FROM-GLC Plus 3.0: Multimodal Land Change Mapping with SAM and Dense Surface Observations
Le Yu, Zhenrong Du, Xiyu Li, Jiatong Gu, Xinyue Li, Liheng Zhong, Duojiweise, Hui Wu, Qiang Zhao, Xiaorui Ma, Junqing Zheng, Yuanzheng Yang, Weimin Song, Pei Wang, Zhicong Zhao, Lingyun Liao, Ying Long, Yongguang Zhang, Jinbang Peng, Miaogen Shen, Tingting Li, Zhentao Sun, Yonggan Zhao, Chaoyang Wu, Guanghui Lin, Yong Luo, Dailiang Peng
Abstract
Land cover mapping plays a critical role in monitoring land system changes. Despite advancements in remote sensing technologies, traditional satellite-based approaches are often constrained by cloud cover, coarse temporal resolution, and limitations in capturing fine-scale landscape dynamics, leading to gaps in continuous and real-time monitoring. Near-surface cameras offer a solution by providing high-frequency, ground-level observations that bridge temporal gaps and enhance spatial detail. Therefore, this study makes substantial contributions by pioneering the integration of near-surface camera observations with satellite imagery, addressing key challenges in imaging perspective differences and limited coverage of ground-based observations for enhanced land cover monitoring at a 30-m/10-m scale. A key innovation lies in leveraging near-surface cameras to reconstruct dense satellite data time series and capture daily land cover dynamics, addressing critical temporal gaps in traditional satellite-based approaches. The research further advances the field by implementing state-of-the-art deep learning techniques, particularly the Segment Anything Model (SAM), to achieve precise parcel-level delineation and reduce classification noise at a high-resolution (meter- and submeter level) scale. Furthermore, the framework’s ability to synthesize multimodal data sources (near-surface cameras, Sentinel-1/2, and high-resolution imagery) represents a methodological breakthrough in space and surface sensor integration for real-time land cover change detection, enabling time-sensitive applications and early warning systems for land system changes.