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In the development of meteorological detection technology and services, weather radar undoubtedly plays a pivotal role, especially in the monitoring and early warning of severe convective weather events, where it serves an irreplaceable function. This research delves into the landscape of weather radar research from 1945 to 2024, employing scientometric methods to investigate 13,981 publications from the Web of Science (WoS) core collection database. This study aims to unravel, for the first time, the foundational structures shaping the knowledge domain of weather radar over an 80-year period, exploring general features, collaboration, co-citation, and keyword co-occurrence. Key findings reveal a significant surge in both publications and citations post-1990, peaking in 2022 with 1083 publications and 13832 citations, signaling sustained growth and interest in the field after a period of stagnation. The United States, China, and European countries emerge as key drivers of weather radar research, with robust international collaboration playing a pivotal role in the field's rapid evolution. Analysis uncovers 30 distinct co-citation clusters, showcasing the progression of weather radar knowledge structures. Notably, deep learning emerges as a dynamic cluster, garnering attention and yielding substantial outcomes in contemporary research efforts. Over eight decades, the focus of weather radar investigations has transitioned from hardware and software enhancements to Artificial Intelligence (AI) technology integration and multifunctional applications across diverse scenarios. This study identifies four key areas for future research: leveraging AI technology, advancing all-weather observation techniques, enhancing system refinement, and fostering networked collaborative observation technologies. This research endeavors to support academics by offering an in-depth comprehension of the progression of weather radar research. The findings can be a valuable resource for scholars in efficiently locating pertinent publications and journals. Furthermore, policymakers can rely on the insights gleaned from this study as a well-organized reference point. [ABSTRACT FROM AUTHOR]

The meteorological data of 38 meteorological stations in Xinjiang, Gansu and other regions in northwest China from 1971 to 2020 were used to analyze the temporal and spatial change characteristics of temperature by the Mann-Kendall test method, and the future change trend of temperature was evaluated by the Hurst index method, and the temporal and spatial changes of temperature in this region were compre)hensively analyzed according to the spatial changes. The results showed that overall, the temperature in the entire northwest region showed an increasing trend during the study period. From the perspective of future trend, the temperature in the northern part of Xinjiang also showed the opposite trend to the past, while other regions showed strong consistency with the past. According to the above results, in the 21st century, the temperature most area of Northwest China would continue to increase, only the Northern part of Xinjiang would become colder in the future. [ABSTRACT FROM AUTHOR]

Urbanization is a crucial indicator which reflects the socio-economic development of a country or region. The regions across the Taiwan Strait (TSR) have garnered attention worldwide as being representative of typical urbanization development along the southeastern coast. Currently, research in the TSR predominantly focuses on individual regions, with limited academic achievements comparing urbanization paths across the strait. In particular, the domain of comparative analysis of the spatiotemporal characteristics of urbanization dynamics in TSR by using long time series of nighttime light data remains largely underexplored. Therefore, this study focused on comparing the urbanization paths in the TSR and analyzing the spatiotemporal characteristics of urbanization by using the long-term nighttime light data from 1992 to 2020. Additionally, some methods such as Theil–Sen median trend analysis, Mann–Kendall significance test, Hurst exponent, spatial statistics, and time series were used to quantitatively analyze the spatial distribution patterns and temporal trends of nighttime lights in the TSR since 1992. The results were as follows: (1) From 1992 to 2020, the spatial distribution of nighttime light data in TSR exhibited significant spatial heterogeneity, with high-value areas mainly located in southeastern Fujian and northwestern Taiwan, while low-value areas were concentrated in Fujian's inland regions; (2) During this period, nighttime lighting data increased from 729,863 in 1992 to 2,729,052 in 2020, and the percentage of its high-value (40–063) increased from 2.59% in 1992 to 12.22% in 2020; (3) Comparison of nighttime light data across representative cities from Taiwan (Taipei, Hsinchu) and Fujian (Xiamen, Fuzhou) uncovered distinct growth patterns—while Taiwanese cities had a high initial brightness value (the lowest value in the last 30 years was 518,379.4), their growth was relatively slow (average growth rate of 17%); Fujian cities, on the other hand, started from lower initial brightness value (the lowest value in the last 30 years was 35,123.1), but displayed substantial growth vigor (average growth rate of 222%); (4) During the study period, the nighttime light data of the vast majority of cities in the TSR demonstrated a significant increasing trend, particularly in coastal areas and urban centers; (5) Predictions of future trend variation suggest that the significantly increasing trend of cities surrounding Taiwan's primary metropolitan areas will intensify, whereas metropolitan regions such as Keelung may witness a decline in future trend variations. However, only a mere 0.03% of the nighttime light data show a significant decreasing trend. Additionally, there are distinct differences in the urbanization development stages of the TSR. Fujian is currently undergoing rapid urbanization, while Taiwan's urbanization has entered a stable stage. The study reveals that factors such as geographical location, natural resources, transportation infrastructure, population size, and industrial structure collectively influence the urbanization characteristics of the TSR. This research bears substantial significance for deepening the comprehension of the patterns and processes of urbanization development in the TSR and provides valuable insights for urban construction and development across the strait. [ABSTRACT FROM AUTHOR]

This study comprehensively analyzes the spatiotemporal distribution of the meteorological variables and large-scale atmospheric patterns that produce high concentrations of particulate matter with aerodynamic diameters below 2.5 μm (PM 2.5) in South Korea. Through self-organizing map (SOM) analysis of upper-level geopotential height fields and aerosol optical depth (AOD), the recurring coupled patterns of the large-scale circulation and the AOD are classified into three clusters associated with high pollution episodes that frequently occur in spring and winter. In addition, the long-range transport is investigated for each SOM type using the Hybrid Single-Particle Lagrangian Integrated Trajectory model, which provides a comprehensive understanding of the factors influencing PM 2.5 levels. An analysis of frequency shows an increasing trend in one of the three spring patterns. Results from the Coupled Model Intercomparison Project Phase 6 indicate a continued increase in frequency for the aforementioned pattern with rising surface temperatures. Our findings underscore the importance of understanding synoptic-scale effects on PM 2.5 variability to inform mitigation strategies in the context of climate change. • Combined SOM analysis identifies synoptic circulation patterns influencing PM 2.5 concentrations in South Korea. • Circulation patterns influence PM 2.5 concentrations via transport, ventilation, and stagnation. • Circulation patterns contributing to higher PM 2.5 concentrations over Korea are projected to intensify. [ABSTRACT FROM AUTHOR]

Land use is closely related to the sustainability of ecological development. This paper employed a patch-generating land use simulation (PLUS) model for the multi-scenario simulation of urban agglomerations. In addition, mathematical analysis methods such as Theil-Sen Median trend analysis, R/S analysis, Getis-Ord Gi* index and unary linear regression were used to study the temporal and spatial evolution characteristics of net primary productivity (NPP) for the impact of land use changes on NPP in urban agglomerations from 2000 to 2020 and to forecast the future trend of NPP. The results indicate that urban expansion is obvious in the baseline scenario and in the ecological protection scenario. In the scenario of cropland protection, the urban expansion is consistent with the land use plan of the government for 2035. The NPP in Beijing decreased gradually from northwest to southeast. The hot spot areas are concentrated in the densely forested areas in the mountainous areas of northwest. The cold spot areas are mainly concentrated in the periphery of urban areas and water areas. The NPP will continue to increase in forest and other areas under protection and remain stable in impervious surfaces. The NPP of Beijing showed a strong improvement trend and this trend will continue with the right ecological management and urban planning of the government. The study of land use in urban agglomeration and the development trend of vegetation NPP in the future can help policymakers rationally manage future land use dynamics and maintain the sustainable development of urban regional ecosystems. [ABSTRACT FROM AUTHOR]

Based on the humidity index, using the daily climate data of 113 meteorological stations in and adjacent the Yellow River Basin(YRB) from 1960 to 2020, climate trend rate, Morlet wavelet, simple correlation analysis, and Hurst index were used to analysis the spatiotemporal characteristics of dry-wet condition in the YRB in the latest 61 years and to predict the future trend of dry-wet changes in the YRB, to provide scientific basis for drought prevention and mitigation and rational utilization of climate resources in the YRB. The results showed that: (1) among all the geographic zones, the annual and seasonal humidity index in the YRB was high in the southeastern YRB and low in the northwestern YRB. Spatially, the climate of the annual, spring and autumn in the YRB was mainly dry, the proportions of stations with significant decrease of humidity index of the total stations were 5.31%, 7.96% and 6.19%, respectively. The climate of summer and winter was mainly wet, the proportions of stations with significant increase of humidity index were 10.62% and 13.27%, respectively. (2) As for the interannual change, the annual and seasonal humidity index of the YRB from 1960 to 2020 showed no significant change. Semi-humid, semi-drought, semi-humid, semi-humid, semi-drought were found in entire year, spring, summer, autumn, and winter, respectively. The annual and seasonal humidity index of the YRB had periodic oscillation characteristics at multiple time scales, and the first main period was 3 years, 26 years, 14 years, 3 years and 15 years, respectively. (3) The change of humidity index in the YRB was extremely significantly positively correlated with precipitation and relative humidity. There was a extremely significant negative correlation between sunshine duration and humidity index. Precipitation, relative humidity, and sunshine duration were the main factors affecting the change of humidity index in the YRB. (4) The Hurst index of annual and seasonal humidity index in the YRB were larger than 0.50, indicating that the climate of annual, spring, and autumn of the YRB would continue to be drying, the summer and winter climate would continue to be wetting. [ABSTRACT FROM AUTHOR]

Based on literature measurement and knowledge graph, this paper systematically sorted out and analyzed 2 563 articles on theme of 􀆳natural resources􀆳 published in China Population, Resources and Environment from 1991 to 2021. It was found that the amount of published articles experienced three rising periods and one falling period, research popularity showed an upward trend, and the pro⁃ portion of published articles tended to be stable. From a longitudinal perspective, there existed research hotspots such as resources and sustainable development, natural resources utilization and protection, 􀆳resource curse􀆳, resource⁃based cities, energy resources and car⁃ bon emissions. Current research hotspots are mainly distributed in water resources, land resources, energy resources and carbon emis⁃ sions. In the early stage, the research tended to focus on macro, qualitative and normative analysis, with topics mainly on resource poli⁃ cies and strategies under the concept of sustainable development. With the gradual deepening of the research, micro, quantitative and empirical analysis took the leading position, with conclusions becoming more targeted. In terms of content, the published articles show four salient features: ① The articles focus on the forefront of international sustainable development and natural resources; ② Most of the published articles carry out analysis integrating theories and methods of economics, management, law, sociology, security science and other disciplines; ③ The articles pay attention to theoretical innovation, the use of new methods and the production of new conclu⁃ sions; ④ The articles focus on solving practical problems, and the subject of each article is a practical scientific proposition. It is sug⁃ gested that future improvement needs to pay attention to the following aspects: focus on the forefront of international sustainable devel⁃ opment, and explore new research fields based on the important goal of sustainable use of global natural resources; closely follow the na⁃ tional resource policies, and accurately target and serve the national strategic needs for major resources; focus on comprehensive re⁃ search results on resource issues; focus on the combination of natural and economic laws of various resources and the systematic correla⁃ tion mechanism between them, the asset of various natural resources under the market economy system, and other related research re⁃ sults. It is up to the journal to discover and even actively explore, so as to present more high⁃quality research results to the academic community. [ABSTRACT FROM AUTHOR]

High voltage circuit breakers (HVCBs) play a critical role on providing the desired reliability, and resiliency in power systems. In order to extend their lifetime and predict the failures, various maintenance policies could be applied on these critical components. Amongst these strategies, condition-based maintenance (CBM) provides a satisfactory agreement with future smart environment. This paper aims to provide an insight into the relevant developments in this subject and to explore the viable visions compatible with future research stream. Accordingly, three directions, i.e., diagnostic signals, intelligent modelling and using monitoring data in asset management have been addressed in this paper. It presents challenges dealing with real-time assessment of the diagnostic signals relating to measurements, and analyses. Subsequently, the issues associated with using artificial intelligent (AI) and Machine learning for providing intelligent algorithms have been discussed. Finally, the connection between the monitoring data and the asset management approach is investigated. The latter is looking for the subjects including remaining lifetime estimation, prioritization, and health index definitions. This paper has attempted to make a bridge from past to future research trends in the failure diagnosis of HVCBs. [ABSTRACT FROM AUTHOR]

The increasingly meagre copper ore resources constitute one of the decisive factors influencing the price of this commodity. The demand for copper has been showing an accelerating trend since the Covid pandemic broke out. It is thereby imperative to estimate the future price movement of this material. The article focuses on a daily prediction of the forthcoming change in prices of copper on the commodity market. The research data were gathered from day-to-day closing historical prices of copper from commodity stock COMEX converted to a time series. The price is expressed in US Dollars per pound. The data were processed using artificial intelligence, recurrent neural networks, including the Long Short Term Memory layer. Neural networks have a great potential to predict this type of time series. The results show that the volatility in copper price during the monitored period was low or close to zero. We may thereby argue that neural networks foresee the first three months more accurately than the rest of the examined period. Neural structures anticipate copper prices from 4.5 to 4.6 USD to the end of the period in question. Low volatility that would last longer than one year would cut down speculators' profits to a minimum (lower risk). On the other hand, this situation would bring about balance which the purchasing companies avidly seek for. However, the presented article is solely confined to a limited number of variables to work with, disregarding other decisive criteria. Although the very high performance of the experimental prediction model, there is always space for improvement - e.g. effectively combining traditional methods with advanced techniques of artificial intelligence. [ABSTRACT FROM AUTHOR]

With the emerging of new media and hybrid publishing, the huge increase in the number of Chinese books published, the rise in the unit price of books, the readers' diversified demand for books and the change of library space, it is required that the library designed the development strategy of transformation in the construction of Chinese collections, especially with the problems exposed in the use of Chinese books during the epidemic period of COVID-19. The library should recognize the direction and clarify the ideas in order to better promote the transformation of library services. We should adapt to the situation, speed up the construction of the hybrid collection development system of printed and electronic books. [ABSTRACT FROM AUTHOR]

The relationship between the bank-breaching frequency of the lower Yellow River and climate change in the past 2 000 years was studied by Hilbert-Huang transform(HHT) method. This relationship could be divided into three stages: 0-800 AD(Early and before the Sui and Tang Dynasties); 800 AD-1000 AD(Later Sui and Tang Dynasties and Early Northern Song Dynasty); 1000 AD-Now(After Northern Song Dynasty). In the first stage, the bank-breaching frequency of the lower Yellow River was hardly affected by climate change. In the second stage, the bank-breaching frequency of the lower Yellow River was increasing because of vegetation destruction and at the same time it rose with the increase of the temperature. The second stage could be seen as the transition stage of the first and the third stages. In the third stage, the bank-breaching frequency of the lower Yellow River continued to grow. There was a significant negative correlation between the bank-breaching frequency and the temperature change. It could be explained by the Yellow River channel became shrunk during dry and cold periods so that when large flood came, bank-breaching was more likely to occur. In the next 30 years, the temperature of the middle Yellow River basin would keep on increasing. Precipitation was expected to increasing with less extent. The bank-breaching frequency would decrease in the future warm and humid climate, it was conductive to large-scale river regulation project. With the increasing of precipitation, the water and soil conservation could be enhanced on one hand; on the other hand, man-made-flood by reservoir cooperation dispatch could be used to broaden the channel. These measures could prevent serious consequences due to channel shrinkage and extreme floods in the next cold and dry period. [ABSTRACT FROM AUTHOR]

More than 300 participants from 28 countries, some 60 lectures and case studies on current developments and visions, interactive sessions and social events – this was the conference Internet Librarian International 2018, October 16–17, Olympia Center, London. The main topics of the event for librarians and information professionals were the library as a place for encounters and learning, future technologies, how they will influence the everyday life of information experts as well as active advertising. Many interesting lectures in six tracks, three of them in parallel. [ABSTRACT FROM AUTHOR]

Climate change has become an increasingly dominant environmental issue which has been attracting more and more attention in recent years. It is necessary to determine the cycle and trend of annual precipitation in the Haihe River Basin in the context of climate change because it is the largest river system in northern China. A combined method of rescaled range analysis and wavelet analysis is applied to identify the cycle and trend in annual precipitation based on data from 12 weather stations in the Haihe River Basin. The results of wavelet analysis show that the 12 weather stations all have the long main cycles of 35-38 years and the mediumlength cycles of 22-25 years. Datong, Yuanping, Shijiazhuang, Taiyuan, Anyang, and Huimin stations have the short-length cycles of 9-11 years. The results of rescaled range analysis show that all of the Hurst exponents are greater than 0.5, which indicates that the future trend of annual precipitation will very likely follow the historical trend. Therefore, nine stations will have the downward trends, and other stations will have the upward trends in the future, according to the analysis of the historical trends by the method of wavelet analysis. [ABSTRACT FROM AUTHOR]

Primary energy consumption has increased by 49% and CO2 emissions by 43% during the last two decades, and the predictions indicate that the growing trend will continue as a consequence of the notable growth in world population. Nations with developing economies (South America, Middle East, Africa and Southeast Asia) have an average annual energy consumption rate of 3.2%, whereas the rate is 1.1% for most of the developed economies (North America, Japan, Australia and Western Europe). In this paper, overall energy consumption in the UK by sector is evaluated from 1973 oil crisis to the present. The scope is split into four sectors as transport, domestic, industrial and services sector and the results for each are presented in a comparable way. Percentage of total primary energy consumption and final energy consumption by fuel type are presented. Several factors affecting the overall energy consumption are also investigated. [ABSTRACT FROM AUTHOR]

The past decade has witnessed the rapid development of Artificial Intelligence (AI), especially the explosion of deep learning-related connectionist approaches. This study combines traditional literature review, bibliometric methods, and the Science of Science (SciSci) theory to scrutinize the development context of AI in the last decade on AMiner. 4 4 www.aminer.cn , AMiner is an academic mining system, which will be introduced in the following section. With the assistance of AMiner tools and datasets, this paper aims to describe a further explicit context and evolution of AI in the past decade from the development of connectionist approaches. Five aspects of the past decade are highlighted: self-learning and self-coding algorithms, Recurrent Neural Networks (RNN) algorithms, reinforcement learning, pre-trained models, and other typical deep learning algorithms, which represent the significant progress of this field. By combining these critical parts, we then summarize the current limitations and corresponding future of AI trends in the next decade and discuss some topics about the next generation of AI. Discoveries in this paper will benefit AI research in promoting understanding of the current critical stage and future trends of AI development and the AI industry in the dramatic ascendant for the academic research results transformation and its industrial layout. [ABSTRACT FROM AUTHOR]

Big data has been a hot topic both in academia and industries. At the same time, new storages, such as flash memory and phase changing memory, are greatly changing the design and applications of both software and hardware in modern computrr systems. Basically, big data management has to deal with a lot of challenges, such as energy and performance, whereas new storages are superior to traditional magnetic disks in many aspects including I/O latency and energy consumption. Therefore, researchers conduct big data management study on new storages and expect to solve the critical issues in big data management. However, so far lots of issues are still to be further explored. We summarize the state-of-the-art studies in big data management over new storages, and try to answer some key questions , e. g. , "What new challenges and issues are brought by introducing new storages to big data management?", "Can we solve or partially solve the key issues in big data management by using new storages?". Particularly, we first discuss the special features of new storages, and then present the recent research advances in storage architectures and core algorithms for big data management over new storages. Finally, some future research directions in this area are proposed, which are expected to provide useful references for the future study in big data management and new-storage-based data management. [ABSTRACT FROM AUTHOR]

Amplitudes, rates, periodicities, causes and future trends of temperature variations based on tree rings for the past 2485 years on the central-eastern Tibetan Plateau were analyzed. The results showed that extreme climatic events on the Plateau, such as the Medieval Warm Period, Little Ice Age and 20th Century Warming appeared synchronously with those in other places worldwide. The largest amplitude and rate of temperature change occurred during the Eastern Jin Event (343-425 AD), and not in the late 20th century. There were significant cycles of 1324 a, 800 a, 199 a, 110 a and 2-3 a in the 2485-year temperature series. The 1324 a, 800 a, 199 a and 110 a cycles are associated with solar activity, which greatly affects the Earth surface temperature. The long-term trends (>1000 a) of temperature were controlled by the millennium-scale cycle, and amplitudes were dominated by multi-century cycles. Moreover, cold intervals corresponded to sunspot minimums. The prediction indicated that the temperature will decrease in the future until to 2068 AD and then increase again. [ABSTRACT FROM AUTHOR]

Abstract: Korea, selected as a target nation of the second commitment period for the reduction of greenhouse gases by 2013, is making efforts to reduce the production of greenhouse gases in all industrial fields. In particular, Korea is working hard to prepare for measures on the national level to reduce energy consumption and to limit the creation of carbon dioxide in the construction industry, which is responsible for over 40% of all carbon dioxide production. In order to pursue sustainability in the construction industry, existing development-focused construction activities must be transformed via a new paradigm focusing on sustainable development through the adoption of sustainable policies by the government and the development and dissemination of sustainable construction technologies. For such reasons, this study examined sustainable policies, research, and education recently used in Korea to identify future trends in the sustainable construction industry toward which Korea should strive in terms of governmental policy, research, education, and projects. [Copyright &y& Elsevier]

• We have assessed the long-term ecosystem services (ESs) of the Yellow River Basin. • Future change trends in ESs will either increase or decrease in different regions. • The relationship among different ESs in the region are mainly synergies. • Multiple factors jointly affect the changing trend and related relationship of ESs. Global changes have significant impacts on changes in ecosystem services (ESs) and their interrelationships. The Yellow River Basin (YRB) is an important ecological barrier in China, and it is important for ecological decision-making and management in the basin by quantitatively assessing the trends and drivers of ESs and analyzing the trade-offs and synergies among them. In this study, the food production model, InVEST model, and RUSLE model were used to quantitatively assess three ESs (food production, water yield, and soil conservation) in the YRB from 2000 to 2018. The spatio-temporal trends and future trends were quantified using Theil-Sen Median trend analysis and Hurst exponent. Correlation analysis was used to determine the main influencing factors of the spatio-temporal changes of ESs and analyze the trade-offs and synergies among ESs. The research results show that during 2000–2018, in terms of spatial distribution, food production in the YRB gradually decreases from east to west, water yield gradually decreases from south to north, and the dominant areas of soil conservation are mainly distributed in the plateau areas in the upper and middle reaches of the basin; in terms of temporal changes, food production shows a continuous increase, while water yield and soil conservation generally show an increasing trend in fluctuation. Excluding areas with no significant change and random change, food production will mainly show improvement in the future, and water yield and soil conservation will show some degree of decline in the future. Food production is mainly influenced by the type of land use, water yield is mainly influenced by precipitation, and soil conservation is influenced by a combination of slope and land use type. ESs in the YRB were generally dominated by synergy but locally dominated by trade-offs. Our results will provide reference for policymakers in ecological construction, and analyze trade-offs and synergies of regional ESs in a holistic and local context based on the assessment results and change trends of ESs, thus providing a basis for formulating scientific and reasonable ecological protection policies, and will promote the high-quality development of the YRB. [ABSTRACT FROM AUTHOR]

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China. [ABSTRACT FROM AUTHOR]

Rockfall is one of the main phenomena in mountainous environments due to its fast and high speed of movement, its unpredictability, and, therefore, the difficulty of identifying signs of instability and detachment of the blocks. Compared to other types of sliding, the proportion of rockfall research is smaller and sometimes little known, but, in the last five years, rapid growth in this area has been shown. Therefore, this research aimed to review the intellectual structure of rockfall, through analysis of scientific production using bibliometric techniques that allow its analysis, knowledge, global evolution, and future trends in rockfall. The research methodology consists of three steps: (1) data compilation, (2) software and data cleaning, and (3) analysis, interpretation, and visualization. This analysis focuses on the period from 1975 to 2019. For the data, a total of 811 academic publications were retrieved from the Scopus database. The results indicate an increasing trend of annual publications on rockfall. This analysis reveals the main topics, countries, and most influential institutions in the world that have carried out relevant research in scientific publications; it also shows the journals that have the most publications. VOSviewer software was adopted to evaluate the co-occurrence of author keywords. Currently, the hotspots rockfall issues mainly include: hazard-risk assessment, remote sensing, and rockfall monitoring. Finally, this article analyzes the limitations of current research and proposes a future direction for the development of new research. [ABSTRACT FROM AUTHOR]