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多模遥感立体信息获取发展现状与展望-航天遥感图像智能处理与分析

何书剑1,李贤1,谷延锋2   

  1. 1. 哈尔滨工业大学
    2.
  • 收稿日期:2025-10-09 修回日期:2026-02-05 出版日期:2026-02-27 发布日期:2026-02-27
  • 通讯作者: 李贤
  • 基金资助:
    国家自然科学基金青年项目;中国博士后科学基金特别资助项目

Development Status and Prospects of Multi-Modal Remote Sensing Stereoscopic Information Acquisition

  • Received:2025-10-09 Revised:2026-02-05 Online:2026-02-27 Published:2026-02-27
  • Contact: Xian Li

摘要: 遥感立体信息能够全面准确表征观测场景/目标空间三维多维度属性信息,在农作物表型提取、植被生物量估计、军事目标侦察等领域展现出巨大的应用潜力。随着遥感科学、传感器技术与人工智能迅猛发展,遥感立体信息获取已迈入多平台协同-多传感器融合-多元数据处理模式。现有综述聚焦于相对单一的平台/传感器/数据处理模式,缺少不同模式遥感立体信息获取相关综述。基于此,本文从天-空-地多平台、图像-光谱-点云多传感器、三维重建-异源配准多元数据处理模式视角,梳理总结多模遥感立体信息获取发展现状,并展望多模遥感立体信息获取未来潜在的研究方向。

关键词: 立体信息获取, 多模遥感, 多平台协同, 多传感器融合, 三维重建, 异源配准

Abstract: Remote sensing stereoscopic information can comprehensively and accurately characterize the 3D multidimensional attribute information of observed scenes or targets, demonstrating significant application potential in fields such as crop phenotype extraction, vegetation biomass estimation, and military target reconnaissance. With the rapid advancement of remote sensing science, sensor technology, and artificial intelligence, the acquisition of remote sensing stereoscopic information has transitioned into a multi-platform collaborative, multi-sensor fusion, and multivariate data processing paradigm. Existing reviews primarily focus on relatively singular platforms, sensors, or data processing modalities, lacking comprehensive overviews of remote sensing stereoscopic information acquisition across diverse modes. Based on this, this paper systematically summarizes the development status of multi-modal remote sensing stereoscopic information acquisition from the perspectives of space-air-ground multi-platform collaboration, image-spectral-point cloud multi-sensor fusion, and 3D reconstruction-heterogeneous registration multivariate data processing, while also exploring potential future research directions in Multi-Modal Remote Sensing Stereoscopic Information Acquisition field.

Key words: stereoscopic information acquisition, multi-modal remote sensing, multi-platform collaboration, multi-sensor fusion, 3D reconstruction, heterogeneous registration

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