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Xiaogang Ning - IEEE Xplore Author Profile
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Xiaogang Ning

Publications
6
Citations
10
Publications by Year
20052025
Co-Authors:
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Xiaogang Ning

Affiliation

Chinese Academy of Surveying and Mapping, Beijing, China

Publication Topics

Biography

Xiaogang Ning received the Ph.D. degree in photogrammetry and remote sensing from Wuhan University, Wuhan, China, in 2006.,He is currently a Full Professor and the Director of the Institute of Photogrammetry and Remote Sensing. Since 2006, he has been continuously working with the Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing, China. He has authored or co-authored more than 50 peer-reviewed articles published in international journals. His research interests include high-resolution image processing, pattern recognition, and urban applications of remote sensing.(Based on document published on 13 February 2025).
Publications
6
Citations
10
Publications by Year
20052025
Co-Authors:
Show All Co-Authors (24)
Author's Published Works

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Pattern Integration and Enhancement Vision Transformer for Self-Supervised Learning in Remote Sensing

Kaixuan Lu;Ruiqian Zhang;Xiao Huang;Yuxing Xie;Xiaogang Ning;Hanchao Zhang;Mengke Yuan;Pan Zhang;Tao Wang;Tongkui Liao

IEEE Transactions on Geoscience and Remote Sensing
Year: 2025 | Volume: 63 | Journal Article |
Recent self-supervised learning (SSL) methods have demonstrated impressive results in learning visual representations from unlabeled remote sensing (RS) images. However, most RS images predominantly consist of scenographic scenes containing multiple ground objects without explicit foreground targets, which limits the performance of existing SSL methods that focus on foreground targets. This raises...Show More

Pattern Integration and Enhancement Vision Transformer for Self-Supervised Learning in Remote Sensing

Kaixuan Lu;Ruiqian Zhang;Xiao Huang;Yuxing Xie;Xiaogang Ning;Hanchao Zhang;Mengke Yuan;Pan Zhang;Tao Wang;Tongkui Liao

Year: 2025 | Volume: 63 | Journal Article |

Evaluation of Chinese Urban Land-Use Efficiency (Sdg11.3.1) Based on High-Precision Urban Built-up Area Data

Hao Wang;Yongqiang Wei;Yafei Liu;Yinxuan Cao;Ruowen Liu;Xiaogang Ning

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Quantifying SDG11.3.1, Ratio of Land Consumption Rate to Population Growth Rate (LCRPGR), is crucial to guide decision makers in urban spatial development planning, protect the ecological environment, social and economic resources sustainability. High-precision urban built-up area data is the prerequisite for accurate calculation of land consumption rate. However, high-precision data is lacking. T...Show More

Evaluation of Chinese Urban Land-Use Efficiency (Sdg11.3.1) Based on High-Precision Urban Built-up Area Data

Hao Wang;Yongqiang Wei;Yafei Liu;Yinxuan Cao;Ruowen Liu;Xiaogang Ning

Year: 2024 | Conference Paper |

Change Dino: A Unified Transformer-Based Framework For Object-Level Change Detection and Segmentation in Remote Sensing Imagery

Yixin Chen;Ruiqian Zhang;Xiaogang Ning;Hanchao Zhang;You He;Yuxing Xie;Jiaming Wang

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
In the realm of remote sensing change detection, deep learning-based pixel-level methods have shown commendable accuracy and speed. However, due to the difficulty in distinguishing between each changed object and the high matching accuracy required, there are still limitations in practical applications. To address these issues, we propose Change DINO, a novel unified object-level change detection ...Show More

Change Dino: A Unified Transformer-Based Framework For Object-Level Change Detection and Segmentation in Remote Sensing Imagery

Yixin Chen;Ruiqian Zhang;Xiaogang Ning;Hanchao Zhang;You He;Yuxing Xie;Jiaming Wang

Year: 2024 | Conference Paper |

Semantic Information Collaboration Network for Semantic Change Detection in Remote Sensing Images

Xiaogang Ning;You He;Hanchao Zhang;Ruiqian Zhang;Dong Chang;Minghui Hao

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2024 | Volume: 17 | Journal Article |
Semantic change detection (SCD) extends the traditional change detection (CD) task to simultaneously identify the change areas and their corresponding land cover categories in bi-temporal images. This “from-to” change information holds significant value in numerous practical applications and is increasingly garnering attention in the remote sensing domain. However, prevalent challenges such as los...Show More

Semantic Information Collaboration Network for Semantic Change Detection in Remote Sensing Images

Xiaogang Ning;You He;Hanchao Zhang;Ruiqian Zhang;Dong Chang;Minghui Hao

Year: 2024 | Volume: 17 | Journal Article |

Urban land cover classification based on WorldView-2 image data

Zhiyong Chen;Xiaogang Ning;Jixian Zhang

2012 International Symposium on Geomatics for Integrated Water Resource Management
Year: 2012 | Conference Paper |
Cited by: Papers (2)
Cities hahave a complex construction and easily affected by human activities, so they needsto be surveyed and analyzed timely. WorldView-2 high resolution remote sensing image makes it possible to study the urban land cover classification by its abundant space geometric features and spectral information. This paper would have aimed at given urban land cover types to choose suitable segmentation sc...Show More

Urban land cover classification based on WorldView-2 image data

Zhiyong Chen;Xiaogang Ning;Jixian Zhang

Year: 2012 | Conference Paper |

Automatic threshold selection based on ant colony optimization algorithm

Zhiwei Ye;Zhaobao Zheng;Xin Yu;Xiaogang Ning

2005 International Conference on Neural Networks and Brain
Year: 2005 | Conference Paper |
Cited by: Papers (8)
Image segmentation is a long-term difficult problem, which hasn't been fully solved. Threshold is one of the most popular algorithms. Ant colony optimization algorithm (ACO) was recently proposed algorithm, which has been successfully applied to solve many combinatorial optimization problems. On the analysis of Ostu, we are aware that threshold selection can be viewed as a combinatorial optimizati...Show More

Automatic threshold selection based on ant colony optimization algorithm

Zhiwei Ye;Zhaobao Zheng;Xin Yu;Xiaogang Ning

Year: 2005 | Volume: 2 | Conference Paper |

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