The black soil region in Northeast China bears the great responsibility of food security of the nation. However, long-term intensive utilization and lack of soil fertility maintenance and improvement measures in region resulted in severe soil degradation, which greatly constrained the sustainable utilization of black soil resources. Conservation tillage is defined as any form of tillage that minimizes soil disturbance and at least 30% of the soil surface covered with residues to reduce soil erosion. It can promote the soil health and green farming, and then to strengthen the base of sustainable agriculture in Black soil region, which has been proved by theory and practice. This article summarizes the connotation of conservation tillage technology, its development status and technical overview in the black soil region of Northeast China. Currently, there are three major types of conservation tillage including no-tillage with residue covered, no-tillage with residue covered and wide-narrow row spacing, strip-tillage with residue covered. The ecological and economic benefits of this region from the implementation of conservation tillage were systematically evaluated, which include soil and water conservation, soil structure and soil fertility improvement, carbon sequestration, soil biodiversity increase and cost saving. Conservation tillage has the potential to prevent soil loss from wind and water erosion, increase soil organic matter, sequester carbon and reduce soil CO2 emission to mitigate the global warming; it also can improve soil structure, significantly increase soil biodiversity and functional redundancy. Conservation tillage has no significant impacts on crop yields, but under extreme weather events it has the ability to resist drought and flood for the stable or higher crop yield in Northeast China. The problems and future development directions regarding the implementation of conservation tillage in this region were discussed. It will be beneficial for black soil protection and utilization, and to promote high-quality and leap development of conservation tillage in Northeast China.
Soil Organic Matter (SOM) and Soil Total Nitrogen (STN) provide nutrients for plant growth, and they are important indexes for soil quality evaluation. In this study,the soil sample data were obtained from the cultivated land in the typical black soil area of Heilongjiang, Jilin and Liaoning provinces. The Sentinel-2A images were used as data sources to calculate spectral indices, and SOM and STN prediction models were established by Multiple Stepwise Linear Regression (MSLR) and Random Forest (RF) algorithm respectively, and the performance of the models was evaluated by 10-fold cross-validation. The spatial distribution differences of SOM and STN under different climate, soil types and terrains were compared and analyzed. Results showed that: 1) The contents of SOM and STN were the highest in Hailun demonstration area, anf low annual temperature, high elevation and annual precipitation lead to increasement of SOM, and low annual temperature and high annual precipitation lead to increasement of STN. 2) Compared with SOM and STN prediction models based on MSLR algorithm, SOM and STN prediction models based on RF have higher accuracy and stability. 3) The R2 of SOM inversion model established by RF algorithm is 0.96 and RMSE is 5.49 g/kg, while the R2 of STN inversion model is 0.95 and RMSE is 0.27 g/kg. 4) The unified establishment of SOM and STN prediction models in different demonstration areas is helpful to improve prediction accuracy and realize cross-regional modeling and mapping.
Soil in black land has good quality, high fertility and is suitable for cultivation. As a rare resource, black land is the ballast stone to ensure China’s food security. China attaches great importance to the protection and utilization of black land, which has risen to the national strategic requirements. The black land in Northeast China is one of the four major black land areas in the world, and Heilongjiang Province is one of the most important black land distribution area in China. To improve the understanding of the quality of land resources, optimize the ways and directions of resources utilization, and achieve the black land protection goals and the strategic requirements of ‘Reserving Grain in Land and Technology’, Heilongjiang Province was used as a typical study area for the provincial-level land types classification. Considering the needs of black land protection and utilization and referring to the concept of Earth Critical Zone, a three-level classification system was constructed from the five dimensions of climate, geomorphic, geological, soil, and hydrological conditions. Based on the GIS platform, the spatial overlay method was used to superimpose and synthesize the intermediate classification of dominant factors. As a result, it is divided into 39 first-level land types, 2 121 second-level land types, and 4 945 third-level land types of Heilongjiang Province. The land type units in Heilongjiang are abundant, the area distribution of the land type units is not balanced, and the properties of the low-level units are richer than those of the high-level units. The type units can reflect the natural geographical law of the region. There are three kinds of spatial composite structures: symmetric spatial composite structure, repeated spatial composite structure, and mosaic spatial composite structure. The regular distribution of quantity and structure can lay a foundation for the optimization of the agricultural production layout of black land. The spatial characteristics of the distribution of land types in Heilongjiang Province reveal the natural background of the black land, which can be used as the natural standard for the protection and restoration of the black land and improve the current status of the black land. According to the strategic demand of ‘Reserving Grain in Land and Technology’, the elastic space of cultivated land can be identified, the appropriate utilization priority can be defined, and the differential utilization and protection measures can be taken at the provincial level, and then scientific and reasonable macro adjustment and allocation of black land can be carried out. In terms of classification ideas and methods, this study draws on the previous experience of land types classification, and adopts the data matching the provincial level. The classification results are reasonable and universal to a certain extent.
Conservation tillage has become the core technology to conquer the degradation of black soil. Since soil is a home to a variety of organisms, it is very important to regard soil as a living system to evaluate the impact of conservation tillage on the health of black soil. Therefore, based on the long-term conservation tillage trial established by the Key Laboratory of Mollisols Agroecology of the Chinese Academy of Sciences, the responses of soil biodiversity and its function to conservation tillage were comprehensively elucidated in this study. Compared with conventional tillage, conservation tillage strongly improved the species richness (1%-8%), density (25%-57%), and biomass (30%-50%) of the entire soil assemblages, including microorganisms, nematodes, collembolans, mites and earthworms, as well as the connectance of soil food web (14%-32%). Furthermore, conservation tillage promotes the performance of soil biotic function in soil structure formation, soil carbon sequestration, nitrogen efficient utilization and crop yield stability. These results suggest that conservation tillage can effectively utilize the functional potential of soil organisms, which is of great significance to supporting the healthy and sustainable development of agriculture in the black soil region of Northeast China.
Digital creative industry has become a new field for the symbiosis of global economic competitiveness and cultural soft power, and it was listed as the strategic emerging industry of China in 2016. However, under the background of digital transformation of cultural production, the research on the geographical pattern of digital creative industry in the field of economic geography is still scarce in China. Based on the data of digital creative industry listed enterprises and NEEQ (National Equities Exchange and Quotations)-listed enterprises, this study explored the spatial pattern and evolution of the digital creative enterprises by using the kernel density estimation, standard deviation ellipse, Gini coefficient, then analyze the factors that influence the layout of digital creative enterprises by using the negative binomial regression model. The conclusions are as follows: First, digital creative enterprises generally present a spatial structure characteristic of “Dense East and Sparse West”, with agglomeration and expansion coexisting but focusing on agglomeration, and it always maintain the form of multi-core spatial agglomeration such as the Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta. The spatial distribution is highly uneven and the regional center of gravity has shifted significantly to the north. Second, the spatial distribution of digital creative listed enterprises is heterogeneous in different industries, and their agglomeration areas and intensities are different due to the different industrial characteristics and ownership properties. At last, the spatial differentiation of digital creative listed enterprises is influenced by agglomeration economy, infrastructure, formal institutions, cultural activity and innovation entrepreneurship, global connectivity and financial agglomeration level, and it has an obvious feature of “high-grade city preference”. Due to the difference of industrial nature and ownership, the influencing factors of enterprise site selection are also different.
Against the backdrop of new urbanization in China, the home purchase intention of floating population in the destination city is closely related to the process of citizenization. However, existing studies have paid insufficient attention to the spatial heterogeneity of floating population’s home purchase intention and its influencing factors. Based on China Migrants Dynamic Survey in 2016, this study investigates the determinants of floating population’s home purchase intention and their spatial heterogeneity using the multi-scale geographically weighted regression (MGWR). The results show that the overall willingness of China’s urban floating population to purchase a home in the city of their inflow is on the low side, especially in the southeastern coastal region where the floating population congregates, where the floating population has the lowest willingness to purchase a home. The results of the MGWR model indicate that different factors exerting significant impacts on floating population’ home purchase intention have spatial scale differences. Among them, significant variables such as hukou status, inter-provincial migration have obvious regional differences in the influence of the floating population’s home purchase intention in different regions. Specifically, marital status, hukou status and occupation at the individual level and housing price, public financial expenditure and medical resources at the city level have greater impacts on the willingness of floating population to purchase a dwelling in southeast China than other regions. The impacts of income, frequency of migration, owning a dwelling and migration with children are more significant in northeast China. The educational attainment and housing provident fund have more significant positive effects on floating population’s home purchase intention in northwest China, while the negative impact of inter-provincial migration decreases from northwest to middle central China. This study provides theoretical basis and policy recommendations for alleviating the housing problem of the floating population and advancing the process of urbanization.
Taking the lodging industry in the main urban area of Shanghai as the research object, the spatial distribution law and influencing factors of room prices are studied by drawing equal price circles through Arc GIS and GeoDa software. The results show that: 1) The price circle structure of lodging rooms in Shanghai is obvious. The price peak is formed in the Disney Resort and the Lujiazui of Nanjing East Road, and presents the characteristics of gradual gradient distribution from the center to the periphery. 2) The first level equivalent circle is distributed around the city center, sub center, first level business center, theme block, core scenic spot, university science and technology park and other circles; The second equivalent circle is mainly distributed along the urban core transportation hub, transportation trunk road and around the district administrative center; The third level equivalent circle is mainly distributed to the periphery along the boundary of the main urban area, forming a “price depression” in traditional industrial areas and logistics parks. 3) In the central urban area, Disney Resort, Hongqiao Business District, Minhang University Science and innovation belt and other typical areas, “multi center, single center, ribbon and group” high-value price areas will be formed. 4) Room price is significantly negatively correlated with the distance from enterprises to tourism attractions, transportation hubs, business centers, administrative centers, University Parks and Convention and exhibition centers. In addition, it is also affected by the comprehensive impact of internal and external factors such as enterprise scale, network score, business cycle and so on.
From the perspective of social-spatial integration, on the basis of constructing framework in across-school segregation of compulsory education, using the multi-dimensional data such as the educational resources, teaching achievements and students’ family background of middle school in Dalian in 2015, on the basis of analyzing the state of division among social groups and their spatial performance, the basic types of school and their spatial distribution characteristics are summarized, and the spatial pattern on across-school segregation in compulsory education is summarized. This study argues that there are four types of middle school within the municipal area, namely, school for children of urban integrated social groups with good academic performance; school for children of industrial workers and general technicians with general academic performance; school for children of teachers, administrators of government and enterprises and professional technical personnel with excellent academic performance; and school in rural areas with worse academic performance but where the educational resources per capita were abundant. Schools of different types are distinct within the municipal area, forming five educational circles from the inside out, namely, the urban center education circle, the urban suburban education circle, the urban new district education circle, the peripheral urban education circle and the peripheral rural education circle. Type I schools dominate the urban center education circle, Type II schools are concentrated in the middle three circles, playing a major role in the urban new district education circle, Type III schools are distributed in the inner three circles, especially the urban center education circle, and Type IV schools dominate the peripheral rural education circle. Educational resources distribute alternately of high and low among the educational circles, and teaching achievements and the socio-economic status of students’ families are gradually reduced from the center to the periphery. Different social groups and school resources shape differentiated learning outcomes through the practice of educational activities, generate multiple types of schools and corresponding spatial distribution features, and the distribution of these schools is coupled with the socio-economic characteristics of the region to form different spatial types of compulsory education across school differentiation. The segregation of compulsory education has a multi-scale, multi-dimensional dynamic performance, from individual students, classes to schools, and then to cities, regions and even countries and with differences covering students’ personal characteristics, family background and income status, school resources, achievements and abilities, physical and mental health and many other fields. Segregation is a practical process, not a static state. Therefore, on the one hand, it is not appropriate to simplify or even label segregation to form stereotypes; on the other hand, it is necessary to show the complexity of segregation through more research.
To explore the effect of the sizes of temporal basic units on period division and generation mechanism, this study takes taxi ridership and its generation mechanism in Beijing as an example, dividing a day into 6 temporal basic units from 10 minutes to 60 minutes according to the step length of 10 minutes. Hierarchical Clustering method is used to group temporal units into period on similar spatial distribution, and then Geographically Weighted Regression model is also applied to compare differences of factors for the ridership generation mechanism. The results show that when the size of temporal basic unit is below 40 minutes, the start time of going-to-work period doesn’t show the consistency with the longer. Taking all periods in a day into consideration, there are no consistency below 50 minutes. The results of generation mechanism in going-to-work period also show that the factors are the same when the temporal unit is equal or greater than 50 minutes. The results above reveal that the size of time slice will affect the results of time division and generation mechanism. Considering the consistency of the results and time using habit, the paper recommends using 60 minutes as the basic temporal unit. The method proposed in this paper on boundary consistency of time division could be used into time division in other transport models or big data researches.
Improving the platform of monitoring poverty-returning and making full use of advanced technical means to optimize the accuracy of monitoring is crucial to consolidate the existing achievements and build a solid foundation for rural revitalization. Poverty identification led by traditional socio-economic indicators depends on detailed census data. Collecting and processing census data with different qualities and quantities to research regional poverty requires a lot of expenditures, and it is difficult to monitor poverty quickly and dynamically. However, the night light data with high time-resolution and easy obtaining can to a certain extent make up for the disadvantage of statistical data and reflect the surface socio-economic phenomena in real-time. Machine learning can learn rules and patterns from these data and mine potential information to identify poor areas. Based on this, taking Shaanxi Province as an example, six supervised learning classification algorithms, such as Logical Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest Classifier (RFC), Decision Tree (DT) and Gradient Boosting Decision Tree (GBDT), are used to identify poor areas based on the rich features of nighttime light data. As a result, it shows that: 1) the multidimensional variables have about 5% higher simulation accuracy than single variables, and the accuracy can lift 1%-5% after downscaling, which can be better applied to identifying poverty-stricken regions. In addition, these variables perform similarly in feature importance, which indicate that these features are used reasonably in these algorithms. 2) All six machine learning algorithms can precisely classify poverty-stricken regions based on certain prior knowledge with an accuracy of about 80%, also have a stronger spatial consistency and regionalism. 3) The classification accuracy, F1-score, and Kappa coefficient are used to compare the characteristics between these selected algorithms, and the RFC algorithm ranks in first, the KNN, GBDT, and LR performed moderately, and the SVM and DT get poorer performance. Poverty-stricken regions act as a key region of rural revitalization, so establishing a dynamic system to instantly monitor its relative poverty level in real-time is crucial to enhance the existing poverty alleviation achievements, achieve long-term stable poverty eradication, and build a solid foundation for rural revitalization. The purpose of this paper is to find an auxiliary means to achieve the identification of poverty-stricken regions in an efficient and real-time manner, so as to provide some references for using machine learning algorithms for the dynamic monitoring of poverty-stricken regions.
In the context of rapid urbanization, this thesis takes Huangdu Village in Huaihua, Hunan as a case. Exploring the evolution process and driving mechanism of the landscape style of rural settlements and revealing the law of the multifunctional development of traditional villages are the aim based on the rural multifunctional theory. Combined with field survey data obtained through interviews and questionnaires, the research probes the evolution process of landscape styles by means of image correction and stitching by Participatory Rural Appraisal methods based on Google Earth high-definition image data. The results are as follows: 1) The theory of rural multifunctionality and the change of settlement landscape are interrelated and closely related. 2) Huangdu Village’s landscape evolution stage is divided into three stages, which consists of rural traditional functional stage, rural production functional stage and rural modernity stage. The first stage is slow and stable from 1980 to 1994. The main functions are agricultural production, living and residing and ecological conservation during this period. The second stage is the unorganized and directional from 1995 to 2009. The leading function was used for production security and commercial service during this period. The third stage is the contradiction to coordination. The main functions are cultural inheritance, commercial service and ecological conservation. 3) The settlements present obvious and multi-functional development features such as residential function, production guarantee function, ecological conservation function, commercial service function and cultural inheritance function. The residential function of space has undergone the evolution process from the closure of the four villages to the gathering、intercommunication and expansion to the outer edge. Traditional agricultural production transforms to tourism service industry in the functional space of production guarantee. Ecological conservation function space is stable. It is an important guarantee for promoting the organic renewal of the village in the optimization and expansion of commercial service function space. The cultural inheritance function demonstrates that Huangdu Village is a complete organism. The dominant and recessive landscape genes are the source of Huangdu Village’s vitality. 4) Huangdu village has gradually changed from a single agricultural production function to a multi-functional path, thus realizing the diversity of landscape. It is an external manifestation of the combination of endogenous driving forces, external driving forces and natural driving forces. It has gradually moved from a single agricultural production function to a multi-functional path. The transformation has realized the diversity of landscape style. It also made the settlement landscape of Huangdu Village evolve. Endogenous driving force refers to the elements of villager behavior, villager demand, population economic factors, traffic conditions, etc. External driving force refers to industrial structure factors, management model factors, market demand factors, policy driving factors, etc. The natural driving force is Refers to elements of natural endowment, elements of Feng Shui belief, etc. These days the tourism industry plays an important part in Huangdu Village development. It is essential to realize the sustainable development of settlements by enhancing the sense of identity of the concept of “double repair” to villagers. This thesis takes Huangdu Village, a traditional ethnic minority village as the empirical research object. The aim is to promote the sustainable development of traditional villages and protects the characteristic landscape of traditional villages by effectively revealing its evolution process, evolution characteristics and influence mechanism.
Beautiful village construction is an important measure of agricultural and rural modernization, beautiful China construction and comprehensive rural revitalization. It is of great significance to study the evolution characteristics and influencing factors of its spatial pattern for rational planning and layout of beautiful countryside. Thus, taking 140, 560 and 1216 beautiful village in 2014, 2017 and 2020 as the research object, GIS spatial analysis method is used to study the evolution characteristics of the spatial pattern of beautiful village, and geographic detectors and multi-scale geographic weighted regression are used to explore the influencing factors of the spatial pattern of beautiful village and their spatial differentiation. The results show that: 1) The spatial agglomeration of beautiful village is enhanced, and the main agglomeration areas show a trend of ‘zone-network-plane’ distribution, and the hot spots spread inward from coastal areas. 2) The spatial differentiation of beautiful village is the result of the joint action of multiple factors, but the explanatory degree of each influencing factor is significantly different, among which national intangible cultural heritage, 5A scenic spot and population density have the greatest explanatory power to the spatial distribution of beautiful village. 3) The main influencing factors have obvious spatial differences on the spatial distribution of beautiful village, and the local imbalance is significant. The positive correlation and negative correlation analysis units are blocky and banded.
This article based on the data of 1663 3A tourist attractions in the Yangtze River Delta region, the spatial differentiation characteristics and influencing factors of tourism attraction between urban and rural areas in the Yangtze River Delta region were explored by using GIS spatial analysis technology and geographic detector method. The results show that: 1) The spatial distribution of tourism attractions in the Yangtze River Delta is significantly unbalanced, showing the spatial distribution characteristics of ‘overall dispersion, core agglomeration’, the pattern of ‘single-core, multi-center, hierarchical’ is significant, and the agglomeration form shows an obvious ‘core-edge’ structure. 2) The degree of urban attraction concentration is higher than that of rural areas, and the distribution of urban and rural attractions between provinces has different emphasis. According to the scenic abundance index, 41 cities in the Yangtze River Delta can be divided into four types: ‘Urban & rural double-high type’ ‘urban agglomeration type’ ‘rural agglomeration type’ and ‘urban & rural double-low type’. 3) The urban-rural differentiation of tourism attractions in the Yangtze River Delta is mainly the result of the interaction of natural, economic and social factors, but there are significant differences in the strength of the influencing factors of the spatial pattern of urban and rural attractions. The results will provide a scientific basis for optimizing the spatial structure of tourism attractions in the Yangtze River Delta, promoting the optimal allocation of regional urban and rural tourism elements, and promoting the balanced development of tourism integration.
In order to study the spatial distribution law of urban commerce under the influence of information technology, based on the dataset of restaurants from a number of mainstream websites, this study explored the distribution differences between O2O (Online To Offline) takeaway and the traditional restaurants, and identified their driving factors. The results showed that: 1) Spatial distribution of O2O takeaway caterings is consistent with that of traditional caterings. However, the geographical distribution of O2O takeaway caterings also presents a new feature, which is typically distributed around the commercial and business centers, and the cultural and educational districts. As a result, when compared with traditional caterings, O2O takeaway caterings are more likely to be sparsely distributed. 2) In terms of customers, O2O services mainly target at the middle- and low-income consumers, and are more sensitive to the word-of-mouth reviews and recommendations from consumers. Meanwhile, the O2O caterings are most frequently rated as the medium level in the catering industry. 3) Although population density has an important impact on distribution patterns of caterings, proximity to consumer market seems to be one determining factor in location choice of O2O takeaway caterings. Meanwhile, to a certain extent, utilization of information technology has reduced the dependence of O2O takeaway caterings on the traffic infrastructure. In this regard, the location choice of O2O takeaway caterings is more flexible than traditional caterings.
Under glocalization, rural tourism development is closely tied with the interactions between globalization and localization. The crucial empirical question lies in promoting various elements advantages through rural governance to encourage sustainable rural tourism further. Taking the Bamboo Craft Village in Daoming Town, Chongzhou County, Chengdu City, as an example, this study explored the integration and response mechanics in tourism element integration. Specifically, it focuses on the process of transitioning from Lease-Operation Tourism mode (LOT) to LOT-Community-based tourism mode (CBT). Here, LOT refers to the company-led-tourism mode that motivated various actors of globalization to promote local development. CBT refers to the community-led tourism mode where it has deeper embeddedness with the local village, protects local recourses and local villagers’ rights. This research finds out that: 1) Governance modes have determined the interactions among various elements. These interactions then led to new problems, which further motivated the transformation of tourism governance mode. The developmental elements’ interactions and the change of governance modes revealed a cyclical action path. 2) Different sectors have different utilizing and integrating modes of various elements, leading to differentiated benefit gains from tourism. In LOT mode, compared to the tourism company, villagers have a relatively weak resource integration ability and have a relatively low benefit gain. Hence, their passion for tourism participation also reduced. In CBT mode, villagers could improve that resource integration ability with the help of social workers. They could set up village companies to integrate tourism resources, improve the whole community’s ability to benefit from tourism. 3) Bamboo Craft Village has formed a nested-three-layer developmental mode with different tourism governance modes, including layers of the Bamboo Craft Village, village company and village household. Under the LOT mode, companies from outside would utilize elements of globalization to integrate resources and promote localized and individualized tourism. This stage shaped two layers composed of Bamboo Craft Village and villagers. Meanwhile, villagers are marginalized in this process. With the development of CBT, village companies could interrogate individualized elements and promote localized industries. Here, village companies become the middle layer between households and Bamboo Craft Village. 4) The two modes have combined their advantages through integrated development. The integration of CBT to LOT is closely tied with social workers’ support and coordination. Social workers have motivated villagers by improving their ability to integrate elements and tourism resources to benefit. Villagers have shaped their knowledge and sense to integrate resources to enable Bamboo Craft Village to integrate with village companies and village households. In so doing, it could combine each modes’ advantages. This study has two significant contributions. First, it clarified the community governance’s impact on rural tourism through a lens of developmental elements. Second, it summarized the nested-three-layer mode influenced by tourism governance. This article hopes to provide suggestions and theoretical insights to similar tourism sites.
COVID-19 has caused heavy losses to the tourism industry and the hotel industry. However, it is different that the ability of tourism cities’ hotels to cope with and adapt to the epidemic, that is, their resilience is different. Taking star-rated hotels of 41 tourism cities in China as an example, this paper constructs a resilience evaluation model based on their cumulative loss. Using SARIMA Model and Random Forest Model, this paper analyzes the spatio-temporal differentiation and factors of star-rated hotels’ resilience of tourism cities in 2020 under the impact of COVID-19. The results show that: 1) With the gradual improvement of the epidemic prevention and control in China, star-rated hotels’ resilience of tourism cities continues to increase, but the evolution of their resilience is different. 2) From a spatial point of view, it is different that star-rated hotels’ resilience of tourism cities. The resilience’s spatial differentiation shows the traffic corridor effect and the geographical proximity effect. 3) There are six important factors affecting star-rated hotels’ resilience of tourism cities, which are the growth rate of average rental rate, the ratio of catering to room income, the urban parks and green spaces per capita, the growth rate of domestic tourism income, the rate of excellent air quality, and the disposable income of urban residents per capita, and which have complex and nonlinear effects on the resilience. This paper is beneficial to star-rated hotels’ resilience of tourism cities under the impact of COVID-19.
With the MODIS surface temperature data products, the probabilistic threshold algorithm is introduced to improve the spatial recognition accuracy of urban heat island patches. On this basis, the urban heat island expansion index is constructed to decompose the spatio-temporal change process of urban heat island patches into leapfrogging, edge-expanding, infilling expansion model and reduced model. Based on the land use change process, the path analysis of the spatial expansion pattern of urban heat island plaque is carried out, and the source and trend of the spatial expansion path of urban heat island plaque are accurately identified. The results show that the total area of urban heat island patches in Beijing in summer day and night in 2020 was 3932 km2 and 2266 km2, accounting for 23.96% and 13.81% of the total area of Beijing. From the summer of 2005 to 2020, the proportion of urban heat island patches area had a 43.40% and 24.44% growth in the daytime and nighttime, respectively. The area of new heat urban island patches is larger than that of reduced patches. The edge-expanding model is the most important model for the new urban heat island patches. Cropland, urban land, and rural settlement area are the main spatial expansion paths of new urban heat island patches. The research results provide theoretical basis and data support for revealing the formation process and refined management of urban thermal environment.
To improve the understanding the water cycle of subtropical monsoon region, stable isotopes in precipitation were monitored in the Hukou region. The precipitating moisture sources were identified in this region using the HYSPLIT model, PSCF, and CWT methods. Results showed that isotopic composition in precipitation was obviously depleted in summer and enriched in spring and winter. The slope (8.19) and intercept (12.5) of the meteoric water line in Hukou region were higher than those of the global meteoric water line, which suggested the climate environment in the study area was relatively humid. The variations of precipitation isotopes had significant precipitation effect, humidity effect, and anti-temperature effect. The moisture sources in the study region were mainly from the southeast coastal inland areas, China South Sea, and Bay of Bengal, resulting in the lower isotopic values in summer and autumn. Moreover, stable isotopic compositions in precipitation were influenced by frontal weather systems such as quasi-stationary front and cold front and typhoon. The water vapor that formed typhoon precipitation mainly came from the South China Sea and the East China Sea. During the process of water vapor transportation to the inland, the precipitation isotopes were continuously washed away, and the isotopic values decreased gradually. Under the influence of the quasi-static front, precipitation isotopic value was the minimum, which may be caused by the strong convection between the cold and warm air masses in the front system. In addition, the δ18O and d-excess of the precipitation influenced by the cold front system were relatively higher in the Hukou area, which may be related to the local water vapor replenishment from the inland regions.
