Under the guidance of people-oriented development concepts, improving residents’ life satisfaction has gradually become the goal of urban governance. Based on Chinese household tracking survey data and national socio-economic statistics, this study used the entropy method, multi-layer linear regression model and geographically weighted regression model and discusses the spatial heterogeneity of the impact of objective environmental characteristics and subjective perceived characteristics of urban residential environments on residents’ life satisfaction. It is of great importance to study the mechanisms through which subjective and objective characteristics of urban human settlements influence living satisfaction among residents. It is also important to discuss how to improve living satisfaction levels through the urban human settlements and to realize high-quality urban development. The research results show that in 2018, the overall level of life satisfaction among Chinese urban residents was relatively high. However, it is still necessary to continue to optimize the urban human settlements to improve residents’ life satisfaction. The objective characteristics of the urban human settlements, such as natural environmental comfort and environmental health, have a significant positive impact on residents’ life satisfaction. Residents’ subjective perceptions of government integrity, environmental protection, wealth gap, social security, medical conditions and medical level, as well as residents’ individual gender, age and health status also have a significant impact on residents’ life satisfaction. The direction and intensity of effects of different elements of the urban human settlements and residents’ personal attributes on urban residents’ life satisfaction have different characteristics in different regions.

Vitality can effectively test the quality of regional space, put forward the concept of urban human settlement vitality, and explore the development status of urban human settlement vitality space, which is of great significance in promoting the high-quality development of urban human settlements. By constructing an evaluation index system of urban human settlement vitality and comprehensively using projection pursuit models, spatial correlation analysis, and spatial measurement models, the spatial pattern and influencing factors of the vitality of urban human settlements in the four districts of Dalian were studied. The results are as follows: (1) The spatial differentiation characteristics of the vitality of urban human settlements in Dalian are remarkable. Overall, it gradually decreased from the city center to the administrative boundary. (2) The spatial dependence of the vitality of urban human settlements among regions is relatively strong, with a more obvious “Matthew effect”. Among them, urban human settlement vitality hot spots were mainly distributed in the southeast of Dalian, showing a concentrated distribution trend, while the cold spots were distributed in the northern fringe area of Dalian, with spatial homogeneity characteristics. (3) Topography, ecological environment, social economy, commercial development, spatial structure, spatial form, regional scale, etc. have different impacts on the vitality of urban human settlements.

The suitability of human settlements is critical for quality of life and regional development. As comprehensive evaluations and research on the suitability of human settlements are lacking, a comprehensive evaluation of human settlements in the Yangtze River Delta (YRD) was carried out in 2020 by combining natural and human environmental elements based on multi-source data such as digital elevation models, Landsat remote sensing images, meteorological station data, and points of interest, other multi-source data, and constructions of the human settlements’ suitability indexes. The results showed the following: (1) The spatial suitability of the natural environment in the YRD is significantly affected by the topographic conditions and distance from the sea, showing an increasing spatial differentiation from southwest to northeast, with Shanghai and Yancheng having the best natural environment suitability. (2) The suitability of the human environment in urban areas is better than that in non-urban areas and shows a decreasing trend from the south to the north circle. Shanghai, Zhoushan, and Huaibei have the best human environment suitability. (3) The comprehensive suitability of human settlements includes both the spatial differentiation characteristics of the suitability of natural and human environments. Shanghai and Zhoushan have the mosy comprehensive suitability for human settlements, while Huaibei and Xuzhou have the worst. (4) Land with a comprehensive suitability for human settlements of greater than 0.580 accounts for 23.60% of the total and contains 30.08% of the population and 32.31% of the economy, indicating that areas with a high suitability index have been fully utilized, and the populations and economies with human settlements suitability have a high degree of matching.

The rapid urban development associated with China’s reform and opening up has been the source of many urban problems. To understand these issues, it is necessary to have a deep understanding of the distribution of urban spatial structure. Taking the six districts of Dalian as an example, in this study, we integrated the enhanced vegetation index, points of interest, and surface temperature data into night light data. Furthermore, herein, we analyze the kernel density of the points of interest and construct three indices using image geometric mean: a human settlement index (HSI), a HSI-POI (HP) index, and a HSI-POI-LST (HPL) index. Using a support vector machine to identify the land type in Dalian’s built-up area, 1000 sampling points were created for verification. Then, the threshold boundary corresponding to the highest overall accuracy of each index and kappa coefficient was selected. The relevant conclusions are as follows: As compared with the other three types of data, the HPL index constructed in this study exhibited natural and social attributes, and the built-up area extracted using this method had the highest accuracy, a high image spatial resolution, and was able to overcome the omission issues observed when using one or two data sources. In addition, this method produces richer spatial details of the actual built-up area and provides more choices for assessing small-scale urban built-up areas in future research.

An important indicator for measuring the resilience and ability of urban networks to recover under external environmental shock, which is essential for the healthy development of the region, is urban network structure resilience. Herein we analyzed the resilience of the urban network structure and explored the influencing factors of resilience in the three provinces of Northeast China. We accomplished this by utilizing the Gephi profiling social network analysis tools based on the Baidu Index, road mileage, statistical data, other multi-source data, construction information, and the transportation, innovation, and economic multiple linkage network. This analysis enabled us to propose relevant suggestions and strategies to optimize urban network structure resilience. Our results indicate that (1) in 2019, the multi-city network structure in the three provinces of Northeast China contains both commonalities and characteristics. Overall, each network demonstrates a spatial distribution pattern of “dense in the north and sparse in the south.” (2) There exist evident hierarchical differences in the resilience characteristics of the multi-city network structure in the three provinces; each provincial capital city and sub-provincial city possesses greater advantages, the innovation network exhibits the most evident hierarchy, the mismatch of the information network is the highest, and the transmission and agglomeration of the economic network are the most prominent. (3) The resilience of the urban network structure of the three provinces is the result of the interaction of several factors. Political and economic factors such as government capacity, economic status, and urban vitality are the main factors affecting the resilience of the network structure.

For megacities, they are in a period of transformation from extensive development to smart growth. Recognizing new characteristics and new changes of the residential space in megacities under the backdrop of new development has great practical significance for realizing the sustainable development of the city. As the only megacity in Northeast China, Shenyang was selected to be the research object, with 1989–2018 as the research period. The research comprehensively used multiple spatial representation methods and statistical methods to study the residential space pattern and driving factors in Shenyang City. The results showed that: (1) Residential space expansion can be divided into four stages: slow development, rapid expansion, speedy expansion, and stable extension. (2) The residential space structure presented a spatial evolution characteristic of overall expansion, forming multiple secondary core density centers. The east-west direction had a larger extension range than the northeast-southwest direction. There was an axisymmetric zonal distribution on both sides of the Hun River. (3) The agglomeration of different residential forms was obvious, and the spatial heterogeneity was increasingly stronger. (4) Urban planning measures and economic strength were the main driving forces of residential space expansion.