微波遥感与红外高光谱遥感联合应用的进展与展望
doi: 10.11728/cjss2025.02.2024-0195 cstr: 32142.14.cjss.2024-0195
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李旌阳 女, 现为中国科学院国家空间科学中心助理工程师, 主要从事红外与微波遥感融合技术及精细谱微波遥感分析研究. E-mail: lijingyang@mirslab.cn -
何杰颖 女, 现为中国科学院国家空间科学中心研究员, 风云三号卫星微波湿度计与海洋卫星盐度辐射计副主任设计师、空间科学(二期)预先研究项目负责人, 主要从事星载微波辐射计设计与研制、定标技术及地球与行星探测定量反演研究. E-mail: hejieying@mirslab.cn
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Progress and Prospects of the Combined Application of Microwave Remote Sensing and Infrared Hyperspectral Remote Sensing
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摘要: 随着地球科学研究的深入, 单一遥感技术由于物理机制的限制, 难以满足复杂地球系统观测对精度、时空分辨率和数据维度的需求. 本研究对微波遥感与红外高光谱遥感的结合应用进行综述, 通过分析相关文献, 探讨了两种技术的基础原理与特性, 总结其在灾害管理和生态环境监测中的应用现状, 梳理多传感器融合的技术进展, 并分析其面临的主要挑战, 包括时空分辨率差异、多传感器校准与数据处理复杂性等问题. 研究表明, 微波与红外高光谱遥感的融合能够提升观测精度与数据覆盖范围, 为气象预报、灾害响应和生态保护提供科学支持. 未来需优化融合算法与数据处理技术, 推动融合技术向产品化和实际应用转化, 为全球气候变化与生态环境研究提供更强有力的工具.Abstract: With the advancement of Earth science research, single remote sensing technologies face limitations in meeting the demands for accuracy, spatiotemporal resolution, and data dimensions in complex Earth system observations. This study reviews the combined application of microwave and infrared hyperspectral remote sensing. Through literature analysis, the fundamental principles and characteristics of both technologies are explored, their applications in disaster management and ecological environment monitoring are summarized, and the progress and challenges of multi-sensor data fusion are examined. Challenges include spatiotemporal resolution mismatches, multi-sensor calibration, and data processing complexities. The findings demonstrate that integrating microwave and infrared hyperspectral remote sensing can improve observation accuracy and data coverage, supporting weather forecasting, disaster response, and ecological protection. Future work should focus on optimizing fusion algorithms and data processing techniques to transition from theoretical research to practical applications, providing robust tools for global climate change and environmental studies.
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图 1 (a) 15 km 分辨率微波仪器Advanced Microwaved Sounding Unit-B (AMSU-B)图像, (b) 1.9 km分辨率红外高光谱仪器Advanced Very High Resolution Radiometer (AVHRR)图像, (c)数据融合结果
Figure 1. (a) AMSU-B image with 15 km resolution, (b) AVHRR image with 1.9 km resolution, (c) data fusion result with 1.9 km resolution
表 1 代表性微波载荷参数
Table 1. Specifications of representative microwave instruments
参数 MWHS-II ATMS 频率范围/GHz 89～183 23.8～183 通道数 15 22 空间分辨率/km 15 (166, 183 GHz)
30 (89, 118 GHz)16 (165～183 GHz)
32 (50 ～ 90 GHz)
75 (23～32 GHz)
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表 2 代表性红外高光谱载荷参数
Table 2. Specifications of representative infrared hyperspectral instruments
参数 HIIRS-II AHSI LWIR MWIR SWIR VNIR SWIR 波长范围/μm 15.41～8.55 8.56～5.20 5.21～3.92 0.4～1.0 1.0～2.5 通道数 834 1207 1012 150 180 空间分辨率 14 km 30 m
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