Geographic environment has exerted profound effect on the origin and evolution of world civilizations. Chinese civilization budded and evolved on a vast and varied territory between Yellow and Yangtze rivers, and has been thus deeply affected by the local geographic conditions. But it has been hardly seen to explore the origin of Chinese civilization from the perspective of geography. On the basis of integrated scientific investigation in China's north-south transitional zone, geographic analysis of Neolithic culture distribution and interpretation of pre-Qin and Qin-Han ancient literature, the conclusions can be drawn as follows: (1) The early agriculture pattern of "Rice in the south and millet in the north" and the ancient astronomy formed before about 8000 years were the background for Chinese civilization. The geographic distribution of Neolithic Dadiwan, Yangshao, Majiayao and Longshan culture sites showed that the earliest civilization elements appeared in the upper reaches of West-Hanshui and Weihe rivers, with a spatial trend of spreading toward east. (2) The West Qinling Mts. region, located between the Tibetan Plateau and the Jialing River, especially its inner Chenghui and Xili basins, being characterized by superior natural conditions and resources, is closely related to the three major mysteries concerning the origin of Chinese civilization, i.e., the main areas of the ancient Di and Qiang ethnic groups, the location of ancient Kunlun Mts., and the site of Dayu water control. (3) The Qin ethnic group stepped onto the stage of history by assisting Dayu in water control, and in their history of multiple ups and downs, built the grand water control projects in ancient China, such as the Dujiangyan Irrigation Project, Zhengguo Canal, Lingqu Canal, etc., and pioneered the time of "Books with the same text" and "County system", forming the main line of the origin and early evolution of Chinese civilization. (4) The West Qinling areas are still basically a "blind zone" in archaeological and historical research. It is highly recommended to conduct systematic and in-depth archaeological and historical research in this region so as to realize the breakthrough in the exploration of the origin of Chinese civilization as soon as possible.

In the context of climate change and anthropogenic disturbances, understanding the response mechanisms of streamflow variations to changes in climate and watershed underlying characteristics has been a vital research focus in hydrology. Based on planar geometry and the water-energy partitioning framework, this study proposed the quantitative analytical formulas for attributing the contributions of climate and underlying characteristics to streamflow variations. Using long-term datasets of 83 typical watersheds in the world, the attribution results calculated by the water-energy partitioning framework and the Budyko decomposition method were compared. The results show that the global streamflow attributions of these two approaches were generally consistent, affirming the effectiveness of the newly developed framework. Furthermore, the water-energy partitioning framework is much simpler and easier to be applied, as compared to the Budyko decomposition method. It is also found that in most basins, the positive impacts of climate change on streamflow (resulting in increased streamflow) were offset by the negative effect caused by underlying characteristics (resulting in decreased streamflow), indicating a potential compensatory effect, while such a compensatory effect weakens with increasing drought severity. This study proposes a new decomposition method to streamflow attribution analysis, and also provides new perspectives for understanding the causes of global streamflow changes.

Cholera is one of the three virulent infectious diseases in humans. Based on the perspective of historical medical geography, we collected and sorted out modern cholera historical materials and environmental data, and used methods such as M-K test, wavelet analysis, GIS spatial analysis, and structural equation model to study the spatio-temporal patterns and influencing mechanisms of the cholera epidemic in modern Hubei province. The results show that: (1) From 1850 to 1949, cholera epidemics in Hubei can be divided into four periods: the Xiantong period of the late Qing Dynasty (1850-1874), the Guangxuan period of the late Qing Dynasty (1875-1911), the early Republic of China (1912-1927), and the middle and late Republic of China (1928-1949), and the frequency of cholera epidemics gradually increased. (2) From 1850 to 1949, there were 49 cholera epidemic years in the province. The cholera epidemic in 1932 was the most serious, and the frequency of cholera epidemics increased significantly after 1942. Cholera epidemics mainly occurred in summer and autumn, with fluctuation cycles on the time scales of 35 a, 19 a, 10 a, and 5 a. The 10 a time scale was the first main cycle, followed by the 35 a time scale. (3) From 1850 to 1949, 58 counties had cholera epidemics. The county clustering characteristics of cholera frequency were obvious. The high-value areas were distriuted in the three towns of Wuhan and their surroundings, and the low-value areas were in western Hubei. The cholera epidemic areas expanded along the rivers and lakes from the central Jianghan Plain to the surrounding mountainous areas. The Jianghan Plain was the area with the most serious cholera epidemics. The distribution center of the cholera epidemics swung in the center of the Jianghan Plain, showing a slight trend of migrating from southeast to northwest. (4) Natural factors, disaster factors and humanistic factors jointly affected the spatio-temporal characteristics of the cholera epidemics in modern Hubei. Regional differences in altitude, population, precipitation, river network and road networks presented the spatial pattern of the cholera epidemics in Hubei as "more cases in the east and less in the west". Wars, floods, droughts, and temperature shaped the temporal changes of cholera epidemics in the province, which was "more cases in the late period and less in the early stage".This study is a long-term series of cholera epidemics research, and its conclusions have guiding significance for the prevention and control of cholera epidemics in areas with dense lake water systems.

Cultural ecosystem services (CESs), as the non-material benefits and well-being provided by ecosystems to humans, can bridge and interpret the complex relations between nature and human society and can be organised around "spatial needs-spatial planning-spatial production" to achieve sustainable development and human well-being through top-down and bottom-up interventions. Accurately grasping the practical path of CESs involved in the spatial reconstruction of the human-land relationship is not only a scientific problem that needs to be solved to realise the effective enhancement of human well-being but also an important theoretical basis for realising the harmonious coexistence of human beings and nature. For this reason, based on the deconstruction model of "theoretical analysis-associated mechanism-practical application-development path", this study explores the inherent logical system and feasibility of CESs guiding the spatial reconstruction of the human-land relationship and discusses the value assessment-value trade-offs in the process. Based on the evolution of research on CESs in the "flow" era, this study constructs a framework for CESs to guide the spatial reconstruction of the human-land relationship and use it as a theoretical basis for exploring its application in guiding the spatial reconstruction of the ecological-production-living spaces. This framework is then used to develop a program of data collection, methods system, and practical application to realise the transformation of research on CESs from theory to practice and provide new perspectives for the spatial reconstruction of the human-land relationship in the new period.

The spatio-temporal feature is a fundamental characteristic of an event. A composite event is the intricate amalgamation of multiple events that have multi-scale spatio-temporal features and multi-level semantic attributes. To effectively model and analyze composite events, it is essential to leverage a spatiotemporal data model that captures the basic features of events and to realize the knowledge mining as well as the simulation and reasoning of the spatio-temporal evolution of events. Existing models often struggle to portray the evolutionary trajectories and causal relationships between entities across different scales of composite events, and lack the ability to capture the dynamically semantic changes of composite events, hindering their ability to meet the requirements for accurate modeling. The primary contributions of this paper are as follows: (1) By analyzing the concept of events within composite events, we propose a rich semantic event spatio-temporal data model that broadens the dimensions of events covered by existing models. We describe the diverse states and behaviors associated with the evolution of multiple entities across various temporal and spatial granularities based on the multidimensional characteristics of events in different domains. (2) We aggregate event hierarchies with their characteristics to establish a multi-level logical framework of events, progressing from complexity to simplicity, from the event itself to its constituent elements. (3) In our model, we depict the associations between events and events, as well as entities and entities within complex events, and analyze the potential causal relationship of the event through the evolution of spatio-temporal relationships and attribute relationships. (4) Finally, we elaborate on the modeling and analysis methods of the rich semantic event spatio-temporal data model by instantiating a historical war in human society. We illustrate the model's application using a GIS platform, demonstrating the knowledge inference process of evolving entity states and changing relationships between entities triggered by events, which lead to the occurrence of new events. Through this process, we validate the feasibility and practicality of our model.

Training samples play an important role in machine learning-based regional landslide susceptibility evaluation. These samples consist of both landslide (positive) and nonlandslide (negative) samples collected through various sampling methods. However, existing methods for positive sample collection do not measure the reliability of the collected samples, leading to uncertainty in terms of reliability. To address this issue, this paper presents a landslide prototype sampling method (PBS). This method uses the geographical similarity and dissimilarity between a certain point and the landslide positive sample prototype to measure the reliability of positive and negative samples, respectively. A reliability threshold is set based on a mutual exclusion method to collect training samples. The Youfanggou Basin in Gansu province was chosen as the research area. The PBS and existing representative sampling methods were used to construct landslide susceptibility prediction models based on logistic regression, support vector machines, and random forests for the Youfanggou Basin. The evaluation effects of landslide susceptibility were compared between the reliable and nonreliable samples. The reliability of the positive and negative samples exhibited a "fluctuating increase" and "positive correlation", respectively, in the evaluation of landslide susceptibility. The PBS method improved the accuracy and area under the receiver operating characteristic curve (AUC) of the landslide susceptibility evaluation based on the three machine learning models by at least 14.7% and 14%, respectively, compared to the existing representative sampling methods, and the standard deviation was small, which indicates that the method proposed in this article is effective.

Construction of research teams, an important component of disciplinary development, plays a crucial role in cultivating high-level talents and enhancing disciplinary competitiveness. As the main channel for funding basic research in China, the National Natural Science Foundation of China (NSFC) shoulders the responsibility of leading disciplinary development and supporting talent cultivation. The analysis of research team structure is a hot topic in talent geography, scientometrics, and research management studies. However, existing research has rarely analyzed the age structure and its impact on the development of geographical science disciplines. To address these gaps in existing research and more effectively promote the optimization of research team structure supported by the NSFC, this article systematically analyzes the dynamic characteristics of the talent team structure in the geographical science discipline based on information from project leaders of NSFC projects in the field of geographical science from 1986 to 2022. The results show that, the age structure of the geographical science discipline team has been optimized, the proportion of young research groups has continued to increase, and the overall vitality of the discipline has been significantly enhanced in the past 20 years. However, influenced by regional soft power and the inherent characteristics of branch disciplines, significant differences in the talent team structure between different regions and branches have emerged. In the process of leading disciplinary development and supporting talent team construction in the future, the NSFC in the field of geographical science needs to further provide corresponding strategic guidance according to the internal development logic and existing development stages of the discipline, so as to support the high-quality development of the research team structure in the discipline.