Urbanization is the development trend of all countries in the world, but it has caused considerable ecological problems that need to be alleviated by building ecological security patterns. This study took Ningbo as an example to construct and optimize an ecological security pattern. We analyzed land use types, normalized difference vegetation index, and landscape connectivity for ecological sources selection. In constructing the resistance surface, we considered natural and socio-economic factors. On this basis, we identified ecological corridors based on a minimum cumulative resistance model. Finally, the ecological security pattern was optimized through space syntax. Results showed that Ningbo has 18 ecological sources, with an area of 3,051.27 km2 and 29 ecological corridors, with a length of 1,172.18 km. Among them, 11 are first-level, 10 are second-level, and 8 are third-level corridors. After optimization, the area and protection cost of the ecological security pattern were significantly reduced, which can effectively alleviate the trade-off between ecological protection and economic development. This research can provide a reference for the construction and optimization of ecological security patterns and has reference significance for ecological protection in rapidly urbanized areas.

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Soil wind erosion is a global problem that leads to increasingly serious regional land degradation, where the need for windbreak and sand fixation services (WSFS) is substantial. Inner Mongolia plays an important role in global semiarid and arid areas and the severe land degradation resulting from soil wind erosion warrants an urgent solution. However, the mechanism of influence of various driving factors on windbreak and sand fixation services is still not fully studied. In this paper, the revised wind erosion equation (RWEQ) model was used to synthesize the monthly spatiotemporal dynamics of soil wind erosion modulus (SWEM) and WSFS in Inner Mongolia from January 2000 to February 2020 from a semi-monthly scale. The influencing factors of WSFS were examined from both natural and anthropogenic aspects. Results show that over the past 20 years, the average SWEM in Inner Mongolia was 118.06 t ha−1 yr−1, the areas with severe wind erosion were mainly concentrated in the desert areas in the southwest of Inner Mongolia, and the forests in the northeast suffered less soil wind erosion. Meanwhile, the average WSFS was 181.11 × 108 t yr−1, with the high-value areas mainly located in major deserts, sandy land, and the area bordering Mongolia in the north and the low-value areas mainly located in the densely forested northeast and the Gobi Desert in the northwest. Both SWEM and WSFS showed a clear downward trend and a certain periodicity over the past 20 years. WSFS showed two peaks a year (April and October). Among the natural factors, precipitation and NDVI showed a significant correlation with WSFS and were identified as the main driving factors of WSFS, whereas temperature had no significant correlation. Among the anthropogenic factors, farming and animal husbandry intensity and GDP showed a positive correlation with WSFS, whereas population showed a negative correlation. These four types of factors were identified as socio-economic factors that drive WSFS. Meanwhile, WSFS did not show any significant correlation with the administrative area. Land use change contributed to a large proportion of WSFS change, thereby suggesting that the intensity of human activities is another central driver of WSFS.

The advancing global urbanization puts great pressure on the society and ecosystem, especially in developing countries. Reasonable land‐use policies adapted to local conditions are the key issues to prevent disordered urban expansion. Multi‐scenario simulation provides a new perspective for differentiated policy formulation based on regional heterogeneity. Regarding the Shaanxi Province, a rapid urbanized area with high spatial heterogeneity in western China, as the study case, we tracked its past land‐use changes and predicted the characteristics of urban expansion using the Future Urban‐Regional Environment Simulation model. We found that (1) during the past 35 years, built‐up land evidently increased accompanied by the loss of cropland, grassland, and unused land. (2) The urban expansion mainly will occur in the areas with flat terrain under three scenarios. (3) The urban expansion will transit into the “requiring land from mountains” pattern in the future, which means that it will gradually spread to areas with higher slopes. (4) Differentiated and optimal development patterns are proposed for different subregions by accounting the loss of ecosystem service in the procedure of urban expansion. This research can help local governments formulate differentiated future macro control of territorial spatial planning to optimize subregional land development.