Acta Geodaetica et Cartographica Sinica ›› 2023, Vol. 52 ›› Issue (7): 1212-1226.doi: 10.11947/j.AGCS.2023.20220715

• Special Issue of Hyperspectral Remote Sensing Technology • Previous Articles     Next Articles

Hyperspectral with high-spatial resolution remote sensing from observation, processing to applications

ZHONG Yanfei1, WANG Xinyu2, HU Xin1,3, WANG Shaoyu4, WAN Yuting1, TANG Ge2, ZHANG Liangpei1   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
    3. Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510060, China;
    4. College of Agriculture and Life Sciences, Seoul National University, Seoul 151742, South Korea
  • Received:2022-12-29 Revised:2023-05-10 Published:2023-07-31
  • Supported by:
    The National Key Research and Development Program of China (Nos. 2022YFB3903404;2022YFB3903502); The National Natural Science Foundation of China (Nos. 42071350;42101327)

Abstract: Hyperspectral remote sensing has always been a research hotspot in the field of remote sensing. However, limited by imaging aperture and energy, it is difficult to obtain the imagery with hyperspectral and high spatial resolution at the same time, which greatly limits the application of hyperspectral remote sensing in fine-scale tasks. In recent years, with the development of hyperspectral imaging technology and new observation platforms represented by unmanned aerial vehicles, hyperspectral and high-spatial resolution (H2, with both nanometer spectral resolution and submeter spatial resolution) has developed rapidly, promoting the application of hyperspectral remote sensing technology, but at the same time, it has also brought more problems.The extremely high spatial and spectral resolution makes the data more massive and high-dimensional, increases the spatial heterogeneity and spectral variability of hyperspectral data, and brings greater challenges to intelligent image information processing. Therefore, this article reviews the application and development status of H2 remote sensing image from three aspects:H2 remote sensing image benchmark dataset, H2 remote sensing image intelligent information processing and typical application of H2 remote sensing image.

Key words: hyperspectral and high-spatial resolution remote sensing, H2 remote sensing benchmark dataset, intelligent processing and application of H2 remote sensing image

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