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Articles

Super-resolution GANs for upscaling unplanned urban settlements from remote sensing satellite imagery – the case of Chinese urban village detection

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Pages 2623-2643 | Received 06 Feb 2023, Accepted 23 Jun 2023, Published online: 10 Jul 2023

References

  • Amado, Miguel, Francesca Poggi, Adriana Martins, Nuno Vieira, and Antonio Ribeiro Amado. 2018. “Transforming Cape Vert Informal Settlements.” Sustainability 10 (7): 2571. https://doi.org/10.3390/su10072571.
  • Bai, Yanbing, Erick Mas, and Shunichi Koshimura. 2018. “Towards Operational Satellite-Based Damage-Mapping Using u-net Convolutional Network: A Case Study of 2011 Tohoku Earthquake-Tsunami.” Remote Sensing 10 (10): 1626. https://doi.org/10.3390/rs10101626.
  • Chen, Bin, Jing Li, and Yufang Jin. 2021. “Deep Learning for Feature-Level Data Fusion: Higher Resolution Reconstruction of Historical Landsat Archive.” Remote Sensing 13 (2): 167. https://doi.org/10.3390/rs13020167.
  • Cheng, Gong, and Junwei Han. 2016. “A Survey on Object Detection in Optical Remote Sensing Images.” ISPRS Journal of Photogrammetry and Remote Sensing 117: 11–28. https://doi.org/10.1016/j.isprsjprs.2016.03.014.
  • Diakogiannis, Foivos I., François Waldner, Peter Caccetta, and Chen Wu. 2020. “ResUNet-a: A Deep Learning Framework for Semantic Segmentation of Remotely Sensed Data.” ISPRS Journal of Photogrammetry and Remote Sensing 162: 94–114. https://doi.org/10.1016/j.isprsjprs.2020.01.013.
  • Dong, Chao, Chen Change Loy, Kaiming He, and Xiaoou Tang. 2016. “Image Super-Resolution Using Deep Convolutional Networks.” IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (2): 295–307. https://doi.org/10.1109/TPAMI.2015.2439281.
  • Fallatah, Ahmad, Simon Jones, and David Mitchell. 2020. “Object-based Random Forest Classification for Informal Settlements Identification in the Middle East: Jeddah a Case Study.” International Journal of Remote Sensing 41 (11): 4421–4445. https://doi.org/10.1080/01431161.2020.1718237.
  • Fallatah, Ahmad, Simon Jones, David Mitchell, and Divyani Kohli. 2019. “Mapping Informal Settlement Indicators Using Object-Oriented Analysis in the Middle East.” International Journal of Digital Earth 12 (7): 802–824. https://doi.org/10.1080/17538947.2018.1485753.
  • Fu, Gang, Changjun Liu, Rong Zhou, Tao Sun, and Qijian Zhang. 2017. “Classification for High Resolution Remote Sensing Imagery Using a Fully Convolutional Network.” Remote Sensing 9 (5): 498. https://doi.org/10.3390/rs9050498.
  • Garcia-Garcia, Alberto, Sergio Orts-Escolano, Sergiu Oprea, Victor Villena-Martinez, and Jose Garcia-Rodriguez. 2017. “A Review on Deep Learning Techniques Applied to Semantic Segmentation.” arXiv preprint arXiv:1704.06857. https://doi.org/10.48550/arXiv.1704.06857
  • Gevaert, Caroline M., Richard Sliuzas, Claudio Persello, and George Vosselman. 2018. “Evaluating the Societal Impact of Using Drones to Support Urban Upgrading Projects.” ISPRS International Journal of geo-Information 7 (3): 91. https://doi.org/10.3390/ijgi7030091.
  • Ghorbanzadeh, Omid, Alessandro Crivellari, Pedram Ghamisi, Hejar Shahabi, and Thomas Blaschke. 2021. “A Comprehensive Transferability Evaluation of U-Net and ResU-Net for Landslide Detection from Sentinel-2 Data (Case Study Areas from Taiwan, China, and Japan).” Scientific Reports 11 (1): 1–20. doi:10.1038/s41598-021-94190-9.
  • Gram-Hansen, Bradley J., Patrick Helber, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova, and Piotr Bilinski. 2019. “Mapping Informal Settlements in Developing Countries Using Machine Learning and Low Resolution Multi-Spectral Data.” In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, pp. 361-368. https://doi.org/10.1145/3306618.3314253
  • He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2015. “Delving Deep into Rectifiers: Surpassing Human-Level Performance on Imagenet Classification.” In Proceedings of the IEEE international conference on computer vision, 1026–1034. https://doi.org/10.1109/ICCV.2015.123.
  • Hofmann, Peter. 2001. Detecting Informal Settlements from IKONOS Image Data Using Methods of Object Oriented Image Analysis—An Example from Cape Town (South Africa).” In Proceedings of the 2nd international symposium remote sensing of urban areas, 107–118.
  • Huang, Jingnan, Xi Xi Lu, and Jefferey M. Sellers. 2007. “A Global Comparative Analysis of Urban Form: Applying Spatial Metrics and Remote Sensing.” Landscape and Urban Planning 82 (4): 184–197. https://doi.org/10.1016/j.landurbplan.2007.02.010.
  • Huang, Yingmin, Desheng Xue, and Gengzhi Huang. 2021. “Economic Development, Informal Land-use Practices and Institutional Change in Dongguan, China.” Sustainability 13 (4): 2249. https://doi.org/10.3390/su13042249.
  • 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.
  • Kingma, Diederik P., and Jimmy Ba. 2014. “Adam: A Method for Stochastic Optimization.” arXiv preprint arXiv:1412.6980. https://doi.org/10.48550/arXiv.1412.6980
  • Kuffer, Monika, and Joana Barrosb. 2011. “Urban Morphology of Unplanned Settlements: The use of Spatial Metrics in VHR Remotely Sensed Images.” Procedia Environmental Sciences 7: 152–157. https://doi.org/10.1016/j.proenv.2011.07.027.
  • Kuffer, Monika, Karin Pfeffer, and Richard Sliuzas. 2016. “Slums from Space—15 Years of Slum Mapping Using Remote Sensing.” Remote Sensing 8 (6): 455. https://doi.org/10.3390/rs8060455.
  • Kuffer, Monika, Jiong Wang, Michael Nagenborg, Karin Pfeffer, Divyani Kohli, Richard Sliuzas, and Claudio Persello. 2018. “The Scope of Earth-Observation to Improve the Consistency of the SDG Slum Indicator.” ISPRS International Journal of geo-Information 7 (11): 428. https://doi.org/10.3390/ijgi7110428.
  • Ledig, Christian, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, et al. 2017. “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.” In Proceedings of the IEEE conference on computer vision and pattern recognition, 4681–4690. https://doi.org/10.1109/CVPR.2017.19.
  • Li, Weijia, Conghui He, Jiarui Fang, Juepeng Zheng, Haohuan Fu, and Le Yu. 2019. “Semantic Segmentation-Based Building Footprint Extraction Using Very High-Resolution Satellite Images and Multi-Source GIS Data.” Remote Sensing 11 (4): 403. https://doi.org/10.3390/rs11040403.
  • Li, Yansheng, Xin Huang, and Hui Liu. 2017. “Unsupervised Deep Feature Learning for Urban Village Detection from High-Resolution Remote Sensing Images.” Photogrammetric Engineering & Remote Sensing 83 (8): 567–579. https://doi.org/10.14358/PERS.83.8.567.
  • Li, Ling Hin, Jie Lin, Xin Li, and Fan Wu. 2014. “Redevelopment of Urban Village in China–A Step Towards an Effective Urban Policy? A Case Study of Liede Village in Guangzhou.” Habitat International 43: 299–308. https://doi.org/10.1016/j.habitatint.2014.03.009.
  • Lv, Zhiyong, Tongfei Liu, Jón Atli Benediktsson, and Nicola Falco. 2022. “Land Cover Change Detection Techniques: Very-High-Resolution Optical Images: A Review.” IEEE Geoscience and Remote Sensing Magazine 10 (1): 44–63. https://doi.org/10.1109/MGRS.2021.3088865.
  • Mahabir, Ron, Arie Croitoru, Andrew T. Crooks, Peggy Agouris, and Anthony Stefanidis. 2018. “A Critical Review of High and Very High-Resolution Remote Sensing Approaches for Detecting and Mapping Slums: Trends, Challenges and Emerging Opportunities.” Urban Science 2 (1): 8. https://doi.org/10.3390/urbansci2010008.
  • Mayunga, S. D., D. J. Coleman, and Y. Zhang. 2007. “A Semi-Automated Approach for Extracting Buildings from QuickBird Imagery Applied to Informal Settlement Mapping.” International Journal of Remote Sensing 28 (10): 2343–2357. https://doi.org/10.1080/01431160600868474.
  • Mboga, Nicholus, Claudio Persello, John Ray Bergado, and Alfred Stein. 2017. “Detection of Informal Settlements from VHR Images Using Convolutional Neural Networks.” Remote Sensing 9 (11): 1106. https://doi.org/10.3390/rs9111106.
  • Mosinska, Agata, Pablo Marquez-Neila, Mateusz Koziński, and Pascal Fua. 2018. “Beyond the Pixel-Wise Loss for Topology-Aware Delineation.” In Proceedings of the IEEE conference on computer vision and pattern recognition, 3136–3145. https://doi.org/10.1109/CVPR.2018.00331.
  • Niebergall, Susan, Alexander Loew, and Wolfram Mauser. 2008. “Integrative Assessment of Informal Settlements Using VHR Remote Sensing Data—The Delhi Case Study.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 1 (3): 193–205. https://doi.org/10.1109/JSTARS.2008.2007513.
  • Owusu, Maxwell, Monika Kuffer, Mariana Belgiu, Tais Grippa, Moritz Lennert, Stefanos Georganos, and Sabine Vanhuysse. 2021. “Towards User-Driven Earth Observation-Based Slum Mapping.” Computers, Environment and Urban Systems 89: 101681. https://doi.org/10.1016/j.compenvurbsys.2021.101681.
  • Pan, Zhuokun, Yueming Hu, and Guangxing Wang. 2019a. “Detection of Short-Term Urban Land use Changes by Combining SAR Time Series Images and Spectral Angle Mapping.” Frontiers of Earth Science 13 (3): 495–509. https://doi.org/10.1007/s11707-018-0744-6.
  • Pan, Zhuokun, Guangxing Wang, Yueming Hu, and Bin Cao. 2019b. “Characterizing Urban Redevelopment Process by Quantifying Thermal Dynamic and Landscape Analysis.” Habitat International 86: 61–70. https://doi.org/10.1016/j.habitatint.2019.03.004.
  • Park, Sung Cheol, Min Kyu Park, and Moon Gi Kang. 2003. “Super-resolution Image Reconstruction: A Technical Overview.” IEEE Signal Processing Magazine 20 (3): 21–36. https://doi.org/10.1109/MSP.2003.1203207.
  • Peng, Daifeng, Yongjun Zhang, and Haiyan Guan. 2019. “End-to-end Change Detection for High Resolution Satellite Images Using Improved UNet++.” Remote Sensing 11 (11): 1382. https://doi.org/10.3390/rs11111382.
  • Russakovsky, Olga, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, et al. 2015. “Imagenet Large Scale Visual Recognition Challenge.” International Journal of Computer Vision 115 (3): 211–252. https://doi.org/10.1007/s11263-015-0816-y.
  • Rüther, Heinz, Hagai M. Martine, and E. G. Mtalo. 2002. “Application of Snakes and Dynamic Programming Optimisation Technique in Modeling of Buildings in Informal Settlement Areas.” ISPRS Journal of Photogrammetry and Remote Sensing 56 (4): 269–282. https://doi.org/10.1016/S0924-2716(02)00062-X.
  • Sdraka, Maria, Ioannis Papoutsis, Bill Psomas, Konstantinos Vlachos, Konstantinos Ioannidis, Konstantinos Karantzalos, Ilias Gialampoukidis, and Stefanos Vrochidis. 2022. “Deep Learning for Downscaling Remote Sensing Images: Fusion and Super-Resolution.” IEEE Geoscience and Remote Sensing Magazine 10 (3): 202–255. https://doi.org/10.1109/MGRS.2022.3171836.
  • Sedona, Rocco, Claudia Paris, Gabriele Cavallaro, Lorenzo Bruzzone, and Morris Riedel. 2021. “A High-Performance Multispectral Adaptation GAN for Harmonizing Dense Time Series of Landsat-8 and Sentinel-2 Images.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14: 10134–10146. https://doi.org/10.1109/JSTARS.2021.3115604.
  • Sherrah, Jamie. 2016. “Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery.” arXiv preprint arXiv:1606.02585. https://doi.org/10.48550/arXiv.1606.02585
  • Shi, Wenzhe, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang. 2016. “Real-time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.” In Proceedings of the IEEE conference on computer vision and pattern recognition, 1874–1883. https://doi.org/10.1109/CVPR.2016.207.
  • Simonyan, Karen, and Andrew Zisserman. 2014. “Very Deep Convolutional Networks for Large-Scale Image Recognition.” arXiv preprint arXiv:1409.1556. https://doi.org/10.48550/arXiv.1409.1556
  • Stow, D., A. Lopez, C. Lippitt, S. Hinton, and J. Weeks. 2007. “Object-Based Classification of Residential Land use Within Accra, Ghana Based on QuickBird Satellite Data.” International Journal of Remote Sensing 28 (22): 5167–5173. https://doi.org/10.1080/01431160701604703.
  • Taylor, Linnet. 2017. “Safety in Numbers? Group Privacy and big Data Analytics in the Developing World.” Group Privacy: New Challenges of Data Technologies, 13–36. https://doi.org/10.1007/978-3-319-46608-8_2.
  • Wagner, Fabien H., Alber Sanchez, Yuliya Tarabalka, Rodolfo G. Lotte, Matheus P. Ferreira, Marcos PM Aidar, Emanuel Gloor, Oliver L. Phillips, and Luiz EOC Aragao. 2019. “Using the U-net Convolutional Network to map Forest Types and Disturbance in the Atlantic Rainforest with Very High Resolution Images.” Remote Sensing in Ecology and Conservation 5 (4): 360–375. https://doi.org/10.1002/rse2.111.
  • Wang, Zhihao, Jian Chen, and Steven CH Hoi. 2021. “Deep Learning for Image Super-Resolution: A Survey.” IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (10): 3365–3387. https://doi.org/10.1109/TPAMI.2020.2982166.
  • Wang, Ya Ping, Yanglin Wang, and Jiansheng Wu. 2009. “Urbanization and Informal Development in China: Urban Villages in Shenzhen.” International Journal of Urban and Regional Research 33 (4): 957–973. https://doi.org/10.1111/j.1468-2427.2009.00891.x.
  • Williams, Nathaniel, Duncan Quincey, and John Stillwell. 2016. “Automatic Classification of Roof Objects from Aerial Imagery of Informal Settlements in Johannesburg.” Applied Spatial Analysis and Policy 9 (2): 269–281. https://doi.org/10.1007/s12061-015-9158-y.
  • Yang, Wenming, Xuechen Zhang, Yapeng Tian, Wei Wang, Jing-Hao Xue, and Qingmin Liao. 2019. “Deep Learning for Single Image Super-Resolution: A Brief Review.” IEEE Transactions on Multimedia 21 (12): 3106–3121. https://doi.org/10.1109/TMM.2019.2919431.
  • Yi, Yaning, Zhijie Zhang, Wanchang Zhang, Chuanrong Zhang, Weidong Li, and Tian Zhao. 2019. “Semantic Segmentation of Urban Buildings from VHR Remote Sensing Imagery Using a Deep Convolutional Neural Network.” Remote Sensing 11 (15): 1774. https://doi.org/10.3390/rs11151774.
  • Zhang, Yongbing, Debin Zhao, Jian Zhang, Ruiqin Xiong, and Wen Gao. 2011. “Interpolation-dependent Image Downsampling.” IEEE Transactions on Image Processing 20 (11): 3291–3296. https://doi.org/10.1109/TIP.2011.2158226.
  • Zhaohui, Liu. 2011. “An Empirical Analysis of the Community Life of New Urban Migrants: Guangzhou, Dongguan, Hangzhou, Chengdu, Zhengzhou, and Shenyang.” Chinese Sociology & Anthropology 43 (3): 5–37. https://doi.org/10.2753/CSA0009-4625430301.
  • 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. doi:10.1109/MGRS.2017.2762307.