This study employs GIS spatial analysis methods, utilizing the GHGIS and CShapes-2.0 historical geographic datasets, to systematically compare the strategic postures of Prussia and Austria during the German unification process from a geospatial perspective. Through buffer zone analysis, neighborhood analysis, and topographic analysis, it was found that in terms of spatial reach efficiency, Prussia, leveraging its central location, required only a 100-kilometer buffer zone to cover all 34 German states, whereas peripherally located Austria needed a 500-kilometer buffer to achieve the same effect. In terms of geopolitical connections, Prussia directly bordered 26 states, establishing a dense network of relationships that laid the foundation for customs unions and economic integration; Austria, bordering only 3 states, remained relatively isolated. Military geography favored Prussia, whose territory consisted primarily of lowland plains. It possessed far fewer rugged terrains (elevation >1 000 meters, slope >15°) than Austria, facilitating rapid maneuverability for modern armies and the development of transportation networks. The findings indicate that under 19th-century productivity levels, superior geographic conditions: efficient spatial coverage, close geopolitical ties, and favorable topography: constituted the crucial material foundation enabling Prussia to dominate the German unification process. This study not only addresses the limitations of traditional historiography in precise quantification through spatial analysis but also reflects on the accuracy of historical GIS data, advocating for the systematic advancement of historical GIS applications and data system development within domestic world history research.

GIS technology is increasingly being widely applied in the research of humanities. At present, research on the distribution of modern place names using GIS technology is gradually increasing, but there is still relatively little attention paid to ancient place names. This study takes the geographical names in Guangdong recorded in Essentials of Geography for Reading History as its research object, classifies them into two major categories—natural landscapes and cultural landscapes, and uses GIS technology to conduct an in-depth analysis of their distribution patterns to explore the causes of their distribution. The results show that natural landscape-related place names outnumber those of cultural landscapes. Natural landscape names are dominated by mountain and hydrological terms, mainly concentrated in the Pearl River Delta of Guangzhou Prefecture, the junction of mountainous and plain areas in central Zhaoqing Prefecture (western Guangdong), and the southeastern coast. This coincides with the natural conditions of Ming Dynasty Guangdong, characterized by crisscrossing mountains, dense water networks, and hot-humid climate. Among cultural landscape names, military-related place names constitute the majority, reflecting Guangdong's critical role in guarding against Japanese pirates and curbing ethnic rebellions (such as the Yao uprisings) during the Ming Dynasty. These names are also concentrated in areas like the Pearl River Delta of Guangzhou Prefecture and Zhaoqing Prefecture, roughly overlapping with the distribution of natural landscape names, revealing the influence of topography on military deployments. Additionally, dialectal place names in this region exhibit dense distribution in the Pearl River Delta of Guangzhou Prefecture and the coastal/riverine zones of Zhaoqing Prefecture, influenced by multiple factors such as natural geographical conditions, migration waves triggered by wars, and economic development. Overall, the distribution of Guangdong's place names demonstrates a twin-core shining pattern centered on Guangzhou and Zhaoqing, primarily attributed to Guangzhou's long-standing status as a major port with prosperous economy and Zhaoqing's geographical advantage of being located in the nearby plain area.

Based on the interpretation of historical maps and the examination of relevant historical materials, this study employs GIS-based spatial analytical methods to investigate the spatial pattern of market towns in Fujian Province during the Republican era (1912‒1949) and the factors shaping their distribution. From the perspective of historical geography, the study aims to identify the spatial distribution characteristics and underlying formation mechanisms of Fujian's market towns, thereby contributing to a better understanding of the evolution of regional town systems. The results indicate that market towns exhibited a pronounced clustered distribution, with a distinct "coastal-riverine" pattern. Natural conditions, including altitude and slope, provided fundamental constraints for the formation of the town pattern, while socio-economic factors served as the primary driving forces behind the observed spatial configuration. The findings offer historical evidence for the conservation and sustainable development of market-town heritage in Fujian and support the rational utilization and long-term protection of such heritage resources.

Prehistoric cave dwellings are settlements in prehistoric times with cave dwellings as the main architectural form, and are precious historical and cultural heritage. This study applied ArcGIS 10.8 software and comprehensively utilized methods such as average nearest neighbor analysis, kernel density analysis, multi distance spatial clustering analysis, and overlay analysis to investigate the spatial distribution characteristics of prehistoric cave dwellings in the Loess Plateau region. The results of this study are manifested in three aspects. Firstly, prehistoric cave dwellings include cliff style cave dwellings and sunken cave dwellings. The layout of prehistoric cave dwellings is mostly in the shape of a "Tu" character, with a few in the shape of a "Lv" character. The main chambers of prehistoric cave dwellings have shapes such as elliptical, circular, and rounded rectangular. Secondly, prehistoric cave dwellings are mainly distributed in low to medium altitude areas and flat slopes. Thirdly, prehistoric cave dwellings exhibit an inherent clustering trend, with a spatial distribution type of agglomeration. The border area between Shanxi, Shaanxi, and Inner Mongolia, as well as the surrounding areas of Xi'an, are two high-density core regions for the distribution of prehistoric cave dwellings. This study validates the effective framework of using GIS spatial statistics and qualitative analysis to analyze prehistoric cave dwellings in the Loess Plateau region, and to some extent elevates the research perspective from individual prehistoric cave dwellings to the level of social spatial structure.

During 1368‒1566, the lower Yellow River exhibited distinct spatiotemporal variations in overflow frequency and distribution, influenced by climate fluctuations, natural geographical conditions, and human river management activities. This study integrates historical records with reconstructed climate data, employing kernel density estimation and standard deviation ellipse methods to examine the spatiotemporal patterns of Yellow River overflows and their relationship with climate and river management strategies. The findings reveal: overflow events were highly concentrated around Kaifeng Prefecture before shifting eastward to the Shandong-Jiangsu river sections in the 16th century; the correlation between overflow frequency and Little Ice Age temperatures was complex, alternating between positive and negative, reflecting nonlinear climatic responses; the Ming government's "southern diversion, northern embankment" management approach initially stabilized the Henan river sections but exacerbated downstream siltation over time, ultimately transferring overflow pressures downstream. Through visualization analysis, this study elucidates the complex mechanisms underlying the overflow events of the Yellow River, while also revealing a dynamic relationship in which human activity and the natural environment continuously shape one another.

Continental red beds serve as crucial archives for paleoclimatic and paleoenvironmental data, facilitating analog studies of ancient environments and planetary geological evolution. Within these deposits, white spots are localized bleached reduction zones that typically appear as grayish-white to gray-green spheroidal, ellipsoidal, or banded structures. In biogeochemistry they preserve signatures of the early deep subsurface biosphere. In addition, their mineralogical and spectral characteristics have potential as indicators in the search for extraterrestrial life. Their genesis has long been debated, involving complex interactions among pore-fluid infiltration, organic matter degradation, and microbial processes. Despite this, the formation mechanism remains a subject of debate, necessitating further quantitative analysis and research. This study employed scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), to conduct a comparative analysis of the elemental and mineralogical compositions of the white patches and surrounding continental red-layer deposits.The XPS results indicate a slightly elevated Fe²⁺/Fe³⁺ ratio (~1.00) within the white spots, implying mildly reducing conditions and partial reduction-mobilization of Fe^3+. Concurrent enrichment of Al is consistent with feldspar alteration and clay mineralization processes. SEM observations reveal widespread carbonate cementation, chloritization, and alteration of Cr-Fe-Ti-bearing heavy minerals within pore spaces and fractures, reflecting the penetration of acidic reducing fluids. These findings suggest that the formation of white spots resulted from coupled interactions between pore fluids and detrital heavy minerals, with microorganisms likely serving as catalytic agents in local reductive bleaching. The study provides mineralogical and redox evidence for understanding reduction-oxidation dynamics and potential subsurface microbial activity in continental sedimentary environments.

Fengshui ponds, a type of semi-enclosed static water body artificially excavated or modified, hold unique cultural significance in the Lingnan region. Heavy metal contamination in sediments of rural fengshui ponds (water ponds for geomantic purposes) is crucial for ecological security construction. This study focuses on a typical rural Fengshui pond in Guangdong Province, where water quality ecological restoration has been conducted in recent years. To evaluate the effectiveness of ecological restoration, sediment cores and surface samples were systematically collected. Concentrations of heavy metals (Cr, Mn, Co, Cu, Zn, As, Pb) were determined using ICP-MS. The pollution degree, ecological risk, and health risk were comprehensively assessed using the geo-accumulation index (I_geo), potential ecological risk index (RI), and human health risk assessment models, respectively. Pollution sources were explored via Pearson correlation analysis. The results indicated that concentrations of all measured heavy metals in the sediment cores were significantly higher than the continental crust background values, exhibiting an increasing trend from the bottom to the top layer. Significant positive correlations (r>0.500, P<0.001) among Zn, Mn, As, Co, Cu, and Pb suggested a common source. Analysis of surface sediments from designated restoration zones and untreated controls revealed that the average concentrations of Co, Cu, Zn, As, and Pb in the restoration zones significantly decreased over time, indicating that aquatic phytoremediation had effectively reduced the load of these target heavy metals. As and Pb were identified as the primary enriched pollutants, posing the highest ecological risks. Health risk assessment identified Cr, Mn, and As as the main contributing factors, with dermal contact being the dominant exposure pathway. Children faced higher health risks than adults. This study addresses a research gap in the evaluation of remediation effects in small-scale, culturally significant artificial water bodies, providing a scientific basis for using aquatic plant remediation technology to manage heavy metal pollution in Fengshui ponds, control pollution input and accumulation, and mitigate ecological risks

This study focuses on 57 county-level administrative units in Guangdong Province, using flow network analysis and system coordination coupling degree research methods to calculate the coupling degree between the transportation and economic systems, and explore the coordination relationship between factor flows and economic development. Research has found that: (1) The internal county-level units surrounded by Huizhou, Heyuan and Jieyang, as well as the internal county-level units of Zhanjiang City, form two relatively independent high-intensity traffic flow subgroups, which have a strong radiation effect on the traffic flow of surrounding county-level units. (2) There are 15 county-level units with coordinated traffic flow and economic development, 33 county-level units on the brink of imbalance or with slight imbalance, and 8 county-level units with severe imbalance. (3) The coupling coordination degree of traffic flow and economic development exhibits spatial heterogeneity. The coupling coordination degree of county-level units in the Pearl River Delta is relatively good, with economic development and traffic flow development promoting each other; while the coupling coordination degree of county-level units in eastern, western, and northern Guangdong is relatively low, and there is a certain degree of disorder between economic development and transportation system development. The article proposes differentiated transportation optimization strategies and suggestions to improve the long-term guarantee mechanism for county-level finance, thereby promoting high-quality economic development at the county level.

Chronological Study is of Great Significance in Exploring Environmental Changes in the Salawusu River Basin. This study utilized single-grain optically stimulated luminescence (OSL) dating techniques to determine the ages of quartz and potassium feldspar minerals from surface sediment samples collected in the Salawusu River. For the two collected samples, the quartz and potassium feldspar mineral fractions were separated. The equivalent dose (D_e) of the quartz was measured using the single-aliquot regenerative-dose (SAR) procedure. The D_e of the potassium feldspar was measured using the post-infrared infrared stimulated luminescence (pIRIR) procedure with a two-step infrared excitation protocol. The test results indicate that: (1) The quartz OSL signals from the tested samples were very weak, making quartz unsuitable for OSL dating of fluvial sediments from this location. (2) The pIRIR₁₇₀ protocol was applied to measure the D_e of potassium feldspar in the two modern samples (SCH-QT-M01 and LJB-MR-01). Most recycling ratios fell between 0.9 and 1.1, and recuperation was generally less than 10%, indicating the reliability of the measurement procedure. (3) The anomalous fading rates (g-values) for the IRSL₅₀ signals of the two samples were 1.88±0.11 and 1.79±0.17, respectively. The anomalous fading rates for the pIRIR₁₇₀ signals were 0.18 ± 0.07 and 0.19 ± 0.15, respectively, indicating that anomalous fading of the potassium feldspar pIRIR₁₇₀ signal is negligible. (4) The Minimum Age Model (MAM) ages obtained from the potassium feldspar pIRIR₁₇₀ signals for the two river surface sediment samples were 90 ± 20 years and 50±10 years, respectively. This indicates that the surface sediments of the Salawusu River primarily consist of mixed accumulations deposited over the last century by processes including flowing water and wind. Considering the associated errors, these results demonstrate that the single-grain potassium feldspar pIRIR₁₇₀ technique is suitable for dating fluvial sediments in the Salawusu River.

The grain size characteristics of lake sediments serve as a critical proxy for reconstructing sedimentary dynamics and paleoenvironmental changes. However, traditional studies often rely on bulk grain size parameters, which may obscure signals from mixed depositional processes. This study focuses on the multi-modal grain size distribution of sediments from a 49-cm core (SSL core) collected at the center of the Thirty-Six Feet Lake, a small closed lake on Pingtan Island, Fujian Province, China. Using laser granulometry and log-normal distribution modeling, three distinct grain size components were identified: a dominant coarse-grained component (mode sizes of p1: 25~70 μm), a secondary fine-grained component (mode sizes of p2: 5~12 μm), and a minor ultra-fine component (mode sizes of p3: 0.6~1.5 μm). Unlike typical lake-center deposits in larger lakes, where fine-grained components dominate, the SSL core exhibits a "lakeshore-like" depositional pattern, with p1 accounting for 48.6%~70.9% of the total volume. This anomaly is attributed to the lake's small size (2.1 km²), shallow depth (mean 4~5 m), and proximity to the shore (0.37 km from the center), which enhance hydrodynamic intensity at the lake center, enabling coarse particles to be transported via saltation. The p2 component is deposited under weaker hydrodynamics through suspension. By deconvoluting multi-modal grain size components, this study demonstrates that separating depositional signals from mixed processes enhances the accuracy of environmental proxies. The findings underscore the necessity of considering lake morphology and hydrodynamic conditions when interpreting grain size data, particularly for small lakes. This work provides a theoretical framework for optimizing sedimentological proxies in paleoenvironmental reconstructions and highlights the unique sedimentary dynamics of small closed lakes.

As significant source of greenhouse gases, urban river has wide ranges of N₂O and CH₄ emission rates because of various environmental conditions and different monitoring methods. A typical unban river, the Wei River in Xinxiang City, was selected to monitor the emission rates of N₂O and CH₄ at the river water—air interface in spring. Both the floating static chamber method and the diffusion model method were applied to conduct the experiment, and comparison between their results was carried out. The influences of water quality and other environmental factors on the emission rates were also analyzed. The results showed that the Wei River behaved as continued source of N₂O and CH₄, and both the concentrations and the emission rates of N₂O were significantly related to nitrate (P<0.01), ammonia (P<0.01), dissolved organic carbon (P<0.01) and redox potential (P<0.05), and the air temperature and dissolved inorganic carbon were only related to N₂O emission rates (P<0.05). The concentrations of CH₄ were significantly correlated to dissolved organic carbon (P<0.01) and redox potential (P<0.05), while CH₄ emission rates were significantly correlated to water temperature (P<0.01) and redox potential (P<0.01). The average daily emission rates of N₂O and CH₄ obtained by the diffusion model method were 59.15% and 68% of those measured using the floating static chamber method, respectively. Moreover, the emission rates of the gases calculated from the two methods were significantly correlated (P<0.01), demonstrating that the diffusion model method is suitable for shallow and slow urban rivers. The daily average emission rates obtained by the diffusion model method were 59.15% (N₂O) and 68.74% (CH₄) of the static box method, respectively, reflecting that the contribution of CH₄ bubbling emission in the Wei River was low in spring, while N₂O may have a higher bubbling emission flux.

Considering the urgent need to construct a new pattern of Chinese-style urbanization development in Guangdong Province, this study, based on urban land use data and statistical panel data from 122 districts and counties in Guangdong Province from 2000 to 2020, this study establishes a quantitative model to analyze the spatiotemporal differentiation characteristics of urban land expansion. It further integrates the Optimal Parameter Geographical Detector (OPGD) and the Geospatial Convergent Cross Mapping (GCCM) model to investigate the driving mechanisms and corresponding optimization pathways of urban land expansion. The results show that: (1) From 2000 to 2020, the total urban land area in Guangdong Province continued to expand, increasing by 7.53%. The Pearl River Delta region experienced the most significant growth, exhibiting a spatial pattern with the Pearl River Delta region as the center, where urban land expansion gradually weakened towards the periphery. (2) The OPGD results reveal that the intensity change of urban land expansion is a result of multi-factor interactions. The explanatory power of two-factor interactions (64.2%-85.7%) is significantly higher than that of single factors. (3) The GCCM results indicate a significant bidirectional causal relationship between per capita GDP and urban land expansion intensity during the study period, suggesting a mutual driving effect. The model also identifies per capita GDP as the strongest predictor of urban land expansion intensity. Furthermore, analyses of causality among urban land expansion intensity, population urbanization, road network density, and the Remote Sensing-based Ecological Index (RSEI) show that urban land expansion drives population urbanization, while transportation networks and the ecological environment are also causal factors promoting urban land expansion. Therefore, in the future development process, how to simultaneously improve the quality of urbanization and promote urban-rural integration has become a key issue.

Software serves as a pivotal medium bridging theoretical knowledge and practical application in the teaching process of quantitative geography, playing a fundamental role in the entire process of achieving teaching objectives, cultivating students' abilities, and facilitating the transition to scientific research. To address the issues in undergraduate quantitative geography education, including the lag in introducing frontier research tools, the disconnect between research and teaching, and the scarcity of research on practical teaching reform from the perspective of software application, this paper explores the application and innovation of Stata software in the practical teaching of quantitative geography. It first introduces the models and methods included in mainstream quantitative geography textbooks, compares the advantages and disadvantages of commonly used software in teaching applications, then presents the characteristics and advantages of Stata software, and sorts out the models and methods that can be implemented by Stata. Subsequently, three reform pathways are proposed, including the dual-track parallel practice model, the extension of teaching from classical models to cutting-edge methods, and the empowerment of practical teaching tools through dynamic document functionality. Finally, the effectiveness of Stata in practical teaching is verified through a case study and a questionnaire survey. The research indicates that Stata is easy to learn and efficient, covering most methods in textbooks. Evidence shows that 78% of students found it easy to use, 86% perceived an improvement in learning outcomes, and 96% considered Stata suitable for practical teaching in quantitative geography. Hence, the reform of practical teaching based on Stata software not only improves the quality of practical teaching, but also effectively bridges the gap between undergraduate education and frontier research. It also helps students who are interested in further studies to familiarize themselves with mainstream research tools in advance, thus contributing to the high-quality development of quantitative geography education.

The rapid development of the Guangdong-Hong Kong-Macao Greater Bay Area has led to significant changes in land use patterns, which have far-reaching impacts on the regional ecology, economy, and social structure. In order to deeply understand these changes and formulate scientific and reasonable land management policies, based on a total of 31 periods of land use data from 1990 to 2020, adopts a method combining K-means and a convolutional neural network (CNN). Firstly, K-means is used to preliminarily classify land use data and provide accurate training labels. Secondly, a convolutional neural network is used to extract and classify features to achieve high-precision land use identification. Finally, the classification results and land use dynamic degree are integrated to quantitatively analyze the characteristics of land use change in the study area. The results show that: (1) The optimal effect is obtained when the land use data is divided into four categories. The silhouette coefficient for K-means is 0.73, and the classification accuracy of the convolutional neural network is 89.71%, fully verifying the effectiveness of this method. (2) In the past 30 years, the land use change in the study area can be divided into four typical stages, namely, the initial stage of rapid urbanization (1990—1997), the acceleration urbanization period (1998—2004), the stable development period (2005—2009), and the optimization and sustainable development period (2010—2020). Significant differences in land use patterns exist across these stages. (3) The characteristics of land use change in the study area are mainly reflected in the continuous reduction of farmland area, the rapid expansion of urban and construction land, while ecological land such as forests and water bodies, although remaining relatively stable, also face certain pressures and challenges. The study emphasizes the innovative application of machine learning technology in land use research, noting that the method can effectively identify land use pattern changes under limited labeled data, demonstrating its significant value in complex classification research. The research results not only deepen the understanding of land use change in the Guangdong-Hong Kong-Macao Greater Bay Area, but also deepen the understanding of land use change in the Guangdong-Hong Kong-Macao Greater Bay Area. Moreover, it provides a scientific basis and practical guidance for regional land use planning, management and sustainable development, which is of great significance for promoting regional coordinated development.

Guided by the national policy of “integrate where appropriate, and integrate to the fullest extent possible” for the integrated development of culture and tourism, this paper aims to explore the integration mechanism between museums and regional tourism, analyze the spatiotemporal characteristics of their coordinated development, and provide a reference for the planning and policy-making of the national museum tourism industry. Based on data from 31 provinces, autonomous regions, and municipalities directly under the central government (excluding Hong Kong, Macao, and Taiwan) in China from 2010 to 2019, this study employs the coupling coordination model to empirically analyze the coupling coordination degree and spatial correlation between the museum industry and regional tourism development, thereby revealing the evolutionary trends and spatial patterns of the coordination relationship between the two systems. The results show that during the study period, both China’s museum industry and regional tourism were in a growth stage, exhibiting an interrelated development trend. The degree of coordination continuously improved and remained stable at the moderately coordinated coupling stage. However, in terms of spatial distribution, significant regional differentiation exists nationwide. A cross-shaped high-value planar area of coordination degree formed in central and southern China, while the northwestern region remained a development lowland. From a national perspective, the driving effect of the tourism industry is stronger than that of the museum industry; future sluggish growth in tourism will affect the coupling status of the two systems. The coordinated development of museums and regional tourism exhibits clear spatiotemporal evolution characteristics and regional imbalance. Future efforts should focus on industrial collaboration and regional synergy to promote sustainable and high-quality coordination between the museum and tourism sectors nationwide.

With the unceasing progress of urbanization, regional land use has witnessed increasingly drastic alterations, and consequently, the ensuing regional ecological security problems have gradually come to the fore. Taking Anhui Province as a case in point, this paper delves into the characteristics of land use landscape changes by leveraging the land use data of Anhui Province spanning from 2000 to 2020. Sixteen indicators are meticulously distilled from three dimensions, namely the natural environment, social environment, and economic development, to formulate a land ecological security evaluation system tailored to Anhui Province. The comprehensive index method is employed to quantitatively assess the land ecological security status within the province; meanwhile, the obstacle factor model is used to dissect internal influencing factors and pinpoint key obstacle factors, thereby providing a scientific underpinning for regional land ecological protection and sustainable development strategies. The research findings disclose that: (1) during the study period, remarkable transformations took place in the land use pattern of Anhui Province. The conversion rate of cultivated land into construction land progressively accelerated, and the overall landscape fragmentation and complexity also witnessed a significant upsurge; (2) From 2000 to 2020, the overall land ecological security index in Anhui Province fluctuated upward, surging from 0.418 7 in 2000 to 0.536 1 in 2020, and the security level shifted from relatively unsafe to relatively safe; (3) With the fluctuation of the state of land ecological security in Anhui Province, the main obstacle factors affecting ecological security also change, and the factors such as population and tertiary industry have a relatively large degree of influence on ecological security.This study provides empirical references and theoretical support for land ecological security evaluation and sustainable development in Anhui Province, and helps to promote rational planning and management of regional land use.