Major contribution to carbon neutrality by China’s geosciences and geological technologies

In the context of global climate change,geosciences provide an important geological solution to achieve the goal of carbon neutrality,China’s geosciences and geological technologies can play an important role in solving the problem of carbon neutrality.This paper discusses the main problems,opportunities,and challenges that can be solved by the participation of geosciences in carbon neutrality,as well as China’s response to them.The main scientific problems involved and the geological work carried out mainly fall into three categories:(1)Carbon emission reduction technology(natural gas hydrate,geothermal,hot dry rock,nuclear energy,hydropower,wind energy,solar energy,hydrogen energy);(2)carbon sequestration technology(carbon capture and storage,underground space utilization);(3)key minerals needed to support carbon neutralization(raw materials for energy transformation,carbon reduction technology).Therefore,geosciences and geological technologies are needed:First,actively participate in the development of green energy such as natural gas,geothermal energy,hydropower,hot dry rock,and key energy minerals,and develop exploration and exploitation technologies such as geothermal energy and natural gas;the second is to do a good job in geological support for new energy site selection,carry out an in-depth study on geotechnical feasibility and mitigation measures,and form the basis of relevant economic decisions to reduce costs and prevent geological disasters;the third is to develop and coordinate relevant departments of geosciences,organize and carry out strategic research on natural resources,carry out theoretical system research on global climate change and other issues under the guidance of earth system science theory,and coordinate frontier scientific information and advanced technological tools of various disciplines.The goal of carbon neutrality provides new opportunities and challenges for geosciences research.In the future,it is necessary to provide theoretical and technical support from various aspects,enhance the ability of climate adaptation,and support the realization of the goal of carbon peaking and carbon neutrality.

A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.

Data-enhanced revealing of trends in Geoscience

Purpose:This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023.By integrating bibliometric analysis with expert insights from the Deep-time Digital Earth(DDE)initiative,this article identifies key emerging themes shaping the landscape of Earth Sciences①.Design/methodology/approach:The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database.To map relationships between articles,citation networks were constructed,and spectral clustering algorithms were then employed to identify groups of related research,resulting in 407 clusters.Relevant research terms were extracted using the Log-Likelihood Ratio(LLR)algorithm,followed by statistical analyses on the volume of papers,average publication year,and average citation count within each cluster.Additionally,expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation,relevance,and impact within Geosciences,and finalize naming of these top trends with consideration of the content and implications of the associated research.This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists.Findings:Thirty significant trends were identified in the field of Geosciences,spanning five domains:deep space,deep time,deep Earth,habitable Earth,and big data.These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society,science,and technology.Research limitations:The analyzed data of this study only contain those were included in the Web of Science.Practical implications:This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science,especially on solid earth.The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study.Originality/value:This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.

Machine learning in geosciences and remote sensing

Learning incorporates a broad range of complex procedures. Machine learning（ML） is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficultto-program applications, and software applications. It is a collection of a variety of algorithms（e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.） that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore,nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

Climate change impacts on environmental geosciences: Introduction

Climate change and its impacts have become topical issues of global news,scientific research and conferences.Environmental Geosciences incorporate the various disciplines of geosciences and their multifaceted interactions with life.Research discussions on the interaction of climate change,geosciences and environment may often be blur,and Schmidt-Thoméet al.(2010)stated that“Often past climate changes that can be deduced from geological records may help in understanding the speed of potential climate change effects,i.e.how quickly have sea levels changed,how drastic has nature reacted to ups and downs in temperature,etc.These analyses of past events help in giving outlooks on potential changes in our living environment.It is also of important to understand the magnitude and potential effects of extreme events,such as droughts and floods”.

Progress of machine learning in geosciences:Preface

In the past two decades, artificial intelligence （AI） algorithms have proved to be promising tools for solving several tough scientific problems, As a broad subfield of AI, machine learning is concerned with algorithms and techniques that allow computers to ＂learn＂. The machine learning approach covers main domains such as data mining, difficult-to-program applications, and soft- ware applications. It is a collection of a variety of algorithms that can provide multivariate, nonlinear, nonparametric regression or classification. The remarkable simulation capabilities of the ma- chine learning-based methods have resulted in their extensive ap- plications in science and engineering. Recently, the machine learning techniques have found many applications in the geoscien- ces and remote sensing. More specifically, these techniques are proved to be practical for cases where the system＇s deterministic model is computationally expensive or there is no deterministic model to solve the problem （Lary, 2010）.

Recent progress in submarine geosciences in China

In China submarine geosciences represents a newly established discipline of oceanography, focusing on the oceanic lithosphere, and its interface with the hydrosphere and biosphere. Recently, supported by the National High Technology Research and Development Program and other high-tech development projects, significant progress has been made in the development of advanced technologies and equipment. This en- ables the scientists in China to carry out explorations of the international seabed area in the Pacific Ocean and on the Southwest Indian Ridge. In addition, they have been active in the research activities associated the mid-ocean ridges and western Pacific marginal seas. It is anticipated that this research field will continue to be highly fruitful in the near future.

Special Issue of Mathematical Geosciences for the 33^(rd) IGC

The papers published in this issue are selected from manuscripts submitted by invited authors and most of these papers will be presented at the 33^rd International Geological Congress （33^rd IGC） in Oslo, August 2008. It receives 25 manuscripts and 16 were accepted after going through the journal normal peer reviewing process. The topics of the papers cover various aspects of ＂metallogenic complex processes and mineral resource quantitative assessment＂, one of the strategic research areas of the State Key Laboratory of Geological Processes Resources （GPMR） sponsored by the Science and Technology and the and Mineral Ministry of Ministry of Education of China. Researches in the area are also supported by the National Natural Science Foundation and Ministry of Land and Resources of China as well as by mining companies. Thanks are due to these funding programs and organizations for supporting the research activities of GPMR. Sincere thanks are due to those who have reviewed the manuscripts and provided critical comments and even English editing of some of the papers. We are very appreciated for the assistance of the editorial office especially Professor Wang, the editor-in-chief, Ms. Yuan and many others who have worked hard to make this issue be printed before the event of 33^rd IGC. Special thanks are given to Professor Xie Shuyun, Xu Deyi and Tali Neta and many other members in the Geomatics Research Lab of York University for handling the manuscripts during the reviewing processes.

An Introduction to China University of Geosciences(Beijing)

China University of Geosciences（Beijing）（CUGB）,is one of the leading universities listed in"Project 211,"a national program that offers more government financial support for the advancement of 100 top national universities in 21st-century China.CUGB is also supported by the Ministry of Education for its uniquely strong strengths in geological disciplines.CUGB could be traced back to the former Beijing College of Geology,which was founded in 1952 by combining the Departments of Geology from Peking University, Tsinghua University,Tianjin University and Tangshan Railway College.In 1987,the predecessor of CUGB was renamed China University of Geosciences（Beijing）.

China University of Geosciences in Beijing

FOUNDED in 1952, China University of Geosciences in Beijing （CUGB） is a national key university under the direct auspices of the Ministry of Education. Over the past 60 years, it has developed from a geological college tbcused on a single discipline to a multi- disciplinary comprehensive university, offering courses in geology, natural resources, environment and geological engineering.

从国际文献统计解读地理信息科学发展趋向

针对GIS国际顶级期刊《International Journal of Geographic Information Science》，辅以《Computers ＆ Geosciences 》2001～2010年10 a来发表的文献进行统计，找出我国与美国、加拿大、德国等发达国家的差距，总结我国论文的作者、机构等分布特征，了解分析GIS技术国内外10 a来的发展动态和趋势，为我国地球空间信息技术发展提供参考和依据。

GTP-based Integral Real-3D Spatial Model for Engineering Excavation GIS

Engineering excavation GIS (E 2 GIS) is a real-3D GIS serving for geosciences related to geo-engineering, civil engineering and mining engineering based on generalized tri-prism (GTP) model. As two instances of GTP model, G\|GTP is used for the real\|3D modeling of subsurface geological bodies, and E\|GTP is used for the real\|3D modeling of subsurface engineering excavations.In the light of the discussions on the features and functions of E 2 GIS, the modeling principles of G\|GTP and E\|GTP are introduced. The two models couple together seamlessly to form an integral model for subsurface spatial objects including both geological bodies and excavations. An object\|oriented integral real\|3D data model and integral spatial topological relations are discussed.

Application of 3-D Geoscience Modeling Technology for the Estimation of Solid Mineral Reserves

Applying new approaches, methods, and technologies for the estimation of reserves can effectively improve the efficiency and accuracy of assessments of solid mineral resources. After analyzing the development of 3-D geoscience modeling technology （3-D GMT）, this paper discusses the application of 3-D GMT for the estimation of solid mineral reserves, emphatically introducing its workflow and two key technologies, 3-D orebody surface modeling, and property modeling. Moreover, the paper analyzes the limitations of traditional methods, such as the section method and geological block method, and points out the advantages of 3-D GMT： building more accurate 3-D orebody models, expressing the internal inhomogeneous attributes of an orebody, reducing the potential for errors in the estimation of reserves, and implementing dynamic estimations of reserves.