[8] Huang P, Zheng Q, Liang C. Overview of image segmentation methods[J]. Journal of Wuhan University (Natural Science Edition), 66, 519-531(2020).

[9] Liu X G, Li M M, Wang X Q et al. Use of object-based Siamese neural network to build change detection from very high resolution remote-sensing images[J]. Journal of Remote Sensing, 28, 437-454(2024).

[10] Liang Z H, Li X, Deng P et al. Remote sensing image change detection fusion method integrating multi-scale feature attention[J]. Acta Geodaetica et Cartographica Sinica, 51, 668-676(2022).

[11] Wang Z X, Peng C Y, Zhang Y et al. Fully convolutional Siamese networks based change detection for optical aerial images with focal contrastive loss[J]. Neurocomputing, 457, 155-167(2021).

[12] Peng D F, Zhang Y J, Guan H Y. End-to-end change detection for high resolution satellite images using improved UNet++[J]. Remote Sensing, 11, 1382(2019).

[13] Liu M X, Chai Z Q, Deng H J et al. A CNN-transformer network with multiscale context aggregation for fine-grained cropland change detection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 4297-4306(2022).

[14] Li Z L, Tang C, Liu X W et al. Lightweight remote sensing change detection with progressive feature aggregation and supervised attention[J]. IEEE Transactions on Geoscience and Remote Sensing, 61, 5602812(2023).

[15] Chen J, Yuan Z Y, Peng J et al. DASNet: dual attentive fully convolutional Siamese networks for change detection in high-resolution satellite images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 1194-1206(2021).

[16] Cheng G, Wang G X, Han J W. ISNet: towards improving separability for remote sensing image change detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 5623811(2022).

[17] Liu J F, Chen K M, Xu G L et al. Convolutional neural network-based transfer learning for optical aerial images change detection[J]. IEEE Geoscience and Remote Sensing Letters, 17, 127-131(2020).

[18] Wang C, Wang S, Chen X et al. Object-level change detection of multi-sensor optical remote sensing images combined with UNet++ and multi-level difference module[J]. Acta Geodaetica et Cartographica Sinica, 52, 283-296(2023).

[19] Jiang M, Zhang X C, Sun Y et al. Full-scale feature aggregation network for high-resolution remote sensing image change detection[J]. Acta Geodaetica et Cartographica Sinica, 52, 1738-1748(2023).

[20] Hu J, Shen L, Sun G. Squeeze-and-excitation networks[C], 7132-7141(2018).

[21] Zhang F X, Huang J, Li H. Lightweight bilateral input D-WNet aerial image building change detection[J]. Laser & Optoelectronics Progress, 61, 0828003(2024).

[22] Zhang J B, Yan Z X, Ma S F. Multi-scale cross dual attention network for building change detection in remote sensing images[J]. Journal of Geo-Information Science, 25, 2487-2500(2023).

[23] Huang Y Y, Li X H, Du Z S et al. Spatiotemporal enhancement and interlevel fusion network for remote sensing images change detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 62, 5609414(2024).

[24] Chen H, Shi Z W. A spatial-temporal attention-based method and a new dataset for remote sensing image change detection[J]. Remote Sensing, 12, 1662(2020).

[25] Liu Y, Guo H T, Lu J et al. Remote sensing image change detection method based on adaptive boundary sensing[J]. Acta Optica Sinica, 44, 1828001(2024).

[26] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Computer vision‒ECCV 2018, 11211, 3-19(2018).

[27] Yu F, Koltun V, Funkhouser T. Dilated residual networks[C], 636-644(2017).

[28] Tian Q L, Qin K, Chen J et al. Building change detection for aerial images based on attention pyramid network[J]. Acta Optica Sinica, 40, 2110002(2020).

[29] Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation[M]. Medical image computing and computer-assisted intervention-MICCAI 2015, 9351, 234-241(2015).

[30] Huang L, Yuan Y H, Guo J Y et al. Interlaced sparse self-attention for semantic segmentation[EB/OL]. https:∥arxiv.org/abs/1907.12273

[31] Wang D C, Chen X N, Jiang M Y et al. ADS-Net: an attention-based deeply supervised network for remote sensing image change detection[J]. International Journal of Applied Earth Observation and Geoinformation, 101, 102348(2021).

[32] Ji S P, Wei S Q, Lu M. Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 574-586(2019).

[33] Daudt R C, Le Saux B, Boulch A. Fully convolutional Siamese networks for change detection[C]. Greece, 4063-4067(2018).

[34] Zhang C X, Yue P, Tapete D et al. A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 183-200(2020).

[35] Chen H, Qi Z P, Shi Z W. Remote sensing image change detection with transformers[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 5607514(2022).