With the rapid advancement of remote sensing technology, platforms such as unmanned aerial vehicles (UAV), synthetic aperture radar (SAR), satellites, and LiDAR have enabled the acquisition of large volumes of multi-source and multi-temporal imagery of the Earth's surface. These data contain rich geographic information and hold significant application value in various fields, including natural resource monitoring, urban planning, and disaster assessment. As one of the key techniques in remote sensing image analysis, change detection aims to identify and analyze surface coverage changes from multi-temporal remote sensing images. It plays an important role in helping people monitor environmental dynamics, assess disaster impacts, and plan urban development, and thus has become a major research focus in the field of remote sensing.
LCCDMamba: Visual State Space Model for Land Cover Change Detection of VHR Remote Sensing Images
Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Yapeng Wang, Min Xia
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, 2025, pp. 5765-5781
Junqing Huang, Junqi Bao, Min Xia, Xiaochen Yuan
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, 2025, pp. 16916-16928
F3Net: Feature Filtering Fusing Network for Change Detection of Remote Sensing Images
Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Guoheng Huang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, 2024, pp. 10621-10635
Large kernel convolution application for land cover change detection of remote sensing images
Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Wei Ke, Guoheng Huang
International Journal of Applied Earth Observation and Geoinformation, vol. 132, 2024, p. 104077
MSFGNet: Multi-Scale Features Gathering Network for Change Detection of Remote Sensing Images
Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Wei Ke
2024 IEEE International Conference on Multimedia and Expo (ICME), 2024, pp. 1-6