The construction industry is the backbone of most countries, but its carbon emissions are huge and growing rapidly, constraining the achievement of global carbon-peaking and carbon-neutrality goals. China’s carbon emissions are the highest in the world, and the construction industry is the largest contributor. Due to significant differences between provinces in pressure, potential, and motivation to reduce emissions, the “one-size-fits-all” emission reduction policy has failed to achieve the desired results. This paper empirically investigates the spatial and temporal evolution of carbon emissions in China’s construction industry and their decoupling relationship with economic growth relying on GIS tools and decoupling model in an attempt to provide a basis for the formulation of differentiated construction emission reduction policies and plans in China. The study shows that, firstly, the changes in carbon emissions and carbon intensity in the provincial construction industry are becoming increasingly complex, with a variety of types emerging, such as declining, “inverted U-shaped”, growing, “U-shaped”, and smooth fluctuating patterns. Secondly, the coefficient of variation is higher than 0.65 for a long time, indicating high spatial heterogeneity. However, spatial agglomeration and correlation are low, with only a few cluster-like agglomerations formed in the Pearl River Delta, Yangtze River Delta, Bohai Bay, Northeast China, and Loess and Yunnan–Guizhou Plateau regions. Thirdly, most provinces have not reached peak carbon emissions from the construction industry, with 25% having reached peak and being in the plateau stage, respectively. Fourthly, the decoupling relationship between carbon emissions from the construction industry and economic growth, as well as their changes, is increasingly diversified, and most provinces are in a strong and weak decoupling state. Moreover, a growing number of provinces that have achieved decoupling are moving backward to re-coupling, due to the impact of economic transformation and the outbreaks of COVID-19, with the degraded regions increasingly concentrated in the northeast and northwest. Fifthly, we classify China’s 30 provinces into Leader, Intermediate, and Laggard policy zones and further propose differentiated response strategies. In conclusion, studying the trends and patterns of carbon-emission changes in the construction industry in different regions, revealing their spatial differentiation and correlation, and developing a classification management strategy for low carbonized development of the construction industry help significantly improve the reliability, efficiency, and self-adaptability of policy design and implementation.

By constructing a rural revitalization index evaluation system and using measurement models and software such as AHP, the entropy method, the BCG matrix, and GeoDetector, this paper quantitatively analyzed the evolution mode and driving mechanism of rural revitalization performance based on the research of 131 cities and autonomous prefectures in western China to further put forward relevant policy suggestions and establish a new framework that integrates “performance evaluation, evolution model, driving mechanism, and management strategy”. Findings: firstly, rural revitalization in western China showed slow development and significant regional heterogeneity, with a coefficient of variation of 0.46 or even higher; secondly, the different dimensions of rural revitalization and development varied greatly, with the order being: thriving businesses (about 0.04) < effective governance (about 0.06) < pleasant living environment (about 0.09) < social etiquette and civility (about 1.0) < prosperity (about 0.23); thirdly, the growth and decline of rural revitalization performance coexisted in the context of rapid development in western China, and the evolution was in diversified patterns; fourthly, there were many factors affecting the change of rural revitalization performance, and different factors exhibited significant synergistic effects with each other, with super-interacting factor pairs having a force of over 0. 7 (maximum 1), including permanent population, urbanization rate, added value of primary industry, and per capita GDP as key factors; fifthly, based on the superposition analysis of the evolution pattern and driving forces of rural revitalization, western cities are classified into 8 types (including external assistance zone, general development zone, general retention zone, general demonstration zone, internal governance zone, important development zone, important retention zone, important demonstration zone) for establishment of a zoning planning and management system and design of differentiated development policies, providing a basis for “evidence-based decision-making” for the government.

(1) Background: Digitalization is the key to sustainable village development, posing a new challenge for village planning, construction, and governance in all countries. The construction of digital villages is currently in the stage of experimentation and exploration; China is the largest developing country and a pioneer in the digitization of villages. (2) Methods: Based on a combination of the Boston Consulting Group Matrix and GeoDetector, we conducted an empirical study on 70 counties in Guangxi, aiming to analyze the construction level, evolution model, and driving mechanism of digital villages and to provide a basis for decisions on government investment and social participation. (3) Results: First, Conspicuous disequilibrium in rural digitalization has manifested in Guangxi, and counties at different levels (leader, follower, and straggler) show significant clustering and correlation effects in their geographical distribution. Second, digital village construction in Guangxi has evolves in diversified modes (divided into four types: star, gazelle, cow, and dog), with hot and cold areas forming a center–periphery structure. Third, rural digitalization has a very complex driving mechanism, with high heterogeneity in the direct influencing factors, significant synergistic enhancement of factors, and nonlinear enhancement dominating the interaction’s relationship. (4) Conclusions: According to the results of analysis, we suggest highlighting the government-driven mechanism and regional linkage in the construction of digital villages, formulating differentiated management policies and development plans based on the combination of top-level design and grassroots innovation, establishing joint meetings or development associations and service alliances, and stimulating the enthusiasm of the whole of society, especially farmers and enterprises, in order to achieve rapid and sustainable rural digitalization.

(1) Background: China is beginning to see increasingly complex real estate development dynamics as urbanization, industrialization and globalization advance. As a key driver of economic and social development in China’s cities, real estate has created prosperity while facing the risk of capitalization and a “hard landing”, making it increasingly difficult to bring it under control. (2) Methods: a new approach that integrates “evolution dynamics–driving mechanism–policy design” is constructed based on the Boston Consulting Group matrix, exploratory spatial data analysis, GIS and Geodetector, and this paper empirically studies the dynamics and driving mechanism of real estate development based on the case study of small county-level cities in Gansu, China. (3) Results: Firstly, real estate development in Gansu is characterized by significant spatial differentiation, heterogeneity and autocorrelation, and its distribution pattern comes into being from unsynchronized macroeconomic, population, social, industrial, institutional and policy development interweaved with the real estate control. Secondly, the real estate is diversified in spatiotemporal evolution models, and the cold and hot cities of different models are in quite different geographical patterns with high spatial agglomeration. Thirdly, there are many driving factors affecting the distribution patterns in real estate. These factors are in complex relationships and they are classified into three categories of “Scale–Contribution–Comprehensive”-oriented driving factor and three sub-categories of “Key–Important–Auxiliary” factors. Fourthly, the factors show large differences in the interaction effects, with the real estate industry scale influencing factors being dominated by bifactor enhancement and the economic contribution influencing factors being dominated by non-linear enhancement. Notably, factors such as permanent resident population, urbanization and government revenue have a strong direct influence on the industry scale and economic contribution of real estate, and factors such as expenditure, output value of industry, urbanization rate and number of secondary schools all have a strong interactive influence. (4) Conclusions: The cities are divided into four policy areas of comprehensive development, contribution improvement, scale growth and free decision. Furthermore, differentiated and adaptive measures are proposed for each zoning, which significantly improves the accuracy and synergy of urban real estate management.

In the era of the urban economy and service economy, the decoupling of service industry land expansion from economic growth has always been a key measure to evaluate sustainable and healthy development. Based on the decoupling model and GIS spatial analysis method, this paper conducted an empirical study of Chinese cities from 2012 to 2019. Results: (1) Increasing spatial heterogeneity, correlation and agglomeration of land expansion were found in China’s urban service industry and its economic growth; (2) Most cities were in weak decoupling, with evolved, degraded and unchanged cities accounting for one-third each, and the number of cities in negative decoupling was increasing, leading to increasingly diverse and complex decoupling relationships; (3) From the perspective of changes in the urban service industry land and its decoupling from economic growth, HH cities were clustered in the Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei and Chengdu–Chongqing urban agglomerations in a continuous belt pattern, while LL and HL cities were mostly in the north, especially in the northeast, creating many cluster-like agglomerations that have become problematic spaces; (4) A significant synergistic effect was identified between the factors of urban permanent population, value added of the secondary industry, per capita GDP, government financial expenditure, international trade, foreign direct investment, total retail of commodities, and authorized patents, with factor pairs formed showing nonlinear enhancement. The factor value added of the secondary industry had the largest direct impact, while urban permanent population and foreign direct investment led in terms of net synergies; (5) It is recommended to introduce classified and differentiated urban service industry land use policies, plan and build a number of national, provincial and municipal modern service industry clusters, demonstrate changes in land supply and use, build a scientific and efficient land resource allocation and management system, guard against and prevent recoupling and effectively improve the ability of cities to achieve high-quality economic development.

The protection and utilization of architectural heritage requires the synergistic cooperation of multiple interest groups. Tourists’ perception of the value of architectural heritage will determine how much attention and support they pay to heritage protection, which in turn affects their participation and willingness to pay. This paper establishes the value perception evaluation system of architectural heritage for Kumbum Monastery in China, quantifies tourists’ willingness to pay for heritage protection, and applies an interpretable machine learning model to analyze the causal relationship between value perception and willingness to pay, thereby providing a scientific basis for architectural heritage protection and utilization. According to the findings, tourists’ perceptions of the value of Kumbum Monastery are significantly differentiated, with a willingness to pay for the preservation of its architectural heritage ranging from RMB (China’s currency) 136 to RMB 203. The value perception of the architectural heritage of Kumbum Monastery has a non-linear and complex influence on the willingness of tourists to pay. Engineers responsible for heritage protection projects, heritage managers (government), and tourism development companies should establish a design system for architectural heritage protection and utilization based on value perception over time and introduce positive design, negative design, and zero design strategies as needed to enhance the willingness of tourists to pay for the protection of the architectural heritage of Kumbum Monastery.