论文
论文题目: Deep learning-driven land cover monitoring and landscape ecological health assessment: A dynamic study in coastal regions of the China-Pakistan Economic Corridor from 2000 to 2023
第一作者: Xu Chen, Wang Juanle, Sun Yamin, Liu Meng etc.
联系作者:
发表年度: 2024
摘  要: The coastal regions of the China-Pakistan Economic Corridor (CPEC) are crucial links for the 21st Century Maritime Silk Road. Nonetheless, this region is facing significant ecological challenges due to natural disasters and intensive human activity. To effectively monitor and assess the ecological health of these critical coastal zones, this study employed integrated labels and a deep learning model to obtain land cover data spanning from 2000 to 2023. It then constructed a vigour-organisation-resilience (VOR) model with 12 assessment indicators to evaluate the landscape ecological health of this region. The evaluation results showed distinct spatial patterns. Gwadar and Ormara's Bare land areas remained Sick, while Karachi and Lower Indus' Impervious surfaces were Unhealthy with minimal fluctuations. The Lower Indus region saw Sub-healthy expansion with increased Crops areas. Lasbela was Healthy, dominated by shrub-based Other vegetation, and the Indus Delta's mangroves maintained a Very healthy state. Overall, the CPEC coastal regions were rated Unhealthy, with signs of moderate improvement. We recommend that the CPEC coastal areas focus on restoring Sick areas, promoting sustainable agriculture in Sub-healthy regions, and conserving Healthy and Very healthy areas. This study demonstrates the efficacy of deep learning and VOR model in assessing long-term ecological health, providing a valuable framework that can be applied in other coastal regions facing similar challenges.
英文摘要:
刊物名称: ECOLOGICAL INDICATORS
全文链接:
论文类别: SCI