Global heterogeneous graph convolutional network: from coarse to refined land cover and land use segmentation

References

• Achanta, Radhakrishna, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Süsstrunk. 2012. “SLIC Superpixels Compared to State-of-the-Art Superpixel Methods.” IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (11): 2274–2282. https://doi.org/10.1109/TPAMI.2012.120.
   PubMed Web of Science ®Google Scholar
• Albert, L., F. Rottensteiner, and C. Heipke. 2015. “An Iterative Inference Procedure Applying Conditional Random Fields for Simultaneous Classification of Land Cover and Land Use.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5: 369–376. https://doi.org/10.5194/isprsannals-II-3-W5-369-2015.
   Google Scholar
• Barnsley, Michael J., and Stuart L. Barr. 1996. “Inferring Urban Land Use from Satellite Sensor Images Using Kernel-Based Spatial Reclassification.” Photogrammetric Engineering and Remote Sensing 62: 949–958.
   Web of Science ®Google Scholar
• Barnsley, Michael J., and Stuart L. Barr. 1997. “Distinguishing Urban Land-Use Categories in Fine Spatial Resolution Land-Cover Data Using a Graph-Based, Structural Pattern Recognition System.” Computers, Environment and Urban Systems 21 (3): 209–225. https://doi.org/10.1016/S0198-9715(97)10001-1.
   Google Scholar
• Barnsley, Michael J., and Stuart L. Barr. 2000. “Monitoring Urban Land Use by Earth Observation.” Surveys in Geophysics 21 (2): 269–289. https://doi.org/10.1023/A:1006798328429.
   Web of Science ®Google Scholar
• Barr, Stuart, and Micheal Barnsley. 1997. “A Region-Based, Graph-Theoretic Data Model for the Inference of Second-Order Thematic Information from Remotely-Sensed Images.” International Journal of Geographical Information Science 11 (6): 555–576. https://doi.org/10.1080/136588197242194.
   Web of Science ®Google Scholar
• Brown, Christopher F., Steven P. Brumby, Brookie Guzder-Williams, Tanya Birch, Samantha Brooks Hyde, Joseph Mazzariello, Wanda Czerwinski, et al. 2022. “Dynamic World, Near Real-Time Global 10 m Land use Land Cover Mapping.” Scientific Data 9 (1): 251. https://doi.org/10.1038/s41597-022-01307-4.
   Web of Science ®Google Scholar
• Chen, Yunpeng, Marcus Rohrbach, Zhicheng Yan, Yan Shuicheng, Jiashi Feng, and Yannis Kalantidis. 2019. “Graph-Based Global Reasoning Networks.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 433–442.
   Google Scholar
• Chen, Liang-Chieh, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam. 2018. “Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.” In Computer Vision – ECCV 2018, 833–851. https://doi.org/10.1007/978-3-030-01234-2_49
   Google Scholar
• Comber, Alexis J, Chris F Brunsdon, and Carson JQ Farmer. 2012. “Community Detection in Spatial Networks: Inferring Land Use from a Planar Graph of Land Cover Objects.” International Journal of Applied Earth Observation and Geoinformation 18: 274–282. https://doi.org/10.1016/j.jag.2012.01.020.
   Web of Science ®Google Scholar
• Cui, Wei, Meng Yao, Yuanjie Hao, Ziwei Wang, Xin He, Weijie Wu, Jie Li, Huilin Zhao, Cong Xia, and Jin Wang. 2021. “Knowledge and Geo-Object Based Graph Convolutional Network for Remote Sensing Semantic Segmentation.” Sensors 21 (11): 3848. https://doi.org/10.3390/s21113848.
   PubMed Web of Science ®Google Scholar
• Durand, Nicolas, Sebastien Derivaux, Germain Forestier, Cedric Wemmert, Pierre Gancarski, Omar Boussaid, and Anne Puissant. 2007. “Ontology-Based Object Recognition for Remote Sensing Image Interpretation.” In 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007). Vol. 1, 472–479. https://doi.org/10.1109/ICTAI.2007.111.
   Google Scholar
• Esch, Thomas, Wieke Heldens, Andreas Hirner, Manfred Keil, Mattia Marconcini, Achim Roth, Julian Zeidler, Stefan Dech, and Emanuele Strano. 2017. “Breaking New Ground in Mapping Human Settlements from Space – the Global Urban Footprint.” ISPRS Journal of Photogrammetry and Remote Sensing 134: 30–42. https://doi.org/10.1016/j.isprsjprs.2017.10.012.
   Web of Science ®Google Scholar
• Eyton, J. Ronald. 1993. “Urban Land Use Classification and Modelling Using Cover-Type Frequencies.” Applied Geography 13 (2): 111–121. https://doi.org/10.1016/0143-6228(93)90053-4.
   Web of Science ®Google Scholar
• Feddema, Johannes J., Keith W. Oleson, Gordon B. Bonan, Linda O. Mearns, Lawrence E. Buja, Gerald A. Meehl, and Warren M. Washington. 2005. “The Importance of Land-Cover Change in Simulating Future Climates.” Science 310 (5754): 1674–1678. https://doi.org/10.1126/science.1118160.
   PubMed Web of Science ®Google Scholar
• Foley, Jonathan A., Ruth DeFries, Gregory P. Asner, Carol Barford, Gordon Bonan, Stephen R. Carpenter, F. Stuart Chapin, et al. 2005. “Global Consequences of Land Use.” Science 309 (5734): 570–574. https://doi.org/10.1126/science.1111772.
   PubMed Web of Science ®Google Scholar
• Fu, Jun, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang, and Hanqing Lu. 2019. “Dual Attention Network for Scene Segmentation.” In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 3141–3149. https://doi.org/10.1109/CVPR.2019.00326.
   Google Scholar
• Ge, Panpan, Jun He, Shuhua Zhang, Liwei Zhang, and Jiangfeng She. 2019. “An Integrated Framework Combining Multiple Human Activity Features for Land Use Classification.” ISPRS International Journal of Geo-Information 8 (2): 90. https://doi.org/10.3390/ijgi8020090.
   Web of Science ®Google Scholar
• Gong, Peng, Han Liu, Meinan Zhang, Congcong Li, Jie Wang, Huabing Huang, Nicholas Clinton, et al. 2019. “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.” Science Bulletin 64: 370–373. https://doi.org/10.1016/j.scib.2019.03.002.
   PubMed Web of Science ®Google Scholar
• Guo, Meng-Hao, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng, and Shi-min Hu. 2022. “SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation.” Advances in Neural Information Processing Systems 35: 1140–1156.
   Google Scholar
• Hazirbas, Caner, Lingni Ma, Csaba Domokos, and Daniel Cremers. 2017. “FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture.” In Computer Vision – ACCV 2016, 213–228. https://doi.org/10.1007/978-3-319-54181-5_14
   Google Scholar
• He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. “Deep Residual Learning for Image Recognition.” In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770–778. https://doi.org/10.1109/CVPR.2016.90.
   Google Scholar
• Hong, Danfeng, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, and Jocelyn Chanussot. 2020. “Graph Convolutional Networks for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 59 (7): 5966–5978. https://doi.org/10.1109/TGRS.2020.3015157.
   Web of Science ®Google Scholar
• Hu, Hanzhe, Deyi Ji, Weihao Gan, Shuai Bai, Wei Wu, and Junjie Yan. 2020. “Class-Wise Dynamic Graph Convolution for Semantic Segmentation.” In European Conference on Computer Vision, 1–17.
   Google Scholar
• Ioffe, Sergey, and Christian Szegedy. 2015. “Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.” In International Conference on Machine Learning, 448–456.
   Google Scholar
• Jiao, Libin, Lianzhi Huo, Changmiao Hu, and Ping Tang. 2021. “Refined UNet V3: Efficient End-to-End Patch-Wise Network for Cloud and Shadow Segmentation with Multi-Channel Spectral Features.” Neural Networks 143: 767–782. https://doi.org/10.1016/j.neunet.2021.08.008.
   PubMed Web of Science ®Google Scholar
• Karra, Krishna, Caitlin Kontgis, Zoe Statman-Weil, Joseph C. Mazzariello, Mark Mathis, and Steven P. Brumby. 2021. “Global Land Use / Land Cover with Sentinel 2 and Deep Learning.” In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 4704–4707. https://doi.org/10.1109/IGARSS47720.2021.9553499.
   Google Scholar
• Kingma, Diederik P., and Jimmy Ba. 2014. “Adam: A Method for Stochastic Optimization.” arXiv Preprint arXiv:1412.6980.
   Google Scholar
• Kipf, Thomas N, and Max Welling. 2016. “Semi-Supervised Classification with Graph Convolutional Networks.” arXiv Preprint arXiv:1609.02907.
   Google Scholar
• Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E Hinton. 2012. “Imagenet Classification with Deep Convolutional Neural Networks.” Advances in Neural Information Processing Systems 25.
   Google Scholar
• Li, Yin, and Abhinav Gupta. 2018. “Beyond Grids: Learning Graph Representations for Visual Recognition.” In Advances in Neural Information Processing Systems. Vol. 31.
   Google Scholar
• Li, Zhuohong, Wei He, Mofan Cheng, Jingxin Hu, Guangyi Yang, and Hongyan Zhang. 2023. “SinoLC-1: The First 1-Meter Resolution National-Scale Land-Cover Map of China Created with the Deep Learning Framework and Open-Access Data.” Earth System Science Data Discussions 2023: 1–38. https://doi.org/10.5194/essd-2023-87.
   Google Scholar
• Liu, Zhuang, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie. 2022. “A ConvNet for the 2020s.” In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 11966–11976. https://doi.org/10.1109/CVPR52688.2022.01167.
   Google Scholar
• Liu, Mingyuan, Dan Schonfeld, and Wei Tang. 2021. “Exploit Visual Dependency Relations for Semantic Segmentation.” In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 9721–9730. https://doi.org/10.1109/CVPR46437.2021.00960.
   Google Scholar
• Liu, Xuan, Ping Tang, Xing Jin, and Zheng Zhang. 2022. “From Regression Based on Dynamic Filter Network to Pansharpening by Pixel-Dependent Spatial-Detail Injection.” Remote Sensing 14 (5): 1242. https://doi.org/10.3390/rs14051242.
   Web of Science ®Google Scholar
• Liu, Zhi-Qiang, Ping Tang, Weixiong Zhang, and Zheng Zhang. 2022. “CNN-Enhanced Heterogeneous Graph Convolutional Network: Inferring Land Use from Land Cover with a Case Study of Park Segmentation.” Remote Sensing 14 (19): 5027. https://doi.org/10.3390/rs14195027.
   Web of Science ®Google Scholar
• Liu, Qichao, Liang Xiao, Jingxiang Yang, and Zhihui Wei. 2020. “CNN-Enhanced Graph Convolutional Network with Pixel-and Superpixel-Level Feature Fusion for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 59 (10): 8657–8671.
   Web of Science ®Google Scholar
• Long, Jonathan, Evan Shelhamer, and Trevor Darrell. 2015. “Fully Convolutional Networks for Semantic Segmentation.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3431–3440.
   Google Scholar
• Lv, Zhiyong, Pengfei Zhang, Weiwei Sun, Jón Atli Benediktsson, Junhuai Li, and Wei Wang. 2023. “Novel Adaptive Region Spectral–Spatial Features for Land Cover Classification with High Spatial Resolution Remotely Sensed Imagery.” IEEE Transactions on Geoscience and Remote Sensing 61: 1–12. https://doi.org/10.1109/TGRS.2023.3275753.
   Web of Science ®Google Scholar
• Nair, Vinod, and Geoffrey E. Hinton. 2010. “Rectified Linear Units Improve Restricted Boltzmann Machines.” In Proceedings of the 27th International Conference on International Conference on Machine Learning, 807–814.
   Google Scholar
• Niu, Ruigang, Xian Sun, Yu Tian, Wenhui Diao, Yingchao Feng, and Kun Fu. 2022. “Improving Semantic Segmentation in Aerial Imagery via Graph Reasoning and Disentangled Learning.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–18. https://doi.org/10.1109/TGRS.2021.3121471.
   Web of Science ®Google Scholar
• Pielke, Roger A. 2005. “Land Use and Climate Change.” Science 310 (5754): 1625–1626. https://doi.org/10.1126/science.1120529.
   PubMed Web of Science ®Google Scholar
• Song, Wen, Wei Song, Haihong Gu, and Fuping Li. 2020. “Progress in the Remote Sensing Monitoring of the Ecological Environment in Mining Areas.” International Journal of Environmental Research and Public Health 17 (6): 1846. https://doi.org/10.3390/ijerph17061846.
   PubMed Web of Science ®Google Scholar
• Sterling, Shannon M., Agnès Ducharne, and Jan Polcher. 2013. “The Impact of Global Land-Cover Change on the Terrestrial Water Cycle.” Nature Climate Change 3 (4): 385–390. https://doi.org/10.1038/nclimate1690.
   Web of Science ®Google Scholar
• Su, Yanzhou, Jian Cheng, Wen Wang, Haiwei Bai, and Haijun Liu. 2022. “Semantic Segmentation for High-Resolution Remote-Sensing Images via Dynamic Graph Context Reasoning.” IEEE Geoscience and Remote Sensing Letters 19: 1–5. https://doi.org/10.1109/LGRS.2022.3145499.
   Web of Science ®Google Scholar
• Sun, Weiwei, Kai Ren, Xiangchao Meng, Gang Yang, Jiangtao Peng, and Jiancheng Li. 2023. “Unsupervised 3-d Tensor Subspace Decomposition Network for Spatial–Temporal–Spectral Fusion of Hyperspectral and Multispectral Images.” IEEE Transactions on Geoscience and Remote Sensing 61: 1–17. https://doi.org/10.1109/TGRS.2023.3324028.
   Web of Science ®Google Scholar
• Sun, Weiwei, Kai Ren, Xiangchao Meng, Gang Yang, Chenchao Xiao, Jiangtao Peng, and Jingfeng Huang. 2022. “MLR-DBPFN: A Multi-Scale Low Rank Deep Back Projection Fusion Network for Anti-Noise Hyperspectral and Multispectral Image Fusion.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–14. https://doi.org/10.1109/TGRS.2022.3146296.
   Web of Science ®Google Scholar
• Tang, Jiwen, Zheng Zhang, Lijun Zhao, and Ping Tang. 2021. “Increasing Shape Bias to Improve the Precision of Center Pivot Irrigation System Detection.” Remote Sensing 13 (4): 612. https://doi.org/10.3390/rs13040612.
   Web of Science ®Google Scholar
• Tong, Xin-Yi, Gui-Song Xia, Qikai Lu, Huanfeng Shen, Shengyang Li, Shucheng You, and Liangpei Zhang. 2020. “Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models.” Remote Sensing of Environment 237: 111322. https://doi.org/10.1016/j.rse.2019.111322.
   Web of Science ®Google Scholar
• Tong, Xin-Yi, Gui-Song Xia, and Xiao Xiang Zhu. 2023. “Enabling Country-Scale Land Cover Mapping with Meter-Resolution Satellite Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 196: 178–196. https://doi.org/10.1016/j.isprsjprs.2022.12.011.
   PubMed Web of Science ®Google Scholar
• Van der Kwast, Johannes, Tim Van de Voorde, Frank Canters, Inge Uljee, Stijn Van Looy, and Guy Engelen. 2011. “Inferring Urban Land Use Using the Optimised Spatial Reclassification Kernel.” Environmental Modelling & Software 26 (11): 1279–1288. https://doi.org/10.1016/j.envsoft.2011.05.012.
   Web of Science ®Google Scholar
• Vitousek, Peter M., Harold A. Mooney, Jane Lubchenco, and Jerry M. Melillo. 1997. “Human Domination of Earth’s Ecosystems.” Science 277 (5325): 494–499. https://doi.org/10.1126/science.277.5325.494.
   Web of Science ®Google Scholar
• Walde, Irene, Sören Hese, Christian Berger, and Christiane Schmullius. 2014. “From Land Cover-Graphs to Urban Structure Types.” International Journal of Geographical Information Science 28 (3): 584–609. https://doi.org/10.1080/13658816.2013.865189.
   Web of Science ®Google Scholar
• Wan, Sheng, Chen Gong, Ping Zhong, Bo Du, Lefei Zhang, and Jian Yang. 2019. “Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 58 (5): 3162–3177.
   Web of Science ®Google Scholar
• Wharton, Stephen W. 1982. “A Contextual Classification Method for Recognizing Land Use Patterns in High Resolution Remotely Sensed Data.” Pattern Recognition 15 (4): 317–324. https://doi.org/10.1016/0031-3203(82)90034-6.
   Web of Science ®Google Scholar
• Xie, Enze, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, and Ping Luo. 2021. “SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers.” In Advances in Neural Information Processing Systems 34: 12077–12090.
   Google Scholar
• Yang, Kunping, Xin-Yi Tong, Gui-Song Xia, Weiming Shen, and Liangpei Zhang. 2022. “Hidden Path Selection Network for Semantic Segmentation of Remote Sensing Images.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–15. https://doi.org/10.1109/TGRS.2022.3197334.
   Web of Science ®Google Scholar
• Yu, Changqian, Changxin Gao, Jingbo Wang, Gang Yu, Chunhua Shen, and Nong Sang. 2021. “BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation.” International Journal of Computer Vision 129 (11): 3051–3068. https://doi.org/10.1007/s11263-021-01515-2.
   Web of Science ®Google Scholar
• Yuan, Yuhui, Lang Huang, Jianyuan Guo, Chao Zhang, Xilin Chen, and Jingdong Wang. 2018. “OCNet: Object Context Network for Scene Parsing.” arXiv e-Prints September. https://doi.org/10.48550/arXiv.1809.00916.
   Google Scholar
• Zanaga, Daniele, Ruben Van De Kerchove, Dirk Daems, W. De Keersmaecker, Carsten Brockmann, Grit Kirches, Jan Wevers, et al. 2022. “ESA WorldCover 10 m 2021 V200.”
   Google Scholar
• Zhang, Xiuyuan, Shihong Du, and Yuan Zhang. 2018. “Semantic and Spatial Co-Occurrence Analysis on Object Pairs for Urban Scene Classification.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (8): 2630–2643. https://doi.org/10.1109/JSTARS.2018.2854159.
   Web of Science ®Google Scholar
• Zhang, Xiuyuan, Shihong Du, and Jixian Zhang. 2019. “How Do People Understand Convenience-of-Living in Cities? A Multiscale Geographic Investigation in Beijing.” ISPRS Journal of Photogrammetry and Remote Sensing 148: 87–102. https://doi.org/10.1016/j.isprsjprs.2018.12.016.
   Web of Science ®Google Scholar
• Zhang, Li, Xiangtai Li, Anurag Arnab, Kuiyuan Yang, Yunhai Tong, and Philip H. S. Torr. 2019. “Dual Graph Convolutional Network for Semantic Segmentation.” arXiv e-Prints September. https://doi.org/10.48550/arXiv.1909.06121.
   Google Scholar
• Zhang, Wei, Ping Tang, and Lijun Zhao. 2019. “Remote Sensing Image Scene Classification Using CNN-CapsNet.” Remote Sensing 11 (5): 494. https://doi.org/10.3390/rs11050494.
   Web of Science ®Google Scholar
• Zhang, Liangpei, Lefei Zhang, and Bo Du. 2016. “Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art.” IEEE Geoscience and Remote Sensing Magazine 4 (2): 22–40. https://doi.org/10.1109/MGRS.2016.2540798.
   Web of Science ®Google Scholar
• Zhao, Zhitao, Ping Tang, Lijun Zhao, and Zheng Zhang. 2022. “Few-Shot Object Detection of Remote Sensing Images via Two-Stage Fine-Tuning.” IEEE Geoscience and Remote Sensing Letters 19: 1–5. https://doi.org/10.1109/LGRS.2021.3116858.
   Web of Science ®Google Scholar
• Zhao, Bei, Yanfei Zhong, and Liangpei Zhang. 2016. “A Spectral–Structural Bag-of-Features Scene Classifier for Very High Spatial Resolution Remote Sensing Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 116: 73–85. https://doi.org/10.1016/j.isprsjprs.2016.03.004.
   Web of Science ®Google Scholar
• Zhou, Zongwei, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang. 2018. “UNet++: A Nested u-Net Architecture for Medical Image Segmentation.” Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 3–11.
   Google Scholar
• Zhu, Xiao Xiang, Chunping Qiu, Jingliang Hu, Yilei Shi, Yuanyuan Wang, Michael Schmitt, and Hannes Taubenböck. 2022. “The Urban Morphology on Our Planet – Global Perspectives from Space.” Remote Sensing of Environment 269: 112794. https://doi.org/10.1016/j.rse.2021.112794.
   PubMed Web of Science ®Google Scholar
• Zhu, Xiao Xiang, Devis Tuia, Lichao Mou, Gui-Song Xia, Liangpei Zhang, Feng Xu, and Friedrich Fraundorfer. 2017. “Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources.” IEEE Geoscience and Remote Sensing Magazine 5 (4): 8–36. https://doi.org/10.1109/MGRS.2017.2762307.
   Web of Science ®Google Scholar
• Zhu, Zhe, Yuyu Zhou, Karen C. Seto, Eleanor C. Stokes, Chengbin Deng, Steward T. A. Pickett, and Hannes Taubenböck. 2019. “Understanding an Urbanizing Planet: Strategic Directions for Remote Sensing.” Remote Sensing of Environment 228: 164–182. https://doi.org/10.1016/j.rse.2019.04.020.
   Web of Science ®Google Scholar