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This paper analyses the phenology metrics of the Oueme-Boukou Forest Reserve in the centre of Benin using Sentinel-1 data. Radar Vegetation Index (RVI) under the Digital Earth sandbox measured the presence and amount of vegetation in the forest. RVI was plotted over time between January 2019 and December 2023, and used to generate per-pixel-based phenology statistics related to parameters such as the start of the season (SOS), the peak of the season (POS), the end of the season (EOS), the value at the start of the season (vSOS), the value at peak of the season (vPOS), the value at end of the season (vEOS), the length of the season (LOS), the amplitude of season (AOS), rate of greening (ROG), and the rate of senescence (ROS). Results showed that some parts of the forest are illegally used for agriculture. The plotting of RVI over time reveals a variation in the planting cycle, aligning with the season and even the month. At the beginning of each year, which coincides with the dry season, RVI values generally witness a decline during the period considered (January 2019 to December 2023). The highest values of the RVI are observed around river channels or water bodies. The rate of senescence appears to be very low, varying between −0.01 and 0.00, which is attributed to the presence of water channels and humidity. These results demonstrate that active remote sensing can provide valuable information for monitoring forest reserves.

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Remote Sensing-Based Analysis of Phenology Metrics in Oueme-Boukou Forest Reserve, Benin Republic

  • 会议论文

  • 发表日期：

    2026年

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  • Joseph Oloukoi,
  • Momodou Soumah,
  • Sena Ghislain C. Adimou,
  • Hubert O. Yadjemi,
  • Edwards Boamah

摘要

This paper analyses the phenology metrics of the Oueme-Boukou Forest Reserve in the centre of Benin using Sentinel-1 data. Radar Vegetation Index (RVI) under the Digital Earth sandbox measured the presence and amount of vegetation in the forest. RVI was plotted over time between January 2019 and December 2023, and used to generate per-pixel-based phenology statistics related to parameters such as the start of the season (SOS), the peak of the season (POS), the end of the season (EOS), the value at the start of the season (vSOS), the value at peak of the season (vPOS), the value at end of the season (vEOS), the length of the season (LOS), the amplitude of season (AOS), rate of greening (ROG), and the rate of senescence (ROS). Results showed that some parts of the forest are illegally used for agriculture. The plotting of RVI over time reveals a variation in the planting cycle, aligning with the season and even the month. At the beginning of each year, which coincides with the dry season, RVI values generally witness a decline during the period considered (January 2019 to December 2023). The highest values of the RVI are observed around river channels or water bodies. The rate of senescence appears to be very low, varying between −0.01 and 0.00, which is attributed to the presence of water channels and humidity. These results demonstrate that active remote sensing can provide valuable information for monitoring forest reserves.