Against the backdrop of global climate change and resource-environmental constraints, land ecological security is paramount to regional sustainable development. This study innovatively integrates the DPSIRM system framework with a CNN-LSTM hybrid neural network model to establish a land ecological security early warning system for China’s top 100 counties, enabling scientific diagnosis and dynamic early warning of security incidents. Findings indicate: (1) From 2010 to 2023, land ecological security conditions across counties showed continuous improvement, with the proportion of counties classified as ‘relatively safe’ or higher rising from 2% in 2010 to 68% in 2023. (2) The comprehensive early warning index exhibited a ‘stepwise leap’ trend, progressing through four stages from ‘relatively unsafe’ to ‘relatively safe’. (3) The six subsystems exhibited markedly divergent evolutionary trajectories, characterised by dual-core leadership from ‘driving-management’, fluctuating improvements in ‘pressure-impact’, and low-amplitude oscillations in ‘state-response’. (4) Over the next five years, the comprehensive early warning index will exhibit a ‘gradual stabilisation and upward trend’, yet subsystems will display a polarised pattern of ‘three rising, two stagnant, and one declining’. The early warning system developed in this study provides local decision-makers with critical leading indicators, supporting differentiated management and source-level interventions. These findings hold significant implications for refining county-level ecological governance and optimising territorial spatial patterns.

The purpose of this study is to investigate the impact of new-type urbanization on land use efficiency and its spatial spillover effects, aiming to provide theoretical support and practical references for improving land resource allocation and optimizing regional development strategies. Using panel data from 61 counties in Zhejiang Province between 2010 and 2022, this research applies a two-way fixed effects model, supplemented by mediation effect analysis and spatial econometric models, to empirically examine these relationships. The results indicate that: (1) both the level of new-type urbanization and land use efficiency show an overall upward trend, exhibiting a spatial pattern characterized by “coastal regions outperforming inland areas, and northern Zhejiang surpassing the south”; (2) new-type urbanization exerts a significantly positive impact on land use efficiency, with industrial structure upgrading serving as a partial mediator in this relationship; (3) significant spatial spillover effects are observed—new-type urbanization not only enhances local land use efficiency but also generates positive spillovers to neighboring regions through spatial diffusion mechanisms; (4) the influence of new-type urbanization on land use efficiency displays regional heterogeneity, with stronger promoting effects observed in coastal and low-efficiency areas, whereas marginal effects diminish in non-coastal and high-efficiency regions. In conclusion, strategic priorities should be established to enhance the quality of new-type urbanization, foster green and intensive development, optimize the industrial structure, and strengthen land conservation practices. Furthermore, region-specific policies are essential to improve land use efficiency across diverse areas, which will ultimately contribute to coordinated regional development.

Based on the data of foreign direct investment (FDI) and carbon emissions (CE) data in Zhejiang Province from 1995 to 2021, this article utilizes nonlinear dynamic methods to construct a nonlinear dynamic system model (FDI-CENLDS) to empirically examine the relationship between FDI and CE. The results show that: (1) A nonlinear interaction exists between FDI and CE. When carbon emissions exceed 479.41 million tons, the growth of FDI begins to inhibit the growth of carbon emissions. Carbon emissions also indirectly affect the growth of FDI. The FDI growth rate is suppressed when carbon emissions exceed 126.11 million tons. (2) The FDI-CENLDS system exhibits stable attractors. The optimal scale of FDI is 32.98228 billion USD and the optimal scale of carbon emissions is 493 million tons. There is still significant room for FDI development in Zhejiang Province compared to the optimal scale. Meanwhile, carbon emissions are slightly below the optimal scale. Therefore, it is recommended to further enhance the promotion of FDI and encourage FDI in green industries. These suggestions will enable Zhejiang Province to reduce the growth of carbon emissions, while simultaneously promoting economic development and achieving a balance between economic growth and the ecological environment.