Ecological land evolution index: an improved approach to characterize the process of ecological land evolution

Abstract Background Ecological land evolution is pivotal in shaping regional landscapes and ecosystem functions. However, existing metrics are limited in quantifying patch-scale dynamics of connectivity and fragmentation during the processes of ecological land degradation and restoration. This study introduces the Ecological Land Evolution Index (ELEI), a novel framework integrating spatial proximity and connectivity to evaluate spatiotemporal complexities of ecological land changes at the patch level. By incorporating adjacency rules and continuous value systems, ELEI offers a granular analysis of connectivity-fragmentation tradeoffs, addressing limitations in traditional landscape metrics. Results Using four temporal land use datasets (1990–2020) from the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) in China, we applied ELEI to characterize ecological land restoration (ELR) and degradation (ELD). Sensitivity analysis confirmed ELEI’s robustness, identifying connected patch area and spatial proximity as primary drivers. Monte Carlo simulations validated formula stability, highlighting symmetrical responses to connectivity changes but residual uncertainties in extreme scenarios (|ELEI|> 60). Additionally, the results demonstrate significant spatiotemporal heterogeneity in ecological land evolution. Degradation of ecological land initially intensified from 2000 to 2010, but then decelerated from 2010 to 2020, while the restoration process first weakened and subsequently strengthened. Notably, the area of degraded ecological land steadily expanded throughout the study period, reaching 17,684.20 km 2 between 1990 and 2020, while the restored area totaled 12,025.56 km 2 . Fragmentation dominated degradation processes, while connection patterns drove restoration. Urban centers like Wuhan and Changsha experienced severe fragmentation aligned with rapid urbanization, whereas cities such as Yichang, Hengyang, and Jiujiang achieved significant restoration via infilling and connection. Conclusions ELEI provides a nuanced understanding of ecological land dynamics in rapidly urbanizing regions by identifying restoration successes and ongoing degradation hotspots. Additionally, the integration of ELEI variants (arithmetic mean ELEI (MELEI) and area-weighted mean ELEI (AWMELEI)) highlights their value in tracking long-term connectivity trends and degradation processes. This framework offers actionable insights for balancing urban development and conservation, underscoring its value in regional planning and sustainable landscape management.