数据融合是提升遥感影像应用能力的重要手段，一直是遥感信息处理与应用领域的研究热点。本文系统综述了遥感数据融合的进展与前瞻：首先对数据融合的层次与分类进行了总结和归纳，将遥感数据融合划分为同质遥感数据融合、异质遥感数据融合、遥感-站点数据融合、遥感-非观测数据融合4大类；在此基础上，重点针对时-空-谱光学遥感数据的融合，从多视超分辨率融合、多尺度融合、空-谱融合、时-空融合、时-空-谱一体化融合等方面进行了详细阐述；最后总结了遥感数据融合的前瞻研究方向，包括时-空-谱一体化融合的拓展、空天地观测数据的跨尺度融合、传感网环境下的在线融合、面向应用的融合方法等。

Data fusion is an important means of improving the applicability of remote sensing images, and has long been a hot research topic in the remote sensing field. This paper reviews the progress and future of remote sensing data fusion. First, the hierarchy and category of data fusion are summarized, and remote sensing data fusion methods are classified into four categories, namely, homogeneous data fusion, heterogeneous data fusion, fusion for remote sensing observation and station data, and fusion for remote sensing observation and non-observed data. Second, this paper discusses spatio-temporal-spectral fusion of optical remote sensing data, including multi-view spatial fusion, multi-scale fusion, spatio-spectral fusion, spatio-temporal fusion, and integrated spatio-temporal-spectral fusion. Third, this paper discusses the prospective direction of remote sensing data fusion literature, including the extension of integrated spatio-temporal-spectral fusion, across-scale fusion from aerospace to ground observations, online fusion in sensor web environment, and application-oriented fusion.