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Detect changes in marsh plant communities based on Landsat long time series data and BFAST model
  • +3
  • yunlong yao,
  • Yuna Liu,
  • Yi Fu,
  • Xuguang Zhang,
  • Lei Wang,
  • Renping Liu
yunlong yao
Northeast Forestry University

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Yuna Liu
Northeast Forestry University
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Yi Fu
Northeast Forestry University
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Xuguang Zhang
Northeast Forestry University
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Lei Wang
Northeast Forestry University
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Renping Liu
Heilongjiang General Institute of Ecological Survey and Research
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Abstract

Due to the combined effects of human activities and climate change, freshwater wetlands, especially in agricultural watersheds, face severe degradation threats. Therefore, it is necessary to explore in depth the changes in plant communities within these wetlands. This study investigates changes in wetland plant communities within these watersheds and assesses the feasibility of the Breaks for Additive Season and Trend (BFAST) method for detecting abrupt shifts in vegetation over long time series. Using long-term Landsat imagery (1984-2016), annual maximum NDVI values were calculated for the Naolihe Basin Nature Reserve in Northeast China. The BFAST algorithm was then applied to detect NDVI changes in wetland plant communities, with results validated through field surveys. The results revealed four distinct NDVI change trends: no significant change, high-to-low shift, low-to-high shift, and continuous decline. NDVI deviations ranged from -0.85 to 0.94, with 1 to 5 abrupt changes mainly occurring between 1993 and 2006. The study confirms BFAST’s effectiveness in detecting changes in wetland plant communities and, combined with field data, proposes a conceptual model to explain the degradation processes in freshwater wetlands. The model reveals the degradation process of different vegetation types under the influence of water competition and other factors, which contributes to a more accurate understanding of vegetation change in freshwater wetlands and provides strong support for its sustainable conservation and management.
16 Aug 2024Submitted to Land Degradation & Development
19 Aug 2024Submission Checks Completed
19 Aug 2024Assigned to Editor
03 Sep 2024Review(s) Completed, Editorial Evaluation Pending
03 Sep 2024Reviewer(s) Assigned