Mineral resources are are non-renewable precious resources and one of the basic sources of human production and life. At present, the daily work of the mineral management department involves the production of a large number of reports, maps, official document receiving and sending, transmission, examination and approval, query statistics and other work. Due to the low efficiency of data collection, analysis and supervision in all aspects of the life cycle of mining rights, the real-time supervision and management of the exploration, mining, reserves change and development and utilization of mining rights cannot be realized by the mineral regulatory authorities, so it is urgent to build an efficient mineral resource management system to meet the above challenges. This paper mainly studies the design process system of mineral resource management system based on big data technology and GIS technology, which integrates big data technology and GIS technology, covering the functions of mining right management, exploration right management, GIS map management, geological exploration management, resource reserve management, achievement resource database management, data statistical analysis management, etc. The system makes full use of the spatial analysis advantages of GIS system. The government’s mineral supervision department can effectively realize the real-time supervision of the development and utilization of mineral resources. It can also improve the refined production management ability of mineral enterprises under the current mining situation and the adaptability to market changes, and help the industrial upgrading and business model innovation of mineral enterprises.

As the global ecological environment faces serious challenges and extreme climate change threatens the survival of humankind, the promotion of green development has become the focus for all countries in the world. As one of the world’s major greenhouse gas emitters, China has put forward the “twin goals” of achieving carbon peaking and carbon neutrality and is committed to promoting the green and low-carbon transformation of its cities. As the core of economic and social development, cities are the main source of carbon emissions. In response to the dual challenges of carbon emission control and traffic growth, it is particularly important to promote the development of green transportation. With the acceleration of urbanization, urban traffic pollution is becoming more and more serious. As a zero-emission transportation mode, electric vehicles have become a key way to achieve the carbon peak and carbon neutrality targets. In order to deeply analyze the research status of electric vehicles in the field of the green and low-carbon transformation of urban transportation in China and to explore the research hot spots, evolution trends, and their roles and strategies in the construction of green transportation networks, this paper uses the CiteSpace, VOSviewer, and Tableau analysis tools to review and analyze the 2460 articles and reviews in the Web of Science Core Collection (WOS) and 2650 articles and reviews in the China National Knowledge Infrastructure (CNKI), including the “publication volume and publication trend”, “subject citation path”, “countries cooperation and geographical distribution”, “author cooperation and institution cooperation”, “keyword co-occurrence and keywords clusters”, and the “evolution trend of research hot spots in timeline”. The results show that: (1) Since 2010, the research focus on electric vehicles has gradually increased, and especially in the past three years, the number of such publications has increased significantly. (2) China holds the lead in research output regarding electric vehicles and related fields, but its international cooperation needs to be strengthened. (3) In recent years, the research has focused on “energy transformation”, “energy-saving technology”, “carbon emissions”, “battery recycling”, and other relevant topics. The promotion and development of electric vehicles will continue to usher in new opportunities concerning technological innovation, policy support, and market expansion. Finally, based on the research hot spots and evolution trends of electric vehicles in the field of urban green transportation and low-carbon transportation in China, this paper discusses the key paths and strategies for electric vehicles to promote the transformation of urban transportation in China to green and low-carbon types and looks forward to future research directions. The research in this paper can provide theoretical support and practical guidance for China to promote electric vehicles, build low-carbon cities, and realize green transportation. It is expected to act as a useful reference for relevant policy formulation and academic research.

The construction of smart cities, as a key driving force for the low-carbon transformation of the economy, urgently needs a systematic assessment of its carbon emission reduction potential. Based on the panel data of 277 cities in China from 2007 to 2021, this study adopts innovative methods, integrates bibliometric analysis, and employs empirical models to deeply explore the impact of smart city construction on carbon emissions and its regional heterogeneity and resource endowment heterogeneity. The main findings are as follows: (1) The research on smart cities and carbon emissions present knowledge synergy, focusing on innovation and green development strategies. (2) A series of robustness tests show that smart city construction can significantly reduce urban carbon emissions. (3) Heterogeneity analysis reveals that the carbon emission reduction effect varies between regions (more significant in the northern region) and with resource endowments (non-resource-based cities are more advantageous). The important contribution of this study lies in its quantitative assessment of the carbon emission reduction effect of smart city construction, as well as its heterogeneity; this study also provides a solid empirical basis for formulating more targeted regional smart city development policies.