Self-supervised representation learning for geospatial objects: A survey

Yile Chen, Weiming Huang, Kaiqi Zhao, Yue Jiang, Gao Cong

Abstract: Highlights•First survey on self-supervised representation learning for popular geospatial object types.•The integration of various geospatial contextual information is discussed.•A wide array of supported geospatial and urban analyses is presented.•A narrative from traditional deep learning techniques to the recent trend of foundation models is presented.