Households are a key carrier for urban spatial reconfiguration and socioeconomic transition, and also a crucial intermediate level between the individual, the community, and the city. Existing studies have recognized the importance of research on spatial-temporal behavior from the perspective of households, but they usually take the characteristics and division of responsibilities of households as background and explanatory factors. The interactions and connections between household members are rarely considered, and the complexity of intra-household behavioral interactions of various households and different types of behavior is not well understood. This research focused on household and intra-household behavioral interactions. First, it created a time-space-society framework to measure behavioral interactions in three dimensions, that is, temporal interaction, spatial interaction, and social relationship interactions, and refined the patterns of intra-household behavioral interactions. Second, it revealed the mechanisms of influence and effects of intra-household behavioral interactions, taking China's socioeconomic background into account. Finally, aiming to improve the quality of life of household members, it proposed an optimization scheme of living space with the household-friendly orientation. The research contributes to reintroducing the household level in urban research based on spatial-temporal behavior, and promoting behavioral geography research to emphasizing individuals' interactions. It also provides new ideas for examining social issues such as fertility, as well as child and elderly care, offering a scientific reference for the optimization of community life circle and urban space, and promote household-friendly urban planning and social governance.

The water storage information retrieved by GRACE satellite provides high-precision data for the study of water cycle process. However, assimilating terrestrial water storage change data of GRACE satellite into existing distributed hydrological models for streamflow simulation has become a key scientific challenge in utilizing GRACE data to improve the accuracy of water storage and streamflow simulations. Based on a review of current research progress, this article summarized the commonly used methods for assimilating GRACE water storage change data into distributed hydrological model, the principles and advantages/disadvantages of existing data assimilation approaches, and the extent to which different data assimilation methods improve the accuracy of hydrological modeling for water storage and streamflow simulations. Furthermore, this study identified the problems associated with assimilating GRACE water storage change data into distributed hydrological models and then proposed possible solutions to these problems. The results of this study indicate that the challenges in assimilating GRACE water storage change data into distributed hydrological models include: 1) the contradiction between the high spatial and temporal modeling requirements of hydrological models and the low spatial and temporal resolutions of GRACE data and 2) the discrepancy between the individual simulation of water storage components in distributed hydrological models and the representation of total terrestrial water storage changes by GRACE data. Findings from previous studies in different river basins manifest that assimilating GRACE water storage data can reduce the root mean square error of water storage simulations by approximately 5% to 40% and increase the correlation coefficient of water storage simulations by about 10% to 50%. However, the improvement in streamflow simulation accuracy is relatively limited, with an increase in the correlation coefficient of approximately 2% to 16%. This research provides theoretical and methodological references for the development and application of hydrological models assimilating GRACE satellite water storage data.

From the perspective of urban science, this study assumed that the development of built-up areas follows certain natural law. Using the conventional and reconstructed scaling expression of rank-size distribution models, this study analyzed built-up area and population size distributions, and examined whether the size of built-up areas follow the Gibrat's law. The conventional expression of rank-size distribution is from empirical patterns while the reconstructed one is mathematically derived from a hierarchical fractal system. Thus, the reconstructing process itself is to connect the empirical phenomenon to the hidden order, which is consistent with the perspective of urban science. Specifically, to match the area and population datasets, this study first applied city cluster algorithm to delineate all built-up areas in China, using the global impervious area data. Then the boundaries of built-up areas were used to aggregate population size from the LandScan world population product. The study found that the area size of built-up areas follows the rank-size distribution under both models, while the population size follows that only under the reconstructed model. Moreover, the Gibrat's law is not suitable for explaining the rank-size patterns of the built-up area system. The research results reveal the structural differences in the dynamic mechanism of urban development and population mobility within built-up area systems in China. Urban development shows a tendency of centralized management, and area expansion is easier/quicker than population growth. The potential contribution of this research is two-fold: first, the reconstructed scaling model can filter data noises algorithmically and thus can be used as an optimization algorithm for large sample size sequence-scale analysis; second, the reconstructed scaling model has a macroscopic structure that provides an explanation for rank-size distribution, that is, the rank-scale schema is a macroscopic pattern and hidden order, which needs to be rediscovered through reconstructing the empirical data.

Under the background of high-quality urban development in Chinese-style modernization, building open, diverse, and resilient livable community life circles has become an important aspect of the sustainable development of future cities and the improvement of residents' quality of life and sense of well-being. The spatial and temporal optimization of facilities in community life circles is an important direction for urban renewal and transformation. This study took the Dangdai-Yimei community life circle—an area located in the suburb of Beijing—as a case study area, and combined spatial syntactic modeling with spatiotemporal characteristics of residents' daily activities. By conducting a spatial environment evaluation at the scale of urban community life circle, we put forward recommendations for spatial optimization. The study found that space with high availability in spatial syntactic measurement results is usually rarely used in residents' daily life due to access control management, behavioral needs, work arrangements and other factors. The fact that residents indirectly use facilities in other communities reveals the need for sharing of space between communities. Within the community life circle, there are shortcomings such as inadequate facility allocation and insufficient public spaces. Shopping facilities are located far from residential areas, leading to fewer shopping activities within the community life circle. The lack of leisure spaces forces residents to use the major transportation hub as leisure spaces. Finally, the low activity of working professionals within the community life circle during weekday evenings reflects the inadequacy of spatial flexibility planning. We recommend that in the future, human behavioral needs should be integrated with the spatial structure characteristics of the built environment in communities. This includes advocating for increased openness and sharing between communities within community life circles, diversifying the functions of public spaces, and appropriately adding flexible activity spaces. These efforts aim to create more livable and harmonious living activity spaces.

Family constraints on individuals are an important topic in behavioral research in China and internationally, yet large-scale data and effect measurements are lacking. Based on existing studies, this research proposed a family constraint index on commuting distance (hereafter referred to as the constraint index) to quantitatively measure the effect of family constraints on individual members' commuting distance. Taking the Wuhan Metropolitan Development Area as an example, the June, 2019 Unicom cell phone signaling data were used to identify the family samples through the social network model, calculate the constraint index of the family on members of different ages, genders, and single-multiple workers, and quantitatively analyze the effect of family constraints on individual commuting behaviors. The study found that, first, the family has obvious constraints on the commuting distance of both male and female members, and the constraints of females are all positive, that is, the commuting distance is smaller for females with family constrains than those with no family constraints, whereas the constraint of males in multi-employee families are mostly negative, that is, the commuting distance for males with family constrains is greater than those with no family constraints. So women are generally more constrained by their families than men, and men in multi-worker households are the least constrained. The constraint index of females in single-worker households increases with age, and gradually converges with that of females in multi-worker households, while the constraint index of males in multi-worker households is stable at around 0.03. The proposed method based on big data expands the approaches for the study of commuting behavior with family members as the target, and provides references for various theoretical studies on family constraints, as well as the refined modeling of family influences on individual behaviors.

The sustainable development of rural communities in contemporary China bears particular importance, and understanding the mechanisms of change of rural community spaces is vital for scientific advancement. This study, based on sampling surveys and on-site interviews with rural inhabitants in Jingshan City on the Jianghan Plain, established a comprehensive indicator system with indicators spanning from infrastructure, living environment, to spatial organization. Using system dynamics equations, it primarily focused on the number and matching relationships of living service facilities to evaluate the evolutionary traits and mechanisms of rural community spaces, consequently establishing the optimization goals and paths. The research found that: 1) During the study period, the level of rural community living service facilities in the Jianghan Plain greatly improved, with a notable reduction in regional differences. The comprehensive index of rural community space increased from 0.2205 to 0.3742, while the coefficient of variation fell from 0.1700 to 0.0545. The living environment dimension was the largest element in this spatial change, contributing 67.07%, with important contributions from living conditions (43.30%). 2) The coordination of rural community space was insufficient, with an overall coordination value of merely 0.0114. Structural matching was inadequate, and the spatial organization coordination index stood at a meager 0.0001. Mutual inhibition between infrastructure and the residential environment (β₁₂>β₂₁>0), as well as between the residential environment and spatial organization (β₃₂>β₂₃>0), likely inhibited the collaborative change of the rural community spatial systems. 3) The rural community areas on the Jianghan Plain demonstrated systematic evolutionary traits. The interim optimization target comprises improving the indices of infrastructure, living environment, and spatial organization to 0.4510, 0.6867, and 0.2846 correspondingly, and boosting the overall coordination index to 0.3400. The study provides optimization routes concentrating on the number and matching relationships of rural living service facilities.

The social integration of the migrant population is an important indicator of the effectiveness of the household registration system reform and new urbanization, and is of great practical significance for the implementation of high-quality population development in the new era. Based on the 2017 China Migrants Dynamic Survey (CMDS) data, this study investigated the subjective social integration degree of China's migrant population from a binary analysis perspective of individual integration intention and perceived acceptance degree. It explored the spatial heterogeneity of influencing factors using the multiscale geographically weighted regression (MGWR) model. The following conclusions are drawn. 1) The subjective social integration degree of the migrant population was relatively low in the southeastern coastal and Qinghai-Tibet Plateau regions and relatively high in the northern, central, and Sichuan-Chongqing regions. The spatial patterns of individual integration intention and perceived acceptance degree were similar to the subjective social integration degree of the migrant population. 2) The subjective social integration of the migrant population was influenced by a combination of individual internal factors and external city factors. Individual integration intention showed a positive effect in southern and northwestern China and a negative effect in Shandong Province and surrounding areas, while perceived acceptance degree showed a global positive effect decreasing from north to south. Subjective social integration was also affected by a global gradient of age and distance of migration and a locally significant effect of gender, ethnic diversity, and economic level. The scale of spatial heterogeneity in the effects of the variables varied significantly, with spatial heterogeneity more pronounced for individual integration intention, perceived acceptance degree, and gender. 3) The effect of individual integration intention on subjective social integration degree was moderated by the negative spatial moderating effects of marriage, educational level, and migration time, as well as the positive spatial moderating effect of public services. The effect of perceived acceptance degree on subjective social integration degree was moderated by the negative spatial moderating effects of age and education level as well as the positive spatial moderating effects of marriage and public services. The study revealed the spatially nonstationary mechanism of subjective social integration of the migrant population, which provides more precise and optimized policies for the governance of the migrant population in each region based on the perspective of social integration.

Population is the dominant factor of regional development. In the context of coordinated population and regional development, this study took the Hu Huanyong line as reference to define the westward migrants, whose outflow place is in the southeastern side of Hu Huanyong line, while inflow place is in the northwestern side of Hu Huanyong line. Based on this definition, this study analyzed the settlement intention of China's westward migrants and its influencing factors. The analysis used the data of the China Migrants Dynamic Survey in 2017 and the corresponding regional data, and the non-parametric test and multilevel mixed-effects logistic regression methods. The results are as follows: 1) About 30% of the westward migrants chose stable residence, and the settlement intention is at a relatively low level while the vast majority of migrants chose temporary residence. With regard to destination cities, with the increase of urban scale, the settlement intention of migrants became higher. 2) The westward migrants from central China to the northwestern provincial capital cities or regional central cities were more likely to choose stable residence. 3) Settlement intention was influenced by both economic and non-economic factors. At the individual level, residence time, family size, family income, employer status, ownership of housing, active social interaction and psychological integration, and participation in social health insurance had positive effects on settlement intention. The migrants from the northern cities to the southeast of the Hu Huanyong line had a higher settlement intention. At the regional level, altitude had an inhibitory effect on settlement intention, while local development vitality and city size played a positive role. However, GDP per capita and medical and health conditions played no significant role. Based on the above research findings, this study recommend to promote the settlement intention of the westward migrants by steadily increasing income, constructing family-friendly policy system, creating inclusive social and cultural environment, and let urban agglomerations play a leading role.

The flow of cultural ecosystem services, as a bridge between the supply of ecological resources and the needs of human society, represents the nonmaterial benefits that people actually receive from ecosystems and is closely related to human well-being. National parks are spatial carriers to realize the value of natural resources and benefit the general public in typical ecosystems. They take ecological protection, scientific research and education, and recreational use as management objectives to satisfy people's needs for beautiful ecological environments, excellent ecological products, and high-quality ecological services. Taking the Liaohekou National Park as a case area, this study constructed a spatial multiscale integration framework for cultural ecosystem service flow based on the research paradigms for different spatial scales, used multiple source data such as remote sensing and social media data, and applied spatial analysis tools such as the MaxEnt model and ArcGIS platform to evaluate the spatial patterns of recreational, biodiversity, historical, scientific, and educational services provision and flow of the ecosystem and their influencing factors in the study area. The results show that: 1) In general, at the intraregional scale, the total supply of various cultural ecosystem services is greater than the intraregional service flows, and the four types of cultural ecosystem service flows are mainly concentrated in estuaries and eastern coastal areas; at the interregional scale, the distribution of various types of cultural ecosystem service flows is mainly related to the level of economic development, especially in coastal provinces and municipalities. 2) At different spatial scales, the factors that influence the spatial distribution of cultural ecosystem service flows have different strengths, among which the distance from national parks and economic factors show significant differences at different scales, with the former showing strong-weak-strong changes within the region, province, and the whole country, and the latter showing weak-strong-strong changes. The spatial multiscale integration framework of cultural ecosystem service flow constructed in this study is not only an exploratory study on the distribution pattern and mechanism of cultural ecosystem service flow, but also provides a reference for improving the management efficiency and ecological product supply capacity of national parks, and promotes the construction of national park protected area system.

Global warming has led to accelerated changes in the global hydrological cycle, resulting in an increasing number of extreme events and compound events in which multiple extreme events occur simultaneously or consecutively, and are more hazardous than a single extreme event. The Yangtze River Basin has always been one of the areas with the most frequent extreme weather and climate events and disasters in China and has also experienced more severe compound events in recent years due to global changes, which has seriously constrained ecological protection and high-quality development in the region. The Yangtze River Basin is one of the most populous and economically developed regions in China, and climate change and human activities have significantly affected the distribution of water and heat conditions in the region. Therefore, taking the Yangtze River Basin as an example and based on long-term historical observations and CMIP6 model prediction data, this study adopted the compound drought and heatwave magnitude index (CDHMI) to identify compound drought and heatwave events (CDHEs) in the Yangtze River Basin, used cumulative probability density curves to classify the intensity of CDHEs, and explored the spatial and temporal evolution patterns of the compound drought and heatwave events as well as the future trends. Meanwhile, to ensure the accuracy of the data, the applicability of the 23 CMIP6 models in the Yangtze River Basin was assessed using three evaluation metrics, which improved the credibility of future CDHEs predictions. Finally, the spatial changes of CDHEs in the Yangtze River Basin under different future scenarios were characterized based on a multi-model ensemble of 23 CMIP6 data. The results of the study show that: 1) During the historical period, the frequency and duration of CDHEs showed a non-significant increasing trend. The frequency and duration of CDHEs were the highest in July, at 0.511 times and 3.59 days, respectively. The frequency of mild CDHEs was the highest in the historical period, with an annual average frequency of 0.4 times, which mainly occurred in the middle and lower reaches of the Yangtze River Basin, the Hengduan Mountains, and the Yunnan-Guizhou Plateau. 2) Among the 23 CMIP6 models, INM-CM4-8, ACCESS-ESM1-5, NESM3, NorESM2-LM, and INM-CM5-0 are the five most suitable models for the Yangtze River Basin after bias correction. 3) In the future, the middle and lower reaches of the Yangtze River Basin will be the areas with high frequency and long duration of CDHEs, and the annual average frequency and duration of CDHEs by the NorESM2-LM model are the highest. The results of the five models and multi-modal ensemble also show small differences between scenarios in the short term and medium term and significant differences in the long term. In the long term of SSP5-8.5, the average annual frequency of CDHEs would increase by 2.3 times and 1.8 times, respectively, compared to the short term and medium term under the same scenario. The duration was 29.9 days and 21.3 days higher than that of SSP1-2.6 and SSP2-4.5 during the same period. The average annual frequency of mild CDHEs is the highest for all three scenarios, and all severity events should peak at SSP5-8.5. This findings can provide scientific and technical support to actively mitigate future climate change risks in the Yangtze River Basin.

When selecting investment locations, evaluating a region's or country's investment environment is crucial for enterprises. However, existing research often falls short of meeting the current practical needs of businesses. To address this gap, we conducted a field research and developed a comprehensive indicator system to assess Vietnam's investment environment across six key dimensions: factor endowment, infrastructure, industrial development, market conditions, financial environment, and institutional context. Based on this framework, we categorized Vietnam's investment environment, analyzed the key regions for investment and priority investment areas, and proposed four specific investment strategies. The study yielded vital findings: 1) Vietnam's investment environment across multiple dimensions—factor endowment, infrastructure, industrial development, market conditions, financial environment, and institutional context—generally falls within average to medium levels. There is a notable spatial distribution pattern where some areas show high local values, but the overall investment environment remains relatively poor. 2) The investment environment in Vietnam exhibits a clear spatial imbalance. Provinces such as Ho Chi Minh City, Hanoi, Hai Phong, Binh Duong, Dong Nai, and Ba Ria-Vung Tau stand out, ranking above the national average. 3) Vietnam's investment environment can be categorized into five types: priority investment zones, key investment zones, general investment zones, potential investment zones, and cautious investment zones. The spatial distribution of these zones aligns with Vietnam's key economic regions, which are in the north and the south. 4) Investment preferences vary by region. The northern critical economic zone develops industries like electronics, machinery manufacturing, and new energy. In contrast, the southern critical economic zone focuses on industries such as textiles and garments, food processing, and high-tech sectors. This research provides a scientific basis for enterprise investment decisions in Vietnam, fosters China-Vietnam economic and trade cooperation, and supports the long-term development of a resilient China-Vietnam community with a shared future.

Research on crime geography has traditionally focused on objective criminal activities and neglected subjective perceptions such as fear of crime, which is its major shortcoming. Using the deep learning algorithm of image regression, we analyzed the level of fear of crime under different streetscape environments on a large scale in the central urban area of Beijing. This approach compensates for the limitations of social surveys in terms of spatial coverage, spatial resolution, and reliability and validity of measures. Our indigenous deep learning models also make up for the lack of established models that rely on western city street view images and overseas labelers. Our study shows that, first, the spatial pattern of fear of crime has a circular, multi-cluster, and radial structure, and its level gradually increases from the city center to the suburbs. In contrast, the density/number of theft and violent crimes have the spatial distribution with the opposite trend. Second, according to the relationship between the spatial distribution of fear of crime and criminal activities in general, we find a low match between subjective and objective security in the city center, with the objective situation being more dangerous than the subjective perception; in the suburban areas, the degree of match between the two increases; to the outer suburbs, these two still have a low degree of match, but the objective situation is safer than the subjective perception. Third, the built and social environmental factors that influence subjective and objective security are not always identical. A high-density and highly mixed environment would reduce fear of crime, but may accelerate crime. To reduce both fear and crime, it is recommended to add cul-de-sacs, improve the sense of enclosure, increase the amount of greenery, and eliminate various types of physical disorder. As for the effect of social disorganization, concentrated disadvantaged communities tend to have high levels of fear and are more prone to violent crime; population mobility can help reduce fear of crime; residential heterogeneity would exacerbate criminal behavior. Our findings help to clarify the differential explanatory power of classical crime geography theory for subjective and objective security, which in turn facilitates a comprehensive assessment of the security consequences of environmental intervention policies.

As a formal supervisory force, police stops have a significant impact on the spatiotemporal distribution of crimes. However, existing research lacks sufficient discussion on the endogeneity issues between police stops and crimes, as well as an in-depth exploration of the spatiotemporal patterns and preventive effects of police stops in the central business districts (CBDs) of large cities. Therefore, this study took the CBD police station located in the core area of the CBD of ZG City, a big city in southern China, as an example, and used exact spatiotemporal big data of police stops and street thefts to analyze their spatiotemporal pattern characteristics. Then we applied the share-shift method to construct the Bartik's instrumental variable to analyze the causal effect of police stops on street thefts. This study found that: 1) Police stops in the CBD showed an obvious hotspot clustering trend, and their spatiotemporal coverage mainly included sustained hotspots, continuously enhancing hotspots, historical hotspots, new hotspots, and dispersed hotspots, with varying spatiotemporal relationships between police stops and street thefts for different hotspot types. 2) Endogeneity issues affect the assessment of the causal effect of police stops on crimes. After considering instrumental variables, we found that police stops in the CBD had a significant deterrent effect on the occurrence of street thefts, and for every one standard unit increase in the number of police stops in the previous week, the number of street thefts in the current week will drop by about 0.243 cases. This research focused on the quantitative study of the spatiotemporal relationship between daily police activities and criminal behaviors. The findings can serve as a scientific basis for refining the planning of police stops, enhancing patrol efficiency, and realizing the rational allocation of police resources.

As the main actor in crime prevention and control, the activities of the police department have an important impact on the spatial trend of criminal activities. This study focused on the police inspection activity data and theft crime data from May to December 2019 in Haining City of Zhangjiang Province. Grids were employed as the spatial units of analysis, and the study used kernel density estimation and spatial autocorrelation analysis to examine the spatial distribution characteristics of police inspections and theft crimes. Additionally, a spatial regression model was constructed to analyze the impact of different types of police inspections, including routine security checks, inspections of public complex industries, and inspections of key units, on theft crimes. The findings are as follows: 1) Both police inspections and theft crimes exhibited spatial clustering characteristics, with some overlap in hotspot areas. While the spatial distributions of routine security checks, inspections of public complex industries, and inspections of key units were generally similar, there existed certain differences. 2) Inspections of public complex industries and key units were significantly negatively correlated with theft crimes, whereas routine security checks showed a significant positive correlation with theft crimes. 3) Routine security checks in adjacent areas were significantly positively correlated with theft crimes in the local area, suggesting a potential phenomenon of crime site displacement. These results suggest that inspections of public complex industries and key units played a significant inhibitory role in theft crimes, while routine security checks may lead to crime site displacement. The conclusions of this study provide significant reference value for clarifying the relationship between police activities and crime, as well as for assessing the effectiveness of police activities in crime prevention and control.

As an important carrier of civilization inheritance and cultural self-confidence, China's cultural relics have been repeatedly looted and excavated by lawbreakers, which greatly hinders the archaeological exploration of Chinese civilization and the construction of national cultural relics security and cultural self-confidence, and deserves the attention of all sectors of society. Given the lack of focused exploration of the high-incidence areas of this type of crime from the perspective of geography, this research selected Henan Province, one of the hardest-hit areas of criminal looting of cultural relics in China, as the research area, and used the methods of text analysis, mathematical statistics, and spatial analysis to explore the case characteristics, spatial pattern, and formation mechanism of these incidents, to provide a reference for the prevention of criminal looting of cultural relics. The results show that: 1) Most of the offenders were middle-aged and elderly men with low education and low income who dwelled in Henan Province; the looted cultural relics were mainly the ancient tombs of the Qin, Han, Xia, Shang, and Zhou dynasties that lack protection measures; the types of the stolen archaeological artifacts included pottery, masonry products, bronze, porcelain, among others; the micro-environment of the looted cultural relics involved rural settings, above-ground cultural relics, and construction zones. 2) Spatially, the incidents were concentrated in the northeastern and northwestern regions of the province, with two high-incidence cities (Anyang and Luoyang) and three secondary high-incidence cities (Zhengzhou, Kaifeng, and Zhumadian). At the county scale, there was a "high-high" and "high-low" agglomeration; the distribution of high-incidence areas and hotspots was consistent with the city-scale distribution. Over time, the high-incidence area first shifted from the Runlou Site area in the south to the Han-Wei Ancient Luoyang City and Mangshan Mausoleum Group in the northwest, and then moved to the Yinxu Site area in the northeast. 3) The distribution of cultural relics and the educational level of local residents were the main influencing factors of the crime. The distribution of cultural relics highly overlapped with both the residences of the looters and the locations of their crimes, that is, criminal looting of cultural relics in Henan Province showed obvious characteristics of crimes committed by local inhabitantswhich were related to historical, economic, demographic, and social factors and can be explained according to the social disorganization theory and rational decision theory.