Three-dimensional fine characterization of soil pollutant distribution is critical for the implementation of precision remediation and scientific decision making in the management of contaminated sites. This review systematically examined key issues and research progress in this field through a trinity framework of non-stationarity decoupling, data bias correction, and model selection. We identified the spatial non-stationarity of pollutant concentrations and the inherent biases in sparse borehole data as two fundamental constraints that affect the accuracy of existing three-dimensional characterization models and the reliability of characterization results. We first analyzed the formation mechanisms and types of non-stationarity and discussed non-stationarity quantification and decoupling methods. Second, we summarized the principal sources of sampling bias in the collection of sparse biased drilling data and its bias correction method system. We also assessed the adaptability of different models to biased data and possible improvement. Third, we compared the advantages and limitations of the three predominant modeling paradigms (geostatistical, machine learning, and geochemical process models), analyzed the discrepancies and uncertainties in three-dimensional characterization model selection, and stressed the need for constructing a multi-source data-driven high-precision three-dimensional characterization system based on the trinity relationship framework. Finally, in combination with the development of intelligent decision-making technologies, we prospected the potential application of three-dimensional characterization technology in pollution diagnosis, risk assessment, and sustainable remediation. We also emphasize the potential value of model integration and dynamic optimization in soil pollution control. This methodological synthesis provides a reference for improving the accuracy of three-dimensional characterization of soil pollution distribution in complex sites and digital governance mode.
The input-output table serves as a core tool for quantifying the interconnections within an economy's sectors and the material flows between regions, playing a crucial role in studying regional economic ties and the various resulting relationships. Based on a systematic review of the basic structure, development history, and related concepts of the input-output table, this article summarized its functions in various fields, the shortcomings of the existing compilation methods, and its future development trends. The input-output table has played significant roles in economic analysis, industrial configuration optimization, policy evaluation optimization, regional economic connection and resource flow analysis, regional sustainable development and environmental governance, among others. Currently, the compilation of the input-output table overly relies on scarce historical trade data, which has caused problems such as insufficient accuracy, and low timeliness. In highly regionally heterogeneous countries such as China, the common simplistic homogeneity assumption can lead to failures. The future directions of the input-output table development include: First, compiling regional input-output models under future scenarios to predict future regional economic ties, which can provide basic data for predicting future trends of regional economic ties, resource flows, and environmental issues, identifying potential risks and opportunities, and thus providing a strong basis for scientific and reasonable decision-making. Second, establishing spatial input-output models, combining production and demand spatial distribution patterns, transportation and price factors and so on, to analyze regional trade ties, thereby breaking the excessive reliance on trade data. Third, data collaboration optimization, integrating enterprise-level transaction data and AI technology, dynamically computing industrial sector-correcting technical coefficients, and reducing uncertainties. In addition, combining real-time data with predictive models to establish a high frequency response-detailed analysis-multidimensional governance mixed model framework to adapt to dynamic and diversified application needs. This research can provide a reference for further research on input-output models.
The convergence of relational economic geography (REG) and evolutionary economic geography (EEG) offers novel insights into the formation mechanisms of regional emerging industries. Taking the biopharmaceutical industry in the Suzhou Industrial Park (SIP) as a case study, this study employed field research and empirical analysis to unravel the impact of dynamic strategic coupling on regional industrial change. Key findings include: 1) Developing regions rapidly transplant emerging industries through "dual-dependent coupling", yet excessive reliance on external actors poses sustainability risks. 2) External shocks (for example, financial crises) trigger decoupling, creating opportunities for governmental agency to upgrade coupling modes from dependency to functional coupling, thereby achieving value chain leapfrogging and industrial diversification. 3) Locational opportunity windows from industrial transfer must align with local conditions (for example, locational advantages, policy demands) to foster emerging industries. 4) The industrial base and entrepreneurial culture in neighboring regions empower local path creation through knowledge spillovers and synergy. This study enriches the analytical framework for the change of regional emerging industries and deepens the understanding of the influence mechanism of strategic coupling on such change, which is of great policy significance for addressing external shocks and promoting the upgrading of coupling models.
Agricultural industrial chain resilience is crucial for ensuring stable production and increased output of national grain and key agricultural products. Based on the panel data from 80 prefecture-level regions in central China from 2011 to 2022, this study measured agricultural industrial chain resilience using the entropy weight method, and investigated its spatiotemporal differentiation patterns and influencing factors through kernel density estimation and geographical detector analysis. The findings reveal that: 1) From a temporal perspective, the resilience of the agricultural industrial chain in China's central region has demonstrated a consistent strengthening trend, with the southern zone exhibiting marginally higher resilience levels compared to the northern zone. 2) From a spatial perspective, the resilience of agricultural industrial chain in central China exhibited significant spatial correlation. High-resilience regions have expanded from Hunan and Hubei toward the Qinling-Huaihe line. Dagum Gini coefficient analysis confirmed the pronounced regional disparity between northern and southern regions. 3) Geographical detector analysis identified logistics distribution capability, economic development level, and consumption capacity as key influencing factors. Interactive effects between agricultural technology R&D and labor supply significantly enhanced resilience, indicating an ongoing transition of driving forces from traditional production factors to technological innovation and market demand. Policy recommendations include: strengthening infrastructure such as agricultural technology innovation and rural logistics distribution; advancing industrial chain collaboration through cross-regional agricultural professional services; and institutionalizing agriculture-related policies and risk governance frameworks. This research provides empirical evidence and decision-making references for optimizing agricultural industrial layouts in central China.
Border areas are important gateways for opening up to the world, but few studies have explored the characteristics and influencing factors of its foreign trade in sufficient depth. Yunnan Province is an important gateway connecting China's market to the Southeast Asian markets, holding an important position in China's opening up in the new era. Therefore, using the Chinese customs database from 2003 to 2022, this study conducted a comprehensive analysis of the spatiotemporal change and influencing factors of the trade pattern for Yunnan Province based on year-market-product. The main conclusions of this study are as follows: 1) In terms of market characteristics, Myanmar was both the largest export and import markets of Yunnan Province, and the Southeast Asian region occupied an important position in both the import and export patterns of Yunnan Province. The United States was an important export market for the province, while countries such as Saudi Arabia, Peru, Chile, and Kuwait were major sources of imports. 2) In terms of product characteristics, the export structure showed a trend of greening and sophistication, shifting from polluting products, such as chemicals and metals, to electronic products and plant products. Among the imported products, energy such as oil and natural gas as well as metals accounted for more than 50%. 3) In terms of market-product characteristics, there was a significant difference between the province's exports to the United States and Southeast Asian countries, with the former having a more balanced structure. Yunnan Province imported large quantities of mineral products from high-resource countries such as Saudi Arabia, and a relatively high proportion of plant products from tropical countries. The export scale of the province was positively influenced by the local industrial base and industrial policies as well as the institutional environment of the trade markets, and was constrained by the product supply capacity and geographical distance of the trade markets. Differently, the import scale of Yunnan Province was significantly positively correlated with the local industrial base and industrial policies, as well as the institutional environment, openness, and product supply capacity of the trading markets, and significantly negatively correlated with geographical distance. The key influencing factors of trade patterns varied for different types of products. This study provides policy implications for optimizing the foreign trade structure of the border region represented by Yunnan Province.
The structural analysis of tourism flow networks has been a focus of research both in China and internationally. However, previous studies have paid relatively little attention to analyzing tourism flow networks among counties, rarely examined network motif structures, and offered limited investigations into large-scale regional case study areas. Based on big data from online bookings, this study employed complex network and the weighted exponential random graph model to analyze the multi-dimensional structure of "overall-motif-node" levels of intercounty tourism flow network in the Yangtze River Economic Belt and influencing mechanisms. The results reveal that: This network exhibited sparse, scale-free, and small-world features, with tourism flow links primarily concentrated within provincial boundaries and weak inter-provincial connections. The network contained seven 3-node motifs, each forming a loop structure, revealing seven tourist trip patterns including "fully connected triad". Node centrality varied significantly between counties, demonstrating an obvious Matthew effect. The agglomeration and diffusion functions for tourism flow were coupled, with counties possessing strong comprehensive functions concentrated in the Yangtze River Delta urban agglomeration, as well as provincial capitals and key tourist cities in central and western regions. But counties with high betweenness centrality are mainly distributed in Sichuan, Chongqing and Yunnan. This network's formation was affected by endogenous structure, node attributes, and exogenous networks, driven jointly by endogenous forces, positive push forces, and negative resistance forces. Reciprocity provides endogenous motivations. Economic development levels, transportation conditions, and tourism resource endowments of counties serve as positive push forces, while distance from provincial capitals, consumer price, population density, as well as spatial and cultural distances generate negative resistance. This research is conducive to deepening the theoretical research on the network spatial structure of tourism flow among counties.
In recent years, the vigorous development of Douyin short videos has become a crucial channel for enhancing the brand awareness and resulting visitor flow of tourist attractions. Studying the online influence of scenic spots and its influencing factors based on Douyin's sales power is of great significance for improving the digital evaluation system of scenic spots and promoting their high-quality development. Taking the Douyin ticket sales of scenic spots as the measurement indicator, this paper applies methods such as rank-size, Kernel density,typological division and Geodetector to analyze the spatial differentiation of online influence and its influencing factors of China's 5A-level scenic spots. The research findings are as follows: 1) Rank-size characteristics indicate that high-ranked scenic spots account for only 10.45% of the total but demonstrate significant influence and cluster in areas such as the Beijing-Tianjin-Hebei region, the middle and lower reaches of the Yangtze River. Medium-ranked scenic spots are the most numerous, accounting for 71.29%, yet their internal hierarchy is indistinct. Low-ranked scenic spots exhibit substantial variations in influence. 2) From the overall spatial differentiation characteristics, the number of scenic spots of medium-high, medium, and medium-low grades is large, while that of high-grade and low-grade ones is small. The spatial pattern features a single high-density main core, two secondary cores with subordinate density distributions, and multiple low-density cores scattered across the country. 3) Spatial differentiation of ticket types indicates that high grade scenic spots in total ticket sales and subtype metrics show significant convergence, with dominant regions concentrated in the Yangtze River Delta, Sichuan-Chongqing area, and the central plains. 4) A comparison with traditional indicators shows that both the MBI and Douyin ticket sales reflect a "central agglomeration and sparse distribution at both ends" pattern, with high grade scenic spots sharing similar regional distributions. However, from the perspective of brand online influence, high and low grade scenic spots are fewer in number, indicating a relatively balanced and stable distribution. Based on these two indicators: Total ticket sales on Douyin and MBI (Meadin Brand Index), scenic spots are classified into five categories, providing practical guidance for marketing optimization, policy-led resource allocation, and accelerating tourist decision making. 5) Influencing factor analysis results indicate that the number of tourist receptions, favorites, and followers demonstrate strong explanatory power; likes, topics, and posts show moderate explanatory power; while regional per capita Gross Domestic Product has the weakest explanatory power.
Exploring the patterns of change and influencing factors of business is an important basis for promoting the high-quality development of winter tourism destinations. Taking Chongli District of Zhangjiakou City, one of the venues for the Beijing Winter Olympics, as a typical winter tourism destination, this study constructed an industrial system for ice and snow tourism destinations, which took the core dominant formats as the main body to output major tourism products, used the extended synergistic formats to improve the market operation environment, and employed the supporting auxiliary formats to shape the basic development environment. It also clarified the functional relationships among different levels of industrial subsystems. It selected its point of interest (POI) data from 2005, 2010, 2015, 2022, and 2023 and used the ArcGIS spatial analysis method to analyze the spatial-temporal change characteristics of business in Chongli and its influencing factors. The results shows: 1) The number of POIs in the ice-snow tourism destination has demonstrated progressive growth from 2005 to 2023. Especially during the exponential growth stage driven by Winter Olympics preparations, all tourism sectors achieved unprecedented POI proliferation, particularly core dominant sectors that manifested the most substantial quantitative expansion. It also showed a stable development in the high-quality development stage. Significant spatial variations in business distribution have been observed, characterized by predominant concentration within southeastern townships and sparse distribution in northern regions, with dense clustering in southern areas. 2) Chongli's business formats exhibited an agglomerated spatial pattern, transitioning from a "single-core with multiple nodes" configuration to a "dual-core and dual-belt" structure during the study period, with progressively intensified clustering. Spatial diffusion analysis revealed that the distribution centroid is located at the boundary between Hongqiying Township and Xiwanzi Town on the whole. The standard deviational ellipse displayed a distinct northeast-southwest orientation, indicating pronounced directional spread. Spatial correlation analysis demonstrated strong positive spatial interdependence, with prominent clustering features. Low-low clusters significantly decreased, while high-high and high-low clusters gradually increased, indicating enhanced development levels across business formats. 3) The spatiotemporal change of winter tourism destination business formats is mainly driven by the combined effects of multiple factors: distance from administrative centers, socioeconomic development levels, collaborative development with tourism enterprises, transportation network distribution, altitude, slope, sports, and the winter Olympics policy impacts. Particularly during the rapid development stages, administrative centers and ice and snow policies played crucial catalytic roles in accelerating business format development, with the driving force gradually shifting to tourism-oriented enterprises as the primary growth engine.
Promoting the spatial and temporal adaptation of the cultural system and tourism system along the Long March Route is helpful for facilitating the orderly flow and optimal allocation of cultural and tourism production factors along the Long March Route, and it is of great significance to promote the high-quality development of cultural and tourism integration along the Long March Route and optimize the Long March National Cultural Park strategy. Taking 15 provinces within the scope of the construction of the Long March National Cultural Park as the research sample, this study constructed an evaluation indicator system for the culture-tourism system along the Long March Route, and comprehensively used the adaptability evaluation model, coupling coordination model, kernel density estimation, obstacle degree model, and optimal parameter geographical detector to analyze the characteristics of change of the integration development driven by the spatiotemporal adaptation of the culture-tourism system along the Long March Route from 2013 to 2022 and its mechanism. The key findings include: 1) The adaptation and integration levels of the culture-tourism system along the Long March Route showed a high degree of convergence in the spatial and temporal dimensions. With the dynamic adjustment and collaborative optimization of the culture-tourism system along the Long March Route, the integration level of culture and tourism in the region has shown a significant continuous deepening, which confirms the key driving role of system adaptability in the deep integration of culture and tourism. 2) The obstacles faced by the culture-tourism system in the process of adaptation showed significant differences. The driving factor analysis showed that talent reserve and financial support are the core leading forces to shape the adaptation pattern of the culture-tourism system, and industrial structure optimization and innovation potential mining played an important supporting role, jointly promoting the dynamic adaptation and coordinated development of the culture-tourism system. 3) The development of the integration of culture and tourism driven by the adaptation of the culture-tourism system along the Long March Route is essentially a process of wave-like advance and spiral rise, following the logical mechanism of "external drive-internal response-dynamic adjustment-deepening integration". That is, the external driving factors first break the original balance of the system and trigger the internal response mechanism; through dynamic adjustment paths such as resource integration and factor reorganization, system structure optimization and function upgrading are promoted, and finally the integration of culture and tourism is realized from primary coordination to deep integration.
With the rise of electronic word-of-mouth (eWoM), the traditional consumption spatial patterns are reshaping. Taking optical stores within Shanghai's Outer Ring Road as a case study, this research analyzed the spatial distribution changes at both the macro and micro scales based on Dianping.com data from 2017 and 2022. A multinomial logit model was employed to examine the relationship between eWoM and consumption spatial distribution. The results reveal that: 1) Optical stores showed a trend of penetrating into less favored locations, with expansion primarily toward sub-optimal locations at the macro scale, and dispersion toward non-ground floors, especially higher floors, at the micro scale. 2) stores with high ratings accounted for a larger proportion in less favorable locations than in prime locations, revealing a spatial mismatch between locational advantages and service quality, with this pattern being particularly pronounced at the micro scale. 3) the multinomial logit analysis indicated a strong association between electronic word-of-mouth ratings and spatial distribution, with each one-unit increase in rating decreasing the probability of a store being located in macro- and micro-level prime locations by 11.4% and 13.5%, respectively. This study deepens the understanding of the restructuring of consumption spaces in the digital era and provides insights for the optimization and renewal of urban commercial spaces.
The development of digital media has transformed traditional human-environment relationships, as specific narratives and story scenarios within media continuously attract people to visit destinations. Some traditional villages have become Internet-famous check-in spots through the viral dissemination of digital media. However, more traditional villages remain marginalized due to their lack of discursive power in daily spatial representation, raising questions about how they can leverage digital media to gain modern recognition. This study took Taipan Village in Guizhou Province as a case to analyze how multiple actors present and shape this traditional settlement in four dimensions from the digital media perspective: representational change, relational construction, local practices, and power dynamics. The findings reveal that: 1) The spatial representation of traditional villages evolved in phases around media events. 2) The construction of digital-real relationships facilitated consensus on meanings. 3) Individual remote and on-site practices co-created localized symbolic representations. 4) Power dynamics created tension between digital capital operation and local identity preservation, steering development toward sustainability. The research expanded application scenarios for media geography, illuminated the place-making process of traditional villages, and provided insights for innovative and sustainable development of traditional settlements in the digital media era.
Improving total factor ecological welfare performance is a key issue for achieving high-quality development in the Yellow River Basin. Based on the city panel data of the Yellow River Basin from 2010 to 2021, this study adopted the slacks-based measure and directional distance function (SBM-DDF) model to evaluate total factor ecological welfare performance, used the traditional and spatial kernel density estimation methods to explore its spatiotemporal change characteristics and long-term transfer trends, and identified the main influencing factors of change through quantile regression. The research findings are as follows: 1) During the study period, the total factor ecological welfare performance in the Yellow River Basin showed an overall upward trend, with an average annual growth rate of 1.36%, showing regional imbalance of downstream > midstream > upstream. 2) The overall performance distribution showed a unipolar-multipolar temporal trend, with the upstream forming a clear bipolar differentiation pattern, the midstream experiencing bimodal oscillation before returning to a unimodal steady state, and the downstream achieving coordinated development of performance improvement and difference convergence. The overall basin and upstream-midstream regions all showed characteristics of low-level and medium-level cities moving upward and high-level cities moving downward, with only the downstream region achieving upward change across all performance levels. When considering spatial conditions, the overall basin and upstream regions showed positive spatial spillover effects, while high-performance areas in the midstream and downstream regions exhibited a "beggar-thy-neighbor" phenomenon. 3) The change of total factor ecological welfare performance in the Yellow River Basin was influenced by the combined effects of environmental regulation, urban greening, and financial development. Environmental regulation showed significant positive effects at all quantiles across the basin, becoming the primary driving force for the rightward shift of the performance distribution curve. Infrastructure in the upstream region had bidirectional effects of low-quantile suppression-high-quantile promotion, facilitating the formation of the bimodal structure. The research conclusions provide a scientific basis for optimizing ecological welfare spatial governance in the Yellow River Basin and formulating differentiated strategies for improving people's welfare, and offer a reference for achieving the strategic goals of ecological protection and high-quality development in the Yellow River Basin.
The goal of studying the regional integrated system of human-environment relationships is to improve the virtuous cycle of human-environment interactions within the regional system. The mechanisms and functional evolution of the interactions between natural and human elements at different spatial levels are different. Identifying the multi-level characteristic scales of the regional integrated system of human-environment relationships is of great significance for optimizing the territorial spatial pattern. Using the wavelet analysis method and taking land use as the entry point, this study identified the multi-level characteristic scales of the human-environment relationship complex system in Northwest Hunan Province. The results show that: 1) The land use types in the study area are mainly forest land, followed by cultivated land, and the potential for optimizing the territorial spatial pattern is relatively large. Along the transect, there is a significant positive correlation between the distribution of forest land and elevation, while the distribution of cultivated land, wetlands, water bodies, and artificial surfaces shows a significant negative correlation with elevation. The correlation between grassland distribution and elevation is not significant. 2) Through a comparative analysis, we found that the Cmor wavelet function is more suitable for identifying the multi-level characteristic scales in the study area. 3) The spatial characteristic scales of the integrated system in the northwestern region of Hunan can be divided into four levels, with sizes of 36 km, 18 km, 8 km, and 5 km respectively. This study provides a theoretical support and practical guidance for the transmission of multi-scale territorial spatial governance policies, and offers a scientific basis for the multi-scale transformation and functional cascade effect analysis of the regional integrated human-environment system.
The Western Pacific Subtropical High (WPSH) is a key atmospheric circulation system that significantly influences summer precipitation in the eastern monsoon region of China. Future projections indicate that the WPSH is likely to exhibit a strengthening and westward extending trend, driven by suppressed warming in the Western Pacific and an enhanced land-sea thermal contrast. However, the interdecadal variations of WPSH show greater uncertainty, complicating the understanding of its long-term change. In this study, based on daily precipitation data of 277 meteorological stations on the Loess Plateau during the period of 1970-2020, we analyzed the spatiotemporal variation of summer precipitation using the Theil-Sen trend analysis and extreme-point symmetric mode decomposition method. More specifically, four types of combination between the summer ridge line and the westward ridge point position of the WPSH were defined. These combinations are instrumental in identifying the sensitive areas of summer precipitation on the Loess Plateau in response to WPSH variations. The results show that the summer precipitation on the Loess Plateau was dominated by interannual fluctuations from 1970 to 2020. Spatially, from 2003 to 2020, in the southeastern part of the Loess Plateau, the number of stations with summer precipitation exceeding 300 mm increased from 48 in the earlier period to 81. However, this increase did not alter the established spatial pattern of summer precipitation, which remains characterized by "more in the southeast and less in the northwest" across the Loess Plateau. Further analysis revealed that the Fenwei Plain is a sensitive region to the anomalous east-west displacement of the WPSH. When WPSH position is anomalously westward, the Fenwei Plain tends to experience an anomalously high amount of precipitation during the summer. Meanwhile, the location-anomaly response relationship indicates that when the WPSH shifts westward, precipitation increases over the Loess Plateau, whereas an eastward shift corresponds to reduced precipitation. The ridge line, relative to its multi-year mean position at 26.7°N, primarily modulates the southeast-northwest dipole pattern of precipitation anomalies. The findings indicate that when the WPSH is likely to remain strong with its westward ridge point position shifting obviously westward in the future, projected persistent and heavy summer precipitation in the southeastern part of the Loess Plateau would heighten the risk for urban system in adapting to extreme precipitation events. It is necessary to formulate integrated risk governance strategies on the Loess Plateau to address the urgent risks posed by extreme climate change.
Urban parks are key spaces for regulating thermal environments, but their uneven distribution and insufficient cooling effects often lead to spatial mismatches with residents' needs. Scientifically assessing the supply and demand relationship of urban parks' day-night thermal environment regulation services is of great significance for optimizing the urban day-night thermal environment and promoting environmental justice. Previous studies have mainly focused on the daytime thermal environment, with insufficient attention paid to the nighttime thermal environment. The indicator system for assessing supply and demand needs to be further improved. In addition, previous optimization strategies based on the assessment of supply and demand are more general, failing to fully consider the heterogeneity of the causes of key imbalance areas, leading to the negligence of specific causes and the lack of targeted planning interventions. In response, this study employed a thermal environment regulation service supply-demand assessment framework. Using streets as units of analysis, and treating park cooling capacity as the supply and thermal risk—comprising hazard, vulnerability, and exposure—as the demand, this study analyzed the supply-demand relationship through four-quadrant analysis and priority index, classified planning intervention priorities, identified typical supply-demand imbalance areas, and proposed targeted optimization strategies. The results indicate that: 1) There are significant spatial differences in the day-night thermal environment regulation service supply capacity of parks in the central urban area of Shijiazhuang City. Streets with low supply capacity in both daytime and nighttime are clustered in the old urban area, reflecting a significant supply deficiency. 2) The overall demand level shows a pattern of high in the center and low in the periphery, but there are differences between daytime and nighttime. High-demand streets extend westward and southward during the day, while at night, high-demand streets are located in the southwestern part of the center. 3) Most streets exhibit mismatches between supply and demand in both daytime and nighttime, with the highest proportion of "low supply-high demand" streets, accounting for 36% during the day and 41% at night. 4) Based on the degree of supply-demand imbalance, streets are divided into five levels, and 11 typical imbalance areas that require priority intervention in both daytime and nighttime are identified, which are mainly concentrated in the old urban area. These imbalances are mainly caused by the combined effects of multiple factors, with most streets showing insufficient park cooling capacity. In response, differentiated optimization strategies are proposed to provide a scientific basis for optimizing park resource allocation and enhancing thermal environment regulation services in Shijiazhuang City, and to offer a methodological framework for other cities.
Humanistic geography and behavioral geography represent two pivotal schools of thought within human geography, each possessing distinct theoretical and methodological foundations. Despite their significant potential for mutual enrichment, scholarly discourse, particularly within some regional academic contexts, has not fully explored the inherent complementarity between these two paradigms. This article offers a comparative study of their leading proponents, Yi-Fu Tuan for Humanistic Geography and Torsten Hägerstrand for Behavioral Geography, whose seminal works have profoundly influenced geography and cognate disciplines. Employing a tripartite analytical framework that examines representative figures-school characteristics-methodological system, this study meticulously compared their academic trajectories, core theoretical propositions, and methodological approaches. It specifically endeavored to uncover the humanistic undercurrents within Hägerstrand's time geography and to scrutinize the behavioral dimensions underpinning Tuan's experiential perspective. This comparative lens allowed for a nuanced analysis of each school's characteristics, thereby elucidating their critical distinctions and, more importantly, their areas of convergence. Both schools emerged from a shared critique of the "rational economic man" assumption prevalent during the quantitative revolution, instead emphasizing the intricate interplay of human behavior, emotion, and lived experience of place. In doing so, they introduced vital human-centered dimensions to geographical inquiry. A multi-dimensional analysis—encompassing ontological foci, philosophical foundations, epistemological stances, research methodologies, and practical applications—reveals significant compatibilities and potential synergies. The concept of "home", a profound concern for both scholars, serves as a compelling unifying thread, highlighting their shared commitment to understanding the deep meanings of place and human dwelling. This dialogue between Humanistic and Behavioral Geography not only facilitates theoretical cross-fertilization but also promises to stimulate new theoretical innovations. The article concludes by advocating for continued and strengthened exchanges among diverse schools within geography. Such inter-paradigmatic dialogues are essential for identifying the unique methodological value of each school, exploring fruitful integrations of ideas, theories, and methods, and ultimately propelling the ongoing development of the geographical discipline.
