Intelligent Remote Sensing of Ecological Environment | Views:2158Downloads:3710CSCD:9

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    • Accurately retrieving vegetation phenology at high spatial and temporal resolutions based on GEE and multi-source remote sensing data fusion

    • “In the field of vegetation phenology research, experts used the Google Earth Engine platform and ESTARFM algorithm to fuse Landsat 8 images with MODIS products, generating high-resolution EVI sequences. They verified the improvement effect of their phenological monitoring ability compared to MODIS data, and explored the factors that affect the fusion effect, providing theoretical support and data reference for refined vegetation dynamic monitoring and ecosystem research.”
      • role：First author第一作者
      • Affiliation：

        School of National Safety and Emergency Management, Beijing Normal University, Beijing100875, China

        School of Systems Science, Beijing Normal University, Beijing100875, China

      • Email：song_jie@mail.bnu.edu.cn
      • Introduction：宋杰，研究方向为植被定量遥感、物候变化监测。E-mail： song_jie@mail.bnu.edu.cn

      SONG Jie

      12,
      • role：Corresponding author通信作者
      • Affiliation：

        School of National Safety and Emergency Management, Beijing Normal University, Beijing100875, China

      • Email：zhangzhao@bnu.edu.cn
      • Introduction：张朝，研究方向为农业灾害、粮食安全以及自然灾害综合风险。E-mail： zhangzhao@bnu.edu.cn

      ZHANG Zhao

      1 * ,
      • Affiliation：

        School of National Safety and Emergency Management, Beijing Normal University, Beijing100875, China

        School of Systems Science, Beijing Normal University, Beijing100875, China

      HAN Jichong

      12
    • Vol. 28, Issue 11, Pages: 2910-2926(2024)  

    • DOI：10.11834/jrs.20232646    

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