Abstract
Remote sensing image classification method is the focus of current academic field. Most studies use complex machine learning and deep learning methods to extract ground object, but lack simple and effective methods to extract ground object with distinctive features. In this paper, using rule-based object-oriented classification technology, through remote sensing image preprocessing, multi-scale segmentation, extraction rule formulation and other steps, using object-oriented classification method, taking Jinfeng District, Xixia District and Xingqing District of Yinchuan City as an example, The blue roof buildings in the range were extracted, and the results showed that the method can effectively extract the target features.
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Acknowledgments
This work was supported by: Ningxia Hui Autonomous Region Key R&D Plan Projects: Research and Demonstration Application of Key Technologies of Spatial Planning Intelligent Monitoring Based on High Score Remote Sensing (Item Number: 2018YBZD1629).
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Zhang, D., Yin, X., Xie, Y., He, Z., Wang, L. (2020). GF-2 Image Blue Roof Building Extraction Method Based on Object-Oriented Classification Technology. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Communications in Computer and Information Science, vol 1252. Springer, Singapore. https://doi.org/10.1007/978-981-15-8083-3_11
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DOI: https://doi.org/10.1007/978-981-15-8083-3_11
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