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<p>As one of the native salt marsh plants in the coastal wetland, China, <i>Suaeda salsa</i> has seriously decreased in the past four decades due to the influence of natural factors and human activities. It is emergent to master the temporal and spatial distribution and driving forces of <i>Suaeda salsa</i> for ecological restoration projects in the degraded coastal wetlands. The core area of Jiangsu Yancheng Wetland Rare Bird National Nature Reserve was taken as a study area. <i>Suaeda salsa</i> was retrieved by an integrated object-oriented and CART decision tree technique based on the time-series Landsat and Sentinel satellite images from 1985 to 2022. The temporal and spatial distribution characteristics of <i>Suaeda salsa</i> were analyzed in detail based on the transfer matrix. The driving forces were discussed from the natural factors such as <i>Spartina alterniflora</i> and <i>Phragmites australis</i>, annual temperature and annual precipitation, and human factors such as population growth, economic development, and animal husbandry and fishery, qualitative analysis of driver influence patterns by PCA modeling. The results showed that the identification accuracy of <i>Suaeda salsa</i> exceeded 87% and the Kappa coefficients varied from 0.77 to 0.92. The overall accuracy of <i>Suaeda salsa</i> based on Sentinel-2A MSI images is 6.69% higher than that of Landsat 8 OLI images when using the Dimidiate pixel model. The invasion of <i>Spartina alterniflora</i> has the most obvious effect on the spatial and temporal distribution of <i>Suaeda salsa</i>.</p>

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Spatiotemporal Dynamics Distribution and the Driving Force of Suaeda salsa in the Jiangsu Yancheng Wetland Based on Landsat and Sentinel-2 Images

  • 期刊论文

  • 发表日期：

    2026年3月7日

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  • Meng Liu,
  • Xia Lu,
  • Siyao Wu,
  • Mengqiong Xu,
  • Ke Nie

摘要

As one of the native salt marsh plants in the coastal wetland, China, Suaeda salsa has seriously decreased in the past four decades due to the influence of natural factors and human activities. It is emergent to master the temporal and spatial distribution and driving forces of Suaeda salsa for ecological restoration projects in the degraded coastal wetlands. The core area of Jiangsu Yancheng Wetland Rare Bird National Nature Reserve was taken as a study area. Suaeda salsa was retrieved by an integrated object-oriented and CART decision tree technique based on the time-series Landsat and Sentinel satellite images from 1985 to 2022. The temporal and spatial distribution characteristics of Suaeda salsa were analyzed in detail based on the transfer matrix. The driving forces were discussed from the natural factors such as Spartina alterniflora and Phragmites australis, annual temperature and annual precipitation, and human factors such as population growth, economic development, and animal husbandry and fishery, qualitative analysis of driver influence patterns by PCA modeling. The results showed that the identification accuracy of Suaeda salsa exceeded 87% and the Kappa coefficients varied from 0.77 to 0.92. The overall accuracy of Suaeda salsa based on Sentinel-2A MSI images is 6.69% higher than that of Landsat 8 OLI images when using the Dimidiate pixel model. The invasion of Spartina alterniflora has the most obvious effect on the spatial and temporal distribution of Suaeda salsa.