Change detection (CD) aims to reveal the dynamic evolution of the Earth’s surface by analyzing multitemporal remote sensing imagery, exhibiting significant application value in critical domains such as emergency management. With the continuous improvement in the spatial and temporal resolution of remote sensing imagery, traditional CD methods based on handcrafted features are facing increasing limitations. These approaches have gradually become insufficient to meet the demands of increasingly complex and diverse application scenarios. In recent years, fueled by the powerful feature representation capabilities of various network architectures, deep learning-based methods have achieved remarkable breakthroughs in the field of CD. This progress has also given rise to a diverse range of task types, including binary change detection, multiclass change detection, semantic change detection, change captioning, and change detection data synthesis. However, most existing reviews primarily focus on model architectures or supervision strategies, lacking a systematic overview from the perspective of task taxonomy. This keynote presents a task-oriented survey of deep learning-based CD methods for high-resolution remote sensing imagery. It comprehensively summarizes the progress, representative approaches, and application scenarios across different task categories, while also organizing widely used datasets and evaluation metrics. Furthermore, potential future directions are discussed to provide valuable insights for subsequent research.

Feng Shou, Associate Professor, PhD Supervisor of Harbin Engineering University, Deputy Director of the Key Laboratory of Advanced Ship Communication and Information Technology of the Ministry of Industry and Information Technology, IEEE member, Senior member of the Chinese Society of Communications, Member of the Imaging Detection and Perception Committee of the Chinese Society of Image and Graphics, peer review expert of the National Natural Science Foundation of China, academic dissertation review expert of the Ministry of Education, Visiting Scholar of Indiana University Bloomington, Guest Editor of Remote Sensing, an international authoritative journal in the field of remote sensing. Member of the editorial board of international Journal Frontiers in Imaging, American Journal of Remote Sensing, He also serves as a reviewer for many authoritative academic journals such as IEEE TIP, IEEE TGRS, IEEE GRSL, and Remote Sensing. In the past three years, he has published 20 academic papers as the first/corresponding author in top journals in the field of Remote Sensing such as IEEE TIP, IEEE TNNLS, IEEE TGRS, and 6 papers have been selected as ESI highly cited papers. Published 6 conference papers in IGARSS and other international conferences.