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Based on the theory of sustainable development, in order to promote the sustainable development of population-nature-economy-society-environment in Northwest China. Taking advantage of the traction effect of superior resources and the binding effect of inferior resources, the factors under natural resources in the study area are expanded, and social and environmental factors are added to improve the traditional resource carrying capacity model. Using the improved theory and research method of relative resource carrying capacity, taking the whole country and Shaanxi Province as reference areas, the relative resource carrying capacity of Baoji City from 2010 to 2019 was calculated, and the evolution of these three factors was analyzed. The results show that: 1) Compared with the overload of resources carrying capacity in Baoji under the traditional model, the improved resource carrying capacity model shows that the relative resource carrying capacity of Baoji City is still in a surplus state. 2) The contribution rate of social resources carrying capacity and economic resources carrying capacity in Baoji city is on the rise, which is the main carrying resource of Baoji city's population. The contribution rate of natural resources carrying capacity and environmental resources carrying capacity to comprehensive resources carrying capacity is declining, and the overall resources carrying capacity is relatively balanced. 3) The comprehensive carrying capacity index of Baoji City shows a downward trend, which indicates that the surplus scale of resource carrying capacity of Baoji City is shrinking.

Innovation is the engine for the sustainable development of cities and regions, and an innovation perspective is used to study the collaborative innovation relationship between regional cities and the evolution mechanism of regional innovation network formation. Based on the social network analysis method and spatial analysis method, we explore the characteristics of the regional research cooperation network and its spatial pattern, as well as analyze the formation mechanism of the network using the exponential random graph model. The study finds that the scale of the regional innovation network is expanding, the overall network density is gradually increasing, but the nodes are loosely linked, and the regional innovation network is in the stage of deepening development. There is spatial heterogeneity in the regional innovation network, with a dumbbell-shaped distribution of “double-core dominance and central collapse”. During the formation of the regional innovation network, the endogenous structure of the innovation network is multi-connected under the path dependence, and the network development tends to be complicated; the economic strength and scientific research capability of cities and multi-dimensional proximity have a positive influence on the formation of the innovation network, and geographical proximity, social proximity and cognitive proximity can promote intra-regional innovation cooperation.