In this paper, entropy, coupling coordination degree, spatial auto-analysis, LISA time path, and other methods have been used to analyze the coupling coordination degree of urban resilience and urbanization quality of 14 cities in Liaoning Province from 2009 to 2019. The results show that: 1. The number of highly resilient cities accounts for 14.3% of the total number of cities in Liaoning Province, and the overall resilience degree is low; the spatial distribution shrinks along the Shenyang–Dalian Economic Belt toward both sides, with obvious “core-margin” characteristics. 2. The average score of urbanization quality increased from 0.0574 to 0.0966, showing a fluctuating upward trend; the regional difference was significant, and the “dual-core” characteristic was prominent. 3. During the study period, the 14 cities of Liaoning Province were in a state of imbalance, and there was a positive correlation between the coupling degree and the coordination degree. Moran’s I decreased from 0.237 to 0.220 and the spatial agglomeration characteristics also weakened. Further analysis of the spatial and temporal linkage characteristics of the coupling relationship shows that the relative length of LISA time path presents characteristics of protrusion in the central region and shrinkage on the East and West sides, and the curvature presents characteristics that are smaller in the North and larger in the South.

The countryside is the habitat of food, ecology, and culture, and the indispensable basis for human survival and development. Assessing the spatial and temporal evolution of rural settlements contributes to the promotion of rural scientific developments. This study used the fractal theory, center-of-gravity model, and spatial syntax to analyze the spatial and temporal evolution of Shenyang Ciyutuo Subdistrict and its influencing factors based on geospatial data from 2009‒2019, from the perspectives of internal characteristics and external morphological changes. In terms of the external characteristics, from 2009‒2019, the compactness index increased from 0.414 to 0.454, the expansion rate increased from 1.17% to 3.11%, and the expansion intensity increased from 0.05% to 0.15%. From 2014‒2019, the western part of the subdistrict experienced the maximum expansion rate and expansion intensity. The center-of-gravity of the construction land shifted to the west and southwest. The internal characteristics of land use depended on geographical conditions. Clusters of rural settlements were formed in a north-south direction due to the topography and along the riverside in a band-like manner. From 2009‒2019, the integration level of the subdistrict improved and the scale and number of integration axis increased, forming a multicore tree-shaped structure. Pearson’s correlation analysis showed that urbanization is the main factor affecting the spatial and temporal land-use evolution, with transportation convenience, industrial park, and proximity to the river having little effects. This study provides a theoretical basis for the development of Ciyutuo Subdistrict and provides a reference for the development of similar commercial towns.

Biocapacity of a region exhibits spatial differences owing to the limitations of regional scale and natural conditions. Based on the multi-scale perspective, we comprehensively studied and analyzed the temporal and spatial differences of the biocapacity of a region in an attempt to establish the groundwork for optimizing urban development and its utilization framework. By adopting the ecological footprint model along with multi-scale difference evaluation method, the municipal and county scales are incorporated into a unified analysis framework in this paper, thereby facilitating the exploration of the temporal and spatial differences in the biocapacity of Shenyang—a city in China—from 2005 to 2019. The results demonstrated that: 1) At the municipal scale, the biocapacity per capita fluctuated between 1.35 hm²/person and 2.22 hm²/person. It revealed an “up-down-up” trend, which appeared consistent with the Kuznets cycle; at the county scale, the biocapacity depicted spatial differences, while those of downtown and surrounding districts/counties developed a two-level ascending hierarchical structure. 2) The time series of footprint size and depth first ascended and then declined, and can be classified into four types: closed type, inverted U-type, S-type, and M-type. Among them, S-type and M-type have the phenomenon of over-utilizing the stock capital. 3) For a long time, the regional difference of biocapacity has mostly dwelt on two scales with an evident scale effect, and the biocapacity of Liaozhong District was the worst.