Kernel Density Estimation Analysis Research Articles

Nature-Based Solutions in “Forest–Wetland” Spatial Planning Strategies to Promote Sustainable City Development in Tianjin, China

Nature-based solutions are some of the most effective strategies to promote sustainable city development; however, existing research on NbS is mostly comprised of single variable studies rather than multiple variables. The purpose of this study was to explore the possibility of extending the NbS of a single variable to two variables for the better development of sustainable cities. Both forestation and wetland restoration are regarded as NbS for sustainable city development. The research approach of “forest–wetland” NbS was proposed and centers on the process and core issues of traditional NbS. Taking Tianjin as an example, the spatial patterns of forests and wetlands, correlation between the spatial distribution of forests and wetlands, and spatial correlation between the areas of forest growth and wetland growth within a certain distance in different years were studied using a spatial distribution pattern analysis, geographic concentration analysis, kernel density estimation and spatial autocorrelation analysis. Based on the core issues of NbS and the above spatial analysis, a “forest–wetland” spatial planning strategy was formulated. The main conclusions are as follows: forest and wetland were negatively correlated in the whole area of Tianjin, forest resources w mainly located in north, while wetland resources were mainly located in south. Compared with forests, the spatial distribution of wetlands in Tianjin was more balanced. There exist synergy and trade-offs between forest and wetland area under certain circumstances. Growth of forests was positively correlated with the growth of wetlands, within a distance of 0–400 m from 2000 to 2010, and within a distance of 0–600 m from 2010 to 2020. An increase in forest area will lead to an increase in evaporation, which in turn will hinder the growth of wetlands in Tianjin. Forest–wetland ecological network could promote synergistic between forest and wetland, and grey infrastructure to reduce potential trade-off between forest and wetland.

Use of Space by black-and-gold howler monkeys (Alouatta caraya) in an urban environment in Paraguay

AbstractAs urbanisation continues to reduce the available habitat for wildlife, some species, including the black-and-gold howler monkey (Alouatta caraya) in Pilar, southwest Paraguay, are making their homes in anthropogenic environments. Understanding an animal’s home range is an important step to understanding its ecological needs, and an essential requirement for the creation of robust conservation plans. In this study, we determined the home ranges and core areas of five groups of urban dwelling A. caraya using Minimum Convex Polygon (MCP) and Kernel Density Estimation (KDE) Analysis. We used a Spearman’s Correlation to explore the relationship between home range size and group size. All five groups had home ranges of less than 10 ha and used core areas of less than 1 ha. Group size had no significant relationship to home range size. We provide the first estimates of home range for A. caraya in an urban environment in Paraguay. Though the home ranges of the urban A. caraya in Pilar, Paraguay fall at the smaller end of the spectrum of range sizes in Alouatta, they are not abnormal for a species in this genus.

Exploring the Spatial Heterogeneity and Driving Factors of UAV Logistics Network: Case Study of Hangzhou, China

Urban logistics is an important research topic in human and economic geography; unmanned aerial vehicles (UAVs) are an emerging technology that has huge potential in the field of logistics with the release of control restrictions on low-altitude airspace. The scientific identification of the spatial pattern and impact factors of UAV logistics networks is greatly significant in regards to UAV logistics planning and scheduling. This study considered the urban logistics network of Hangzhou in 2020 as the research topic and used kernel density estimation, a geodetector, and geographic information system (GIS) spatial analysis technology to systematically analyze the spatial patterns and influencing factors at the city and district scales. The study found that a significant spatial pattern was revealed in the UAV logistics network in Hangzhou, and the logistics nodes showed an obvious “core-edge” structure. The urban population, market scale and logistics infrastructure jointly shaped the structure and function of the UAV logistics network, and logistics nodes had a strong coupling relationship with the urban spatial structure. Through interaction detectors, the technical route of urban UAV logistics network construction was analyzed and summarized, and results can provide a scientific basis and case reference for other cities to build and plan UAV logistics networks.

Spatially explicit restructuring of rural settlements: A dual-scale coupling approach

Rapid urbanization has had a profound impact on rural socioeconomic development, which has driven the spatial restructuring of rural settlements. Numerous studies have analyzed the spatial restructuring of rural settlements, yet socioeconomic factors and their impacts on villages and rural settlements have been ignored. This paper implemented a dual-scale coupling approach to identify the restructuring direction of rural settlements in Tingzu Town, Hubei Province, China. At the village scale, a population-land-industry evaluation index system was constructed to calculate the development potential of villages. The advanced gravity model was used to measure the intervillage connections, and K-means clustering was applied to divide the village groups, both approaches were used to identify the central villages. At the patch scale, kernel density estimation and accessibility analysis were applied to identify the spatial distribution characteristics of rural settlements, and rural settlements were classified into nine types based on the analysis of density-accessibility spatial combination characteristics. Four types, including relocation and evacuation, characteristic protection, suburban integration, and agglomeration and upgrading were proposed to restructure rural settlements. The restructuring direction and strategies of each type were determined by combining the influence scope of each central village, delineated by the weighted Voronoi diagram and the actual development needs of rural settlements. This study contributes to our understanding of the relationship involved in the restructuring of rural settlements and is of great practical significance for guiding the optimization of rural settlement layouts.

Planktos: An Agent-Based Modeling Framework for Small Organism Movement and Dispersal in a Fluid Environment with Immersed Structures.

Multiscale modeling of marine and aerial plankton has traditionally been difficult to address holistically due to the challenge of resolving individual locomotion dynamics while being carried with larger-scale flows. However, such problems are of paramount importance, e.g., dispersal of marine larval plankton is critical for the health of coral reefs, and aerial plankton (tiny arthropods) can be used as effective agricultural biocontrol agents. Here we introduce the open-source, agent-based modeling software Planktos targeted at 2D and 3D fluid environments in Python. Agents in this modeling framework are relatively tiny organisms in sufficiently low densities that their effect on the surrounding fluid motion can be considered negligible. This library can be used for scientific exploration and quantification of collective and emergent behavior, including interaction with immersed structures. In this paper, we detail the implementation and functionality of the library along with some illustrative examples. Functionality includes arbitrary agent behavior obeying either ordinary differential equations, stochastic differential equations, or coded movement algorithms, all under the influence of time-dependent fluid velocity fields generated by computational fluid dynamics, experiments, or analytical models in domains with static immersed mesh structures with sliding or sticky collisions. In addition, data visualization tools provide images or animations with kernel density estimation and velocity field analysis with respect to deterministic agent behavior via the finite-time Lyapunov exponent.

Comprehensive Measurement, Spatiotemporal Evolution, and Spatial Correlation Analysis of High-Quality Development in the Manufacturing Industry

Based on China’s provincial panel data from 2007 to 2017, this paper constructs a comprehensive indicator system for high-quality development of manufacturing from eight dimensions. Using the composite entropy weights method, kernel density estimation (KDE) and exploratory spatial data analysis (ESDA) to investigate its spatiotemporal evolution and spatial correlation characteristics. The results show that: (1) The high-quality development of the manufacturing industry shows a steady upward trend, but each dimension (subsystem) is quite different and can be divided into three types: growth type, flat type, and attenuation type. (2) The spatial distribution of the high-quality development of the manufacturing industry is highly consistent with the “Hu Huanyong Line”, and the overall layout is “high in the east and low in the west, high in the south and low in the north”. Seventy percent of the provinces are below the average level, with large interprovincial differences and significant spatial imbalance. (3) The high-quality development of the interprovincial manufacturing industry shows obvious spatial positive correlation. The hot spots are more active, and the spatial spillover effect is stronger—the Yangtze River Delta is the core, spreading outward in circles, and the main direction of diffusion is “from north to south”. In contrast, the cold spot area develops slowly and moves from south to north. Therefore, China should pay more attention to the “Botai Line”, which is perpendicular to the Hu Huanyong Line, and formulate differentiated development strategies to promote the coordinated development of the manufacturing industry.

Temporal-spatial pattern and driving factors of cultivated land use transition at country level in Shaanxi province, China.

The county-level Cultivated Land Use Form index (CLUF) in Shaanxi province in 2000, 2005, 2010, and 2015 was measured with the entropy method and the linear combination method. Then, the spatial differentiation characteristics and driving mechanism of CLUF were characterized and identified through exploratory spatial data analysis, standard deviation ellipse model, kernel density estimation, multiple linear, and spatial regression analysis. The conclusions drawn from empirical results were as follows. First, the CLUF presented a spatial differentiation pattern of high in the middle and low in the north and south, and the CLUF had a strong positive spatial correlation. The local spatial patterns were mainly the high-high agglomeration and low-low agglomeration. Second, the gravity center of CLUF moves from northeast to southwest, but it is always located in the central part of Shaanxi province. The CLUF showed a trend from expansion and decentralization to contraction and centralization in geographical space, with an obvious spatial spillover effect. Third, the results of nuclear density estimation showed that the difference in the CLUF between counties displayed a trend of first shrinking and then expanding. Fourth, the cultivated land use transition was promoted by the combination of the natural environment, economic growth, and urbanization development, and factors of the driving mechanism of the cultivated land use transition are complicated. Finally, policy recommendations to promote the rationalization and cultivated land use transition were put forward, such as strengthening infrastructure construction, formulating differentiated policies, and giving play to the role of neighboring demonstrations.

Motion detection in a color video sequence with an application to monitoring a baby

Personal real-time video monitoring devices are popular in recent years especially for people living in bigger houses who are taking care of babies. People take advantage of a real-time video monitoring device to monitor the babies’ activities while they are occupied by other issues. However, danger happens any time in any situations. It is necessary for a baby monitoring device to have a motion detection function to trigger recording functions or alert the guardians. This paper introduces a solution for the motion detection problem. The solution combines statistical methods, kernel density estimation and histogram analysis methods, and deep learning method for detecting the salient object. The final outputs are both the motion levels indicating the severity of the motions and the bounding boxes indicating the location of the motion happening in the video frame. The different levels of motion can later be used as triggers for different functions built into the device, such as starting video recording, playing sirens, etc., and the bounding boxes can provide reference focus areas for the guardians to check the details of the motion to decide whether to take actions or not.

Maritime Traffic Route Detection Framework Based on Statistical Density Analysis From AIS Data Using a Clustering Algorithm

Maritime traffic routes by ships navigation vary according to country and geographic characteristics, and they differ according to the characteristics of the ships. In ocean areas adjacent to coasts, regulated routes are present, e.g., traffic separation scheme for ships entering and leaving; however, most ocean areas do not have such routes. Maritime traffic route research has been conducted based on computer engineering to create routes; however, ship characteristics were not considered. Thus, this article proposes a framework to generate maritime traffic routes using statistical density analysis. Here, automatic identification system (AIS) data are used to derive quantitative traffic routes. Preprocessing is applied to the AIS data, and a similar ship trajectory pattern is decomposed into a matrix based on the Hausdorff–distance algorithm and then stored in a database. A similar pattern makes the AIS trajectory simple using the Douglas–Peucker algorithm. In addition, density-based spatial clustering of applications with noise (DBSCAN) is performed to identify the waypoints of vessels then create routes by connecting waypoints. The width of maritime routes created based on a similar ship trajectory is subjected to kernel density estimation analysis (KDE). Then, waypoints evaluation of the main route is performed from the results of KDE 75% and 90% considering the statistical in the total maritime traffic, and the results applied to the targeted ocean area are compared. Finally, the result of KDE 90% of maritime traffic with framework analyzed the safety route, which can be a basis for developing routes for maritime autonomous surface ships.

Risk factors and spatio-temporal patterns of livestock anthrax in Khuvsgul Province, Mongolia.

Anthrax is a worldwide zoonotic disease. Anthrax has long been a public health and socio-economic issue in Mongolia. Presently, there is no spatial information on carcass burial sites as a potential hazard of future anthrax outbreaks and possible risk factors associated with anthrax occurrences in Mongolia. Here, we analyze retrospective data (1986–2015) on the disposal sites of livestock carcasses to describe historical spatio-temporal patterns of livestock anthrax in Khuvsgul Province, which showed the highest anthrax incidence rate in Mongolia. From the results of spatial mean and standard deviational ellipse analyses, we found that the anthrax spatial distribution in livestock did not change over the study period, indicating a localized source of exposure. The multi-distance spatial cluster analysis showed that carcass sites distributed in the study area are clustered. Using kernel density estimation analysis on carcass sites, we identified two anthrax hotspots in low-lying areas around the south and north regions. Notably, this study disclosed a new hotspot in the northern part that emerged in the last decade of the 30-year study period. The highest proportion of cases was recorded in cattle, whose prevalence per area was highest in six districts (i.e., Murun, Chandmani-Undur, Khatgal, Ikh-Uul, Tosontsengel, and Tsagaan-Uul), suggesting that vaccination should prioritize cattle in these districts. Furthermore, size of outbreaks was influenced by the annual summer mean air temperature of Khuvsgul Province, probably by affecting the permafrost freeze-thawing activity.

Spatiotemporal heterogeneity and driving factors of PM2.5 reduction efficiency: An empirical analysis of three urban agglomerations in the Yangtze River Economic Belt, China

Understanding the spatiotemporal heterogeneities of PM2.5 reduction efficiency (PRE) and their driving factors are substantially critical for the atmospheric environmental governance. Using the balanced panel data covering 2003–2017 of the three urban agglomerations (UAs) in the Yangtze River Economic Belt (YREB), Yangtze River Delta (YRD), Middle-Reach Yangtze River (MRYR), and Cheng-Yu (CY), as the research sample, this paper quantified the PREs by non-separable input–output SBM-Undesirable model and then investigated the spatiotemporal heterogeneities through Dagum Gini Coefficient, Kernel Density Estimation and Markov Chain, as well as analyzed the driving factors of PRE using panel quantile regression. The results show that: (1) The overall PRE of the three UAs was relatively low, with an average of 0.630, the YRD showed the highest PRE (0.684), followed by the CY (0.615), while the MRYR suffered the lowest (0.588). (2) There existed significant differences in PRE among the three UAs, and the intensity of trans-variation was the main source. The Kernel Density Estimation and Markov Chain analysis showed that the gaps of PRE between cities were narrowing and gradually converged to the middle PRE level. (3) The impacts of seven selected driving factors including fixed asset investment, economic development level, investment in education, transport infrastructure, environmental regulation, information level and trade openness on PRE in the three UAs were significantly heterogenous across cities with different PRE scores. The findings of this paper are helpful to formulate differentiated policies in PM2.5 pollution reduction and promote the coordination between economic development and atmospheric environmental protection for the three UAs in YREB accordingly.

An enhanced fault detection method for centrifugal chillers using kernel density estimation based kernel entropy component analysis

In building automation system, timely detecting the operational faults in water chillers is crucial to system operation management. As a linear data transformation technique, the performance of principal component analysis (PCA) based chiller fault detection method is limited, especially for the incipient ones, due to the nonlinearities in chillers. In addition, the control limit for the monitoring statistic, such as squared prediction error (SPE), is determined under the Gaussian assumption of the score variables, which can hardly be satisfied in water chillers. Therefore, an enhanced fault detection method with the application of kernel density estimation (KDE) and kernel entropy component analysis (KECA) algorithm is reported in this paper. Cauchy-Schwarz (CS) divergence was evaluated as monitoring statistic to measure the cosine of the angle between two data sets after being projected onto a dominated subspace, and then adopted as an index for dissimilarity. KDE with its bandwidth being optimized was also applied to estimate the distribution of the CS divergence, so that the control limit for fault monitoring could be determined. The proposed KDE based KECA-CS method was validated using the experimental data from ASHRAE RP-1043, and further compared to the PCA -SPE, kernel principal component analysis (KPCA)-SPE, and KECA-SPE methods. Results showed that the best performance could be realized when using the KDE based KECA-CS method. The reported fault detection ratio was over 68% for the seven typical chiller faults even at their corresponding least severity level. The average fault detection accuracy was over 90%.

Movements and residency of Caribbean reef sharks at a remote atoll in Belize, Central America.

We investigated spatial use patterns of 77 Caribbean reef sharks (Carcharhinus perezi) at Lighthouse Reef Atoll, Belize over 7 years using residency patterns, kernel density (KD) estimation and network analysis. We found a high degree individual variation in spatial use of the atoll, but there were significant differences in residency and activity space between sexes, with females being overall more resident. Ontogenetic shifts in movement and residency were largely limited to females, as the residency index increased and activity space estimates decreased as females matured, while for males there was no relationship between space use or residency and size. KD analysis revealed many mature females were highly resident to discrete locations, and average activity space of the intermediate-sized sharks was significantly larger than that of the adults, but not the smallest sharks. Markov chain analyses indicated that the southwestern portion of the atoll was the most important movement corridor for all sharks. Both the Blue Hole and Half Moon Caye Natural Monuments provide some protection for larger Caribbean reef sharks; however, a gear ban on longlines on the southwestern forereef between Long Caye and the channel entrance to the Blue Hole would maximize the benefits for all sharks.

Spatial-temporal distribution characteristics and evolution mechanism of urban parks in Beijing, China

Urban parks are vital ecological recreational places, and their spatial evolution has a certain influence on the ecological environment and quality of citizens’ daily life. Taking Beijing as an example, this paper firstly explores the dynamic evolution of urban parks in Beijing by comparing spatial distribution characteristics in three time points of 2005, 2010, and 2017. Besides changes in number and area, the spatial structure and accessibility are examined by the methods of directional distribution, kernel density estimation and network analysis. Then three-factor analysis method is used to explain the evolution mechanism. The results reveal that there exist obvious and continuous growths in urban parks regardless of quantity, area or accessibility. According to the core-periphery spatial distribution pattern, Beijing has gradually formed a systematic green recreational network, and the service area of urban parks by walking within 30 min is 58.6 % of total area. Stability factors, dynamic factors and random factors play important roles during the spatial evolution of urban parks through restraint mechanism, supply-demand mechanism and triggering mechanism respectively. The findings offer both theoretical construct and policy recommendations for the development and sustainability of urban parks in Beijing and other rapidly urbanizing cities with high population densities.

Big Arms - The Transformation of an Indigenous Name

This article examines how personhood was shaped in the routine dispositional relations of longhouse life among the Iroquoian societies of eastern North America. Drawing on scholarship that situates the emergence of culturally-specific modes of personhood within relational networks of people and things, I present evidence that over seven centuries, a deep resonance developed between the ‘polyvalence’ of Iroquoian domestic spaces and a broadly ‘fractal’ (sensu Fowler 2004) or ‘part-in-whole’ sense of personhood in Iroquoian societies. An ethnohistoric review of seventeenth-century Ontario Iroquoian concepts of personhood is followed by an archaeological analysis of the development of longhouses between the tenth and sixteenth centuries. I report the results of a kernel density estimation (KDE) analysis of the spatial distribution of post and pit features across longhouse living floors in a diachronic study of 45 hearth areas. The results indicate that everyday practices within the longhouse came to follow several characteristic patterns by the mid-twelfth century ad. These patterns served to define ‘polyvalent’ relationships in which resident persons and nuclear families were at once identifiable as distinct social atoms and as inextricable components of larger hypostatic wholes — most especially house and lineage. A fundamental coherence was thereby established between the embodied experience of domestic taskscapes and a mode of personhood in which any social whole was understood as a dynamic and partible alliance of elements.

Evolution Characteristics of Urban Land Use Efficiency Under Environmental Constraints in China

In the context of high-quality economic development and coordinated regional development, this paper measures the urban land use efficiency of 275 prefecture-level cities in China from 2003 to 2016, taking into account the unexpected output (environmental pollution), and explores the temporal and spatial evolution of urban land use efficiency through kernel density estimation and spatial autocorrelation analysis. The results show that: (1) From 2003 to 2016, China's urban land use efficiency showed an overall fluctuating growth, but it remained at a low level. The mean value of urban land use efficiency has been gradually decreasing in east, west and central regions. (2) In the whole country and the eastern, central and western regions, the regional differences have been increasing, and the efficiency values of the whole country and the east have become polarized. (3) Urban land use efficiency shows a weak spatial positive correlation, but the degree of spatial agglomeration is increasing. High-high agglomeration areas are mostly distributed in the southeastern coastal areas, and extend into the central region, while most of the high-low polarized areas are the capital cities of the central and western regions. The low-high depressed areas are scattered around the high-value accumulation areas, some of which have turned into high-high agglomeration areas during the study period, while the low-low homogeneous areas are mainly distributed in the central, western and northeastern regions. Therefore, it is proposed that strengthening the utilization of urban stock land, strengthening the regional cooperation mechanism, and formulating policies which improve the efficiency of land use are effective ways to promote the intensive and economical use of urban land, as well as regional coordinated development.

Driving Factors and Risk Assessment of Rainstorm Waterlogging in Urban Agglomeration Areas: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area, China

Understanding the driving factors and assessing the risk of rainstorm waterlogging are crucial in the sustainable development of urban agglomerations. Few studies have focused on rainstorm waterlogging at the scale of urban agglomeration areas. We used the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China as a case study. Kernel density estimation (KDE) and spatial autocorrelation analysis were applied to study the spatial distribution characteristics of rainstorm waterlogging spots during 2013–2017. A geographical detector (GD) and geographically weighted regression (GWR) were used to discuss the driving mechanism of rainstorm waterlogging by considering eight driving factors: impervious surface ratio (ISR), mean shape index of impervious surface (Shape_MN), aggregation index of impervious surface (AI), fractional vegetation cover (FVC), elevation, slope, river density, and river distance. The risk of rainstorm waterlogging was assessed using GWR based on principal component analysis (PCA). The results show that the spatial distribution of rainstorm waterlogging in the GBA has the characteristics of multicenter clustering. Land cover characteristic factors are the most important factors influencing rainstorm waterlogging in the GBA and most of the cities within the GBA. The rainstorm waterlogging density increases when ISR, Shape_MN, and AI increase, while it decreases when FVC, elevation, slope, and river distance increase. There is no obvious change rule between rainstorm waterlogging and river density. All of the driving factors enhance the impacts on rainstorm waterlogging through their interactions. The relationships between rainstorm waterlogging and the driving factors have obvious spatial differences because of the differences in the dominant factors affecting rainstorm waterlogging in different spatial positions. Furthermore, the result of the risk assessment of rainstorm waterlogging indicates that the southwest area of Guangzhou and the central area of Shenzhen have the highest risks of rainstorm waterlogging in GBA. These results may provide references for rainstorm waterlogging mitigation through urban renewal planning in urban agglomeration areas.

Virtual Water Trade in the Service Sector: China's Inbound Tourism as a Case Study.

Research on virtual water and the water footprint is mainly focused on agriculture and industry, and less so on the service sector. The trade in products generates virtual water flow, as does the flow of people. The flow of international tourists will inevitably lead to the transfer and exchange of water resources embedded in the virtual form. This study takes China’s inbound tourism flow as the research object, from the perspective of the water footprint, in order to explore virtual water “exports” to the world. Based on kernel density estimation and ArcGIS spatial analysis, spatial-temporal evolution and structural difference were investigated. Virtual water “exports” showed an increasing trend. The kernel density estimation curves basically exhibited a “single peak” feature which indicated that virtual water “exports” from tourism were not significantly polarized in China. In terms of spatial evolution, this varied greatly at the provincial and regional level and Guangdong was always in the high value area. The south displayed greater values than the north, but this difference in provinces narrowed over the years. The water footprint of food was the largest, more specifically, the green component of this water footprint. Promoting a reasonable diet, reducing food waste, improving agricultural production technology, reducing the frequency of changing hotel supplies, and encouraging the use of new energy helped to reduce the water footprint. Virtual water trade in the service sector provides a new idea for helping to mitigate the global water crisis, in addition to virtual water flow for agricultural products.

Spatial Pattern and Development of Protected Areas in the North-south Transitional Zone of China

The north-south transitional zone in China mainly consists of the Qinling-Daba Mountains. It is the most important West-East geo-ecological space in China, containing protected areas vital for biodiversity conservation and ecological security of China. The protection and rational development of its natural habitat is of great significance to China’s ecological security and integration of protected areas based on mountain forest ecosystems on a global scale. In this study, five important types of protected areas in the transitional zone were selected, and their spatial patterns were analysed. Spatial analysis methods, such as kernel density estimation and accessibility analysis, were employed for both point and areal data, and focused on four aspects: land use scale, shift in the centre of gravity, spatial agglomeration, and accessibility. In addition, policy background and evolution of spatial and temporal characteristics of the protected area system in the transitional zone from 1963 to 2017 were also examined. We analysed the characteristics and geographical significance of the West-east corridor using the spatial pattern of the protected area system from the perspective of ecological and economic spaces. We focused on spatial shape, type intersection, and key areas to analyse the spatial overlap of the protected areas. Protected area establishment was divided into three stages: initial (1956–1980), rapid development (1981–2013), and national park transformation (2014—present). These stages reflected the change in the concept of ‘simple protection—sustainable use—integration and upgrade’ for protected areas of China. The spatial centre of gravity of the protection zone system was located in the west Qinling-Daba Mountains, and its high-density core exhibited a relatively stable N-shaped structure composed of four gathering areas. Affected by factors such as geographic environment and socio-economic development density, the average access time for protected areas was high (1.56 h); wetland parks and scenic areas are located closer to the city centre. As the West-east corridor in the transitional zone extends from west to east, there is a clear spatial dislocation between the development of protected areas and the intensity of human activities. During development, differentiated goal orientation should be adopted based on the idea of zoning and classified governance. With the advancement of the construction of protected areas, the spatial overlap of protected areas in the transition zone has become more prominent. At present, the spatially overlapped protected areas in the transitional zone remain prominent, with inclusion overlap being the most common, and forest parks exhibiting the highest probability of overlap with other protected areas, we should focus on in the integration process of the corridor-type ecological space based on the mountain forest ecosystem.

Construction of a Medical Resource Sharing Mechanism Based on Blockchain Technology: Evidence from the Medical Resource Imbalance of China.

Health equity is a very important part of social equity. The outbreak of the novel coronavirus pneumonia (COVID-19) in a short period of time exposed the problems existing in the allocation of medical resources and the response to major public health emergencies in China. By using Kernel density estimation and Data envelopment analysis (DEA), it is found that the allocation and imbalance of medical resources in China are greatly different among regions, and the polarization phenomenon is obvious. As an important part of the information technology system, blockchain technology is characterized by decentralization and non-tampering. It can realize sharing of medical resources through a mechanism of resource storage, circulation, supervision, and protection. The construction of a medical resource sharing mechanism under the condition of blockchain technology will greatly improve the degree of medical resource sharing, will narrow the differences in resource allocation between regions, and can effectively respond to an outbreak of major public health emergencies.