Dynamic Analysis of Mangrove Forests Based on an Optimal Segmentation Scale Model and Multi-Seasonal Images in Quanzhou Bay, China

From 1990 to 2017, mangrove forests in Quanzhou Bay Estuary Wetland Nature Reserve expanded by 2.48 km², primarily converting from mudflats and Spartina, despite threats like climate change, sea-level rise, aquaculture development, and Spartina invasion. The study employed an optimal segmentation scale model combining object-oriented classification, decision trees, and visual interpretation using multi-seasonal Landsat images (1990–2017) to monitor mangrove dynamics. It demonstrated that conservation efforts, such as reforestation projects and Spartina control, significantly aid mangrove restoration and succession. This approach offers a robust framework for government policies to protect mangrove ecosystems effectively.

Lu, C., Liu, J., Jia, M., Liu, M., Man, W., Fu, W., Zhong, L., Lin, X., Su, Y., & Gao, Y. (2018). Dynamic Analysis of Mangrove Forests Based on an Optimal Segmentation Scale Model and Multi-Seasonal Images in Quanzhou Bay, China. Remote Sensing, 10(12), 2020. https://doi.org/10.3390/rs10122020