In recent years, contact crime represented by theft and non-contact crime represented by telecommunication network fraud are both increasing, seriously affecting social stability and people′s property security. Previous studies have paid less attention to the spatial and temporal stability of different types of crime distribution patterns, and no research has yet compared the spatio-temporal stability of contact crime and non-contact crime. In the meantime, current studies also failed to propose spatial joint prevention and control strategies for different types of crime. This study takes HT District of ZG City as an example, takes the community as the analysis unit, uses kernel density estimation and space-time transition measure method to compare and analyze the spatio-temporal distribution characteristics and monthly stability of the spatial distribution pattern of theft and telecommunication network fraud in 2017. After that, we refer to the idea of spatio-temporal transition to improve the method of space-time transition from the perspective of crime prevention and control, and then identified the spatial prevention and control types of theft and telecommunication network fraud. Based on this, combined with the method of two-step cluster to recognize the joint prevention and control spatial types of two kinds of crime. The findings are as follows: (1) The spatial and temporal stability of the two types of crime is different. The spatial distribution pattern of theft crime is stable and its spatio-temoral transition indexes of adjacent months are more than 50%. However, the spatial distribution pattern of telecommunication network fraud is unstable and fluctuates greatly on the whole. What it is worth to mention is that the pattern is especially stably in February and March. (2) Four spatial types of joint prevention and control of these two types of crimes are recognized, which are respectively "two types of crime without prevention and control communities", "two types of crime neighborhood prevention and control communities", "theft crime hotspot prevention and control, telecommunication network fraud without prevention and control communities" and "theft crime coordinated prevention and control, telecommunication network fraud comprehensive prevention and control communities". This study is helpful to understand the similarities and differences between contact crime and non-contact crime in time and space, and provide guidance for police prevention and control.

As the spatial carrier of people's daily behaviors, the street network and behaviors therein constitute the main spatial environment of street network, which affects criminal behavior. Previous studies have shown that there are frequent cases of robberies and thefts in the streets, and the street network pattern and routine activity subjects are both related to crime. However, there are few in-depth explorations of such a relationship. Based on the police patrol area unit of the original DP District of HS City, this paper has adopted spatial analysis and statistical analysis methods to analyze the road network data, demographic data, mobile phone signaling data and other relevant data in order to explore the relationship between crime and street morphological characteristics including geometric and topological form, the relationship between crime and routine activity subjects including dynamic population and static population, and the impact of the street network on robberies and thefts. The results have shown that the factors affecting thefts and robberies in the street network are quite different. The factors affecting the theft crime are more complex. "X-cell" street network, road network density, road network permeability of low-speed traffic, static population density and dynamic population density all have an important impact on thefts. Only the branch density has a negative effect, and the rest of the factors have a positive effect. "T-cell" street network, density of actual residents and migrants in static population are related to robberies. But the street network pattern has not shown a significant correlation with robberies. In general, the street networks with more main roads, better accessibility, higher population density, and higher population mobility are prone to thefts. The street networks with many migrants are prone to the robberies. In addition, the findings of this study can also make certain extensions to the crime pattern theory. Since the accessibility of street network often brings risks, it is proposed at the end of the paper that it is imperative to consider how to reduce the crime risks as much as possible by regulating or improving the overall spatial environment of street network during the planning and construction of a safe street network environment in the future.

This study aims to identify the main types, their magnitudes of influence, and their characteristics of regional heterogeneity of theft places, and take the lead in discussing the application of geographical detector in the field of crime geography analysis. Using criminal judgement, Points of Interest, Location-based Service data, road network, census data, housing data, and other data in the central urban area of Beijing and taking the 1 km×1 km square grid as our spatial analysis unit, this research demonstrates that thirty-seven types of urban facilities belong to the major crime generators, crime attractors or crime enablers at the global level, and the edge areas of roads, administrative districts and land uses are also proved to be evident theft locations. Among them, the more influential theft locations are more aligned with the crime generating conditions proposed by crime pattern theory, including accessible crime target and lower risk of arrest. Second, as stated by social disorganization theory, if the level of social disorganization composed by mobility factor and housing factor decreases, the number of theft location types as well as their impacts will gradually diminish. But except for the low social disorganization districts, the rankings of relative influence of various facilities and edge areas on theft crime remain relatively stable. Third, geographic detector has the advantages of no linear hypothesis, no collinearity problem, clear physical meaning and so on. But owing to the neglect of the potential interference by confounding factors, geographical detector would probably overestimate the impacts of independent variables. It can be testified by the moderate correlation between the rankings of the overall influence of theft locations obtained from the negative binomial regression and those calculated by the geographical detector. We suggest that combining elimination control method with geographical detector is a feasible path to achieve robust results, so classification discussion after grouping units with similar confounding factors is essential to overcome the potential endogeneity problem if we use geographical detector in crime geography as well as other sub-fields of human geography.

It has been found that the type of community housing has an important impact on the spatial pattern of burglary in urban areas. However, few scholars have explored the difference of the impact of different housing types in different degrees of population mobility on burglary. This study takes ZG city, a coastal city in southeast China, as a research area. It is based on theories of routine activity theory, crime pattern theory, rational choice theory and social disorganization theory. This paper, taking community as the unit of analysis, adopts data of burglary, the sixth national census and Point of Interest (POI). The spatial lagged negative binomial regression method is used to analyze the impact of the interaction between community population mobility and housing types on the spatial pattern of burglary. Among them, the population mobility factors were extracted based on the proportion of migrant population and the proportion of renting houses. The results show that population mobility has a significant positive impact on burglary rate. There is a significant positive effect of the proportion of owner-built housing on the rate of burglary, and the proportion of former public owned housing and commercial housing has a significant inhibitory effect on the burglary rate. In addition, the impact of affordable housing on burglary is not significant. The results of the interaction variables found that the interaction coefficients of population mobility with different types of housing variables are varied. Among them, the interaction of population mobility with self-built housing, affordable housing and former public housing has a significant promoting effect on burglary rate, indicating that the higher the degree of population mobility, the greater the impact of these three types of housing on burglary. Nevertheless, the interaction effect of population mobility and commercial housing is not significant. This study proves that population mobility can further mediate the effects of different types of housing on burglary, and suggests that we should pay attention to the impact of the degree of population mobility in the community where different types of housing are located when discussing the relationship between different types of housing and burglary.

The disorders of urban micro-built and social environments ("urban micro-environment", UME in short) are key factors that affect the spatial and temporal pattern and formation mechanism of theft, as well as the opportunity, cost and means of crime. To understand the spatio-temporal heterogeneity of their impact on theft is the core content of CPTED and crime geography. This paper focuses on the progress on the link between UME and theft, systematically sorts out the characteristics of UME that affect the spatio-temporal differentiation of theft, and summarizes the measurements of UME. Overall, four issues need to be addressed urgently: (1) At present, the ambient population variables calculated by using mobile phone data are mainly population size and mobility, while the micro-social environment has not been precisely depicted by population′s demographic attributes and social regularity. (2) There is a lack of systematic research on the integration of micro-social and built environment, which may lead to pseudo-correlation or irrelevance. (3) The localized empirical research of Western criminological theories is not sufficient, and the theoretical connotation and concept are often difficult to be operated locally. The local knowledge generated by Chinese empirical research is somewhat complementary and challenging to Western criminological theories, but needs to be further "conceptualized internationally". (4) Street view has been used for virtual audit of micro-built environment, but randomly selecting audit sites lacks pertinence, because it paid no heed to the spatial variation of micro-social environment. Four avenues can be proposed for future research: (1) Cooperating with the public security department, employing sensitive data to measure micro-scale population attributes and social regularity, expanding the extension of the concept of "population at risk", and accurately reflecting the micro-social environment. Conducting theoretical and policy-oriented empirical research. (2) Coupling micro-social and micro-built environment, and analyzing the inter-embedding basis and coupling path of the two micro-environments from the multidimensional theoretical levels of society, environment, and behavior. Using "big" data to depict "micro" environment, and exploring the conditional interaction mechanism and scale dependence between the UME and theft. (3) Grasping the theoretical connotation of criminology, taking into account the social context of Chinese cities, and developing new possibilities for the local operationalization of the core concept of criminological theories. (4) Developing remote, virtual, automated and intelligent built environment observation methods based on street view, and paying attention to targeted sampling and systematic integration research.

Optimizing land system is an important path to realize rural development transformation and vitalization. Based on the connotation of land system and rural development transformation, this paper systematically analyzed the research progress of land system optimization and rural development transformation and constructed the conceptual framework of land system optimization promoting rural development transformation. At last, the emphasis of current research and the direction of future research were probed systematically. Main conclusions are drawn as follows: (1) Land system is a complex system that takes land as the main object and coordinates the relationship between human, land and land right by carrying out land use and management activities within the scope of the earth′s land surface. Rural development transformation is the long-term and stable change of rural development model and paradigm, involving multiple dimensions such as factor, structure and function. Rural development transformation is the path of implementation that can bring the fundamental change of rural productivity. At present, Chinese rural territory is transforming from productive rural territory to multifunctional rural territory and even global rural territory. (2) The comprehensive research on the process, pattern, mechanism and effect of land system′s participation in rural development transformation is still insufficient. It is urgent to establish the proper scientific paradigm and methodology system, clarify and expand the analytical tools, and gradually establish the discourse system of this field. (3) Based on the mechanism analysis, level evaluation, effect and development model, future prospect simulation and optimization regulation, the research on the impact and marginal contribution of land system optimization on urban-rural integrated development, regional sustainable development and even global governance should be further expanded. (4) In the future, we need to focus on the process mechanism and regional practice of land system, the key issues of land science of realizing effective connection of consolidating and expanding the achievements of poverty alleviation and rural vitalization, the dynamic mechanism and scene simulation of rural development transformation and vitalization, and the proposition between land system, rural vitalization and modernization of agriculture and rural territory.

Land Use/Cover Change (LUCC) is a classical geographical method to study the interaction of human system and the earth system. An important basis of LUCC is the Land Use/Land Cover (LULC) classification of the earth surface in spatio-temporal dimension which could recover the interaction patterns, intensity, drivers, tendency, impacts, etc. With the technology development of earth observation and Internet connection, we are entering the era of geographic big data. The multi-scale, long time series, multi-modal and other massive "extra" coverage data greatly enrich the LULC classification and its change detection, and support the cognition and application of the interaction between the two systems of human and earth in the new era. However, most geographers believe that the basic principles and core ideas of geography have not undergone essential changes when entering the big data era. Therefore, it has become a feasible way to understand the development of LULC classification techniques from the perspective of the basic principles of geography, especially the development direction in the big data era. To this end, we describe the technology and application of LULC classification from the three geographic thoughts of regions, scaling and integration by dividing the development stage of LUCC detection into the earth observation data scarce stage, the human behavior data fusing stage, and the geographic big data "extra" coverage stage. In the earth observation data scarce stage, LULC classification uses limited remote sensing data sources to perform land cover categories at the pixel scale with low spatial resolutions; in the human behavior data fusing stage, LULC classification can realize the urban function zoning by the fusion of earth observation data and human behavior data at the block scale; and in the geographic big data "extra" coverage stage, LULC classification will realize multi-scale collaboration and functional heterogeneity division for the whole space, and integrate multi-source quantitative social-economic-natural attributes on the basis of the main spatial function, which we called "spatial scene". Thus, the spatial scene can reveal the spatio-temporal structure of the natural system and also of the human system. We hope the discussion can provide useful enlightenment for the development of new technologies and new applications for LULC classification in the era of geographic big data.

Transboundary water governance is an important geopolitical issue because it is associated with states′ natural resources ownership and sovereignty. Although the spatial politics of the transboundary watersheds have attracted considerable attention in Western academia, the research from domestic political geographers remains scant. To better capture the research trends and themes of transboundary hydropolitics, this study conducts qualitative systematic and bibliometrics-based literature reviews on 235 English articles from the Web of Science Core Collection and 158 Chinese articles from the CNKI database between 1990 and 2020. It shows that transboundary hydropolitics research is highly interdisciplinary. The English literature mainly covers geography, critical geopolitics and political ecology, while Chinese studies primarily draw on international relations and international law. Both English and Chinese researchers have paid the most attention to water cooperation and conflicts. Whereas such topics as "space", "territory", and "state" have gained popularity in English studies, Chinese articles are more concerned about water diplomacy and other issues of reality. Water cooperation and conflicts, critical and discursive analysis, and hydro-social relations jointly constitute three pillars of transboundary hydropolitics research. The research on the first topic evolved from a conflict-cooperation dualism to the transboundary water interaction, highlighting the power asymmetries, actions and strategies among the countries. However, this line of inquiry is subject to the "territorial trap" due to its state-centricity and statist understanding of sovereignty. Against this backdrop, critical hydropolitics and securitization theory have examined multiscalar actors′ representative, discursive, and imaginative practices, which provides a more subtle and dynamic analysis of power relations. Moreover, the realist thinking of water conflict and cooperation research has given rise to the dichotomy of nature and society, which treats water as the object of interstate competition. Drawing on a dialectical and relational ontology of water, some political ecologists and political geographers investigated the hydro-social relations via the frameworks of the waterscape, hydro-social cycle, hydro-social territories, etc. This research assists in analyzing the spatial deployment of power and the mutual construction process of power and nature. We argue that political geographers may contribute to the geopolitical analysis of the international river by engaging in the discussion of space, territory, and scale.

Profile soil moisture (PSM), which is essential for a comprehensive understanding of the entire soil layer water content, is more difficult to retrieve than surface soil moisture (SSM). It is an effective approach to estimate PSM at regional scale by combining multi-source data. Based on random forest regression (RFR), this study established SSM-deep layer soil moisture (DLSM) relationship models for different seasons with in-situ observations over China. European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product was used to estimate DLSM. Spatiotemporal variation of SM in 10 soil layers, i.e., 0-10, 0-20, 0-30, 0-40, 0-50, 0-60, 0-70, 0-80, 0-90 and 0-100 cm, in China from 1980 to 2019 was analyzed in detail. ESA CCI SM product matched well with in-situ observations, but the former was generally higher than the latter. A method using saturated soil water content and wilting point for range constraining was proposed, which effectively reduced the overestimation error of ESA CCI SM product. As a whole, accuracy of RFR models was the highest in autumn, followed by summer and spring, and the lowest in winter. The models performed best in arid zone (ARZ), followed by temperate zone (TEZ) and cold zone (COZ), and worst in Qinghai-Tibet zone (QTZ). The multi-year mean and standard deviation of soil water storage of 10 soil layers were 1.64±0.11, 3.50±0.21, 5.29±0.30, 7.13±0.38, 10.04±0.46, 12.25±0.54, 14.47±0.62, 16.75±0.69, 19.05±0.76, and 21.36±0.83 cm, respectively. Soil profile was divided into fluctuating layer (0-40 cm), leap layer (40-60 cm) and stable layer (60-100 cm). Water storage of 1-m soil layer (WS-1m) over China increased from northwest to northeast and southeast, with lower PSM and greater heterogeneity in cold and arid regions and higher PSM and lower heterogeneity in warm and humid regions. WS-1m in tropical zone (TRZ), ARZ and QTZ peaked in summer, while that in TEZ and COZ was the lowest in summer. Soil profile became wetter in wet zone and wet season and drier in dry zone and dry season over the last 40 years. WS-1m in TRZ significantly increased after 2004-2009, and that in ARZ increased and decreased during 1985-1986 and 2013-2014, respectively. The main cycles of WS-1m over China were 5 a and 11 a.

Based on GIMMS NDVI 3g V1.0 data from 1982 to 2015, meteorological datasets, digital elevation model, China's vegetation zoning data and measured phenology verification data, we used seasonal vegetation phenology extraction, Theil-Sen median trend analysis and Partial Least Squares (PLS) to investigate the spatiotemporal changes of vegetation phenology in China's transitional zone between the second and third steps and to explore the response of vegetation phenology to elevation, latitude and climate change. The results shown that: (1) The spatiotemporal changes of vegetation phenology in the study area was significant during the 34 years. Temporally, vegetation phenology showed trends that the start of season (SOS) was significantly advanced, the end of season (EOS) was not significantly delayed and the length of growing season (LOS) was significantly prolonged; spatially, it was distributed by 86.24% advance for SOS pixels, 69.66% deferral for EOS pixels and 84.42% extension for LOS pixels. (2) The phenological zonality of the premontane vegetation in the transitional zone was obvious during the study period. In aspect of vertical zonality, vegetation phenology in the mid-low latitudes was influenced by the elevation gradient bounded by the 400-m contour, producing a segmented change from plains to mountains; in aspect of horizontal zonality, the vegetation phenology in low and mid-high latitudes was divided by 35°N and 43.5°N as the turning point. (3) The vegetation phenology in the transitional zone was driven by meteorological factors during the 34 years. About SOS, the temperature had the greatest impact on SOS in the middle latitude, the contribution of precipitation increased with the decrease of latitude, and the contribution of solar radiation in the middle latitude was greater than that in the low latitude; about EOS, the contribution ranking of meteorological factors to EOS in middle latitudes was solar radiation > temperature > precipitation (solar radiation made no contribution to the grassland), and the contribution order of meteorological factors in low latitudes was opposite to it. This study has academic significance for the phenological changes of different vegetation divisions in the macro-geographical zones, and also provides new understandings of the joint influence of geographical factors and climatic factors on the phenological changes.

Iran is a hot climate change study area due to the unique geographical location and fragile ecological environment. As an important source of water resources, precipitation is crucial to the ecological environment and socio-economic development in Iran. Therefore, the applicability evaluation of precipitation datasets is the basis for conducting scientific research. In this paper, we use the mean error (ME), root mean square error (RMSE), and correlation coefficient (R) to evaluate the applicability of four global gridded precipitation datasets (Global Precipitation Climatology Centre (GPCC) V2020, Climatic Research Unit (CRU) TS 4.05, Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series (UDEL) V5.01 and NOAA's Precipitation Reconstruction over Land (PREC)) by comparing them with the annual precipitation data from 103 stations in Iran from 1988 to 2017. The effect of terrain on the accuracy of different datasets is also investigated. The results show that: (1) Compared with the other three sets of gridded precipitation data, the GPCC precipitation dataset has the smallest deviation and the highest correlation with the observations (OBS), the trend and change inflection point of the time series are the closest to OBS, which is most suitable for the study of modern climate change. (2) GPCC, CRU, and UDEL precipitation datasets generally underestimate the precipitation with high values, but they can reflect the basic characteristics of precipitation. In contrast, PREC dataset cannot accurately reflect the spatial distribution mode of precipitation. Therefore, it should be cautious to use PREC data to analyze the characteristics of precipitation. (3) Altitude and slope have a certain impact on the accuracy of precipitation datasets. When the altitude exceeds 1500 m, the ME of the dataset increases and R decreases. When the slope is greater than 4°, the ME increases significantly and the R decreases significantly. The four datasets are affected by elevation and slope to a certain degree, and aspect hardly affects the accuracy of these datasets. These results can provide a scientific basis for improving the quality of the four datasets and their application in the study of climate change in Iran.

It is the key issue of current regional studies to understand how to promote regional knowledge exchange and innovation growth. With the development of the global urban innovation network, the focus of regional innovation research has begun to shift from the intra-city innovation to the inter-city technological proximity and knowledge spillovers from the network perspective. The acquisition of knowledge in a region does not only originate from local creation, but the exchange of knowledge between cities is also an important factor driving the growth of regional knowledge. This paper measures the inter-city technological proximity by using the patent data of 278 prefecture-level and above cities in China. The knowledge complexity is introduced to understand different types of inter-city technological proximity, and their differences in promoting knowledge spillovers using the city level panel data from 2007 to 2019. We divide the knowledge complexity into two dimensions, namely diversity and ubiquity, as a basis for discussing the different types of inter-city technological proximity. Our results show that (1) inter-city technological proximity is related to the diversity and ubiquity of urban knowledge structure, and the diversified, or the specialized and ubiquitous knowledge structures are easier to generate high inter-city technological proximity; (2) the types of inter-city technological proximity are influenced by the knowledge structures of cities, instead of the knowledge stock of cities. The average technological proximity between cities with diversified knowledge structures is the highest with the least internal variation; (3) knowledge spillovers based on the different types of inter-city technological proximity vary greatly, and compared to the knowledge ubiquity, the technological proximity brought by the knowledge diversity is more favorable to the inter-city knowledge spillover; and on the basis of knowledge diversity, the knowledge ubiquity will strengthen this effect. Our contributions are twofold. Firstly, we distinguish different types of inter-city technological proximity according to the city′s knowledge structure. Secondly, we construct a spatial weight matrix based on the inter-city technological proximity and reveal that different types of inter-city technological proximity can generate differentiated knowledge spillovers through the spatial econometric model. Our findings help to understand how the inter-city technological proximity is determined by the city′s knowledge structure and its differential effect on knowledge spillovers, which provide implications for the choice of innovation policies in different cities.

After Myanmar's military took over the state power in February 2021, the democratization process came to an abrupt end, which once again aroused wide attention and discussion in related academic circles. However, most of the existing studies have analyzed the causes and prospects of Myanmar's democratization process from the perspectives of political, economic, cultural and other structural factors, or from the perspectives of the interests of soldiers and the struggles among domestic and foreign actors, lacking in comprehensive analysis on the application of intersecting fields by domestic and foreign actors from the perspective of cross-scale coupling. As geo-setting research growingly reflects three characteristics, namely cross-scale coupling, multi-actor interaction and the multi-field intersection, this paper will firstly put forward an analytical framework of democratization based on the new national geo-setting perspective. Then, taking Myanmar as an example, the paper will explore the characteristics of Myanmar's geo-setting in different periods and its multi-dimensional influence on the democratization process, and forecast the trend of its democratization process in the future. The results are as follows: (1) The national geo-setting can be considered as a situation in which domestic and foreign geo-actors interact comprehensively with political, economic and other fields from the view of cross-scale coupling, thus influencing the democratization process. (2) Since the 1980s, the geo-setting of Myanmar has evolved from internal chaos and external pressure, external pressure and internal stability to external stability and internal chaos, which drove Myanmar's democratization reform through the stages of democratic initiation, transformation, consolidation and recession successively. (3) In the future, the democratization reform is most likely to be carried out through the cooperation between the elected government and the military under the military control. The analysis of the process of democratic reform in Myanmar is not only helpful for China to understand the political changes in Myanmar so as to build a harmonious and stable China-Myanmar relation, but also can promote the academic circle to further think about the issue of "what kind of democratization process should be put forward", and also promote the theoretical and applied research on the national geo-setting in the future.

The existing "B&R" studies have gradually drawn attention to the influence of historical and cultural resources on today's development. However, as the historical support and starting point of the Belt and Road Initiative, the quantitative studies related to the Silk Roads are still in their initial stage. From a civilizational perspective, how the Silk Road is understood is key to contemporary China's understanding of the global situation. Using OLS Regression, Logistic Regression and other means, we quantitatively explored the driving factors influencing the formation of the Silk Roads and Silk Roads' influence on the historical and contemporary world. Some conclusions can be drawn as follows: (1) The density distribution of the Silk Roads is generally fluctuating. The density value has increased significantly at the starting points of the transportation network represented by Rome, Chang'an, and Dayidu, and the important internal transit hubs represented by Samarkand and Tashkent. (2) The analysis of the influencing factors of the Silk Roads shows that, as a commercial trade route, the most influential factor on its route selection is geography, which mainly favors areas with low slope and high ruggedness, and this is especially evident in the complex mountainous terrain of Central Asia. (3) The opening and unobstruction of the Silk Roads played a significant role in the socio-economic, and urban development in history. The density of the Silk Roads, together with the distance from the nearest coastline, latitude, historical civilization index and other indicators, constituted the main influencing factors for the distribution of ancient cities. (4) The positive impact of the Silk Roads on regional economic development has a certain persistence, and the Silk Roads continue to play an undeniable role in supporting economic development today. For every 1% increase in road density of the Silk Roads, the night light index of the region where it is located increases by 0.373. This paper can provide differentiated theoretical perspectives and technical tools through the exploration of history, geography and economics, serve as a reference and inspiration for the development of related studies, and offer theoretical support and historical evidence for the improvement of the theory of "B&R".

This paper analyzes the (non)linear effects of tourism on carbon emissions using a dynamic panel data model based on data for 88 countries worldwide from 1995 to 2018. The paper also explores the regional heterogeneity of such effects by distinguishing between developed and developing countries. This paper further examines the moderating effects of economic growth, industrial structure, renewable energy use, and technological progress. The article significantly contributes to the existing body of knowledge in terms of variable selection, research methodology, and mechanism analysis. The main findings of this paper include: Firstly, on a global scale, tourist arrivals significantly affect carbon emissions per capita and carbon intensity. There is an inverted U- and N-shaped curve relationship between the former and the latter two. Tourism receipts significantly decrease carbon emissions per capita, and there is also an inverted U- and N-shaped curve relationship between the two. Tourism receipts also exert a significant decreasing effect on carbon intensity; however, there is a U-shaped and inverted N-curve relationship between the two. Secondly, tourist arrivals significantly positively affect carbon emissions per capita in developed countries while exert negative effects in developing countries, with the opposite effects on carbon intensity. In both developed and developing countries, tourist arrivals have inverted U-shaped and N-shaped curve effects on carbon emissions per capita. There exists an inverted U-shaped curve relationship between tourist arrivals and carbon intensity in developed countries and inverted U- and N-shaped curve relationships in developing countries. Tourism receipts have significant negative effects on carbon emissions per capita and carbon intensity in developed countries and positive effects in developing countries. U- and inverted N-shaped curve relationships exist between tourism receipts and carbon emissions per capita in developed countries and the opposite in developing countries. In contrast, tourism receipts have more similar quadratic and cubic curve effects on carbon intensity in developed countries than in developing countries. Thirdly, economic growth and industrial structure have a significant positive moderating effect on the nexus of tourist arrivals and carbon emissions per capita. Technological progress significantly reduces the marginal positive effects of tourist arrivals on carbon intensity. Economic growth, industry structure, and renewable energy use significantly mitigate the adverse effects of tourism receipts and carbon emissions per capita. The moderating effects of economic growth and industrial structure on the relationship between tourism receipts and carbon intensity are the opposite of renewable energy use and technological progress.

Land space governance is an important strategic means for developing, utilizing, protecting, and restoring China's land and resources in the new era. However, the current land space governance system has a mismatch of dominant functions on the spatial scale. It is urgent to unify spatial units of different scales to coordinate governance boundaries and improve governance efficiency. Accordingly, facing the pertinent problem orientation of the control boundary of traditional governance units, this study put forward research hypotheses such as "land space units defined by different concepts or methods have different functional orientations." Using Chengdu as an example, land-use conflicts, ecosystem barriers, and social development status are constructed to verify these assumptions on governance units such as basic administrative units, natural ecological units, and social development units. The results show that the spatial pattern characteristics of the land space governance issues in the study area are significantly different, and the contradiction between human activities scope and natural environmental restrictions is the core factor leading to regional governance issues. In spatial correlation analysis, all governance problem types show significant autocorrelation in different spatial units and pass the 0.05 significance test, but different spatial units have theoretical directional characteristics. Among them, social development units, natural ecological units, and basic administrative units are more suitable for solving the economic development power gap, ecosystem connectivity resistance, and resource management conflicts, respectively. On this basis, landscape units were used to coordinate the problem attributes of different spatial scales. The study area is divided into five types: weak development momentum type in high mountains (22.98%), governance attributes balanced type in hilly areas (11.55%), intensified management conflicts type in rural areas (44.57%), development-oriented composite type in urban-rural fringe areas (9.44%), and increased connectivity resistance in core built-up areas (11.46%). A cross-administrative integration path of multi-scale spatial units can be realized further through the region division. Summarily, it is necessary to establish an integrated spatial unit system with nested management-protection-development function, expand the power and responsibilities from government agencies to a wider range of actors through refined landscape scale, and systematically enhance land space governance efficiency.

The urban thermal environment effect seriously threatens the safety of human life and the sustainable development of social economy. Identifying the key areas of heat island regulation imbalance between supply and demand is very important to alleviate the urban thermal environment effect. Based on the climate risk assessment framework and the environmental justice framework, this paper constructs an indicator system and technical route for the evaluation of urban thermal environment regulation supply and demand. First, we select hazard sources, exposure, and vulnerability indicators to evaluate the level of urban residents' demand for heat island adjustment. Secondly, we use the heat island adjustment efficiency index to evaluate the supply capacity of green infrastructure to heat island adjustment. Finally, we apply the supply-demand matching and priority index to identify the key areas of supply-demand imbalance, and to divide the priority level of intervention. Xiamen Island is taken as an example. The results show that: (1) There is obvious spatial heterogeneity among the urban thermal environment hazards, exposure and vulnerability; the three indicators jointly determine the level of demand. The high-demand area accounting for 29.13%, it also presents the characteristics of the spatial pattern of "dispersion in the whole area and dense in the area". (2) The unevenly distributed green infrastructure space leads to the imbalance of urban thermal environment regulation and supply capacity. The high-value area includes 155 units, accounting for 13.2%, and the low-value area includes 857 units, accounting for 72.9%, and there is a spatial agglomeration opposite to the demand level of heat island regulation. (3) The supply-demand relationship of urban thermal environment adjustment services has four types: "high supply-high demand", "low supply-high demand", "low supply-low demand" and "high supply-low demand", of which 451 units are in an imbalanced state of "low supply-high demand", and they face the severe challenge of short supply. (4) A total of 84 units with high priority are mainly distributed in Malong Community, Jiangcun Community, Yuhou Community and Lujiang Community, which should be given top-level regulation. This article can provide a scientific basis for efficient site selection and targeted formulation of urban thermal environment mitigation strategies. The index system and technical route constructed are applicable to other cities.