Soil thermal conductivity (STC) plays a crucial role in regulating the energy distribution of both the surface and underground soil layers. It is widely applied in various fields, including engineering design, geothermal resource development and climate change research. A rapid and accurate estimation of STC remains a key focus in the study of soil thermodynamic parameters. However, the methods for estimating STC and their distinct characteristics have yet to be systematically reviewed. In this study, we used bibliometrics to comprehensively and systematically review the literature on STC, focusing on knowledge graph characteristics to analyze the development trend of calculation schemes. The main conclusions drawn from the study are as follows: (1) In recent years, most studies have been focused on soil thermal characteristics and their main contributing factors, the soil hydrothermal process in the Qinghai-Tibet Plateau, geothermal equipment and numerical simulations, and the exploration of geothermal resources. (2) A systematic review of various schemes indicates that no single scheme is universally applicable to all soil types. Moreover, a single parameterization scheme fails to meet the practical requirements of land surface process models. We evaluated the advantages and disadvantages of the traditional heat conduction schemes, parameterization schemes, and machine learning-based schemes and the findings suggest that a comprehensive scheme that integrates these three different schemes for STC simulations should be urgently developed.

The knowledge graph based on research papers can accurately identify and present the latest developments in scientific and technological (S&T) innovation and is of great significance for supporting strategic decision-making relating to S&T innovation in undeveloped areas. Based on the international research papers produced in Gansu Province during the 13th Five-Year Plan period (2016-2020), five metrics, including the number and characteristics of papers, co-authors, main publications and their fields, major supporting institutions, and main research areas, are established herein. The results indicate that: (i) the total of 29,951 papers were published, which is about 2.89 times that in 2010-2015; (ii) Gansu Province collaborated with 149 countries/regions globally; (iii) the top 5 journals in terms of the number of papers were Medicine, Scientific Reports, RSC Advances, Science of the Total Environment, and Physical Reviews D; (iv) the funding sources were mainly from the national level; and (5) the top 5 research areas were chemistry, engineering, physics, material science, environmental science, and ecology, which accounted for 64.7% of all papers. Finally, the present study puts forward some recommendations for the decision-making process in the strategic layout of S&T innovation in Gansu Province.