Bulletin of Surveying and Mapping ›› 2025, Vol. 0 ›› Issue (1): 35-41.doi: 10.13474/j.cnki.11-2246.2025.0107

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Spatial information enhancement in FY-3D MERSI-Ⅱ images and application validation through lake monitoring

MIAO Shunxia1, SUN Kaimin1,2, HU Xiuqing2,3, QU Jianhua4   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. Innovation Center for Xu Jianmin Meteorological Satellite, Beijing 100081, China;
    3. China Meteorological Administration, Beijing 100081, China;
    4. Beijing Huayun Shinetek Company, Beijing 100081,China
  • Received:2024-04-24 Published:2025-02-09

Abstract: The medium-resolution imaging spectrometer (MERSI-Ⅱ), a key payload on the Fengyun-3D (FY-3D) satellite, provides essential data for ecological monitoring through high-frequency, multi-band observations over extensive areas. While primarily focusing on L1-level swath observations, MERSI-Ⅱ offers limited downstream products including surface reflectance and ecological parameter retrieval. This study develops an innovative image spatial enhancement method tailored to MERSI-Ⅱ's imaging characteristics. By efficiently leveraging redundant scanning observations to eliminate the Bowtie effect, this method ensures quantitative integrity while achieving tonal and spatial coherence. It effectively converts L1-level digital signals(DN) into geospatially comprehensive, high-quality surface reflectance data. The accuracy of lake monitoring depends on factors like image resolution, positioning accuracy, and imaging quality. To validate the effectiveness of our approach, we analyze 96 lakes in the Tibetan Plateau region. Using Landsat 8 OLI water extraction as a reference, our enhanced images demonstrated average extraction errors below 3.5% for large lakes(≥550 km2) and under 6.5% for small to medium-sized lakes(<550 km2). Overall, the application of spatial information enhancement improved the monitoring accuracy for all sample lakes by 3.62% compared to conventional imagery.

Key words: Fengyun-3 satellite, image processing, MERSI sensor, lake monitoring, water area inversion, Landsat 8

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