Spatial distribution characteristics and analysis of influencing factors on different manufacturing types in Shandong Province
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ABSTRACT:
SUBMITTER: Zhang Y
PROVIDER: S-EPMC10511096 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Optimizing the spatial layout of high-quality tourist attractions is of great significance in the sustainable development of the tourism industry. This work employs the ArcGIS spatial analysis tool to study the form, equality, and density of the spatial distribution of the 892 3A+ tourist attractions (high-quality tourist attractions hereafter) in Shandong Province, China. It also examines the factors influencing the spatial distribution of tourist attractions from the perspectives of geographic features and landscapes, culture and heritage, socioeconomic development, and transportation. We therefore find the following: 1) High-quality tourist attractions in Shandong Province have obvious clustering in spatial distribution with the high-density areas mainly concentrated in Qingdao, Jining, Jinan, Tai'an and other cities. Influenced by resource endowment and economic development, the two major geographical areas in Central Shandong and Jiaodong Peninsula have the most concentrated distribution of high-quality tourist attractions. 2) The distribution of high-quality tourist attractions shows a southwest‒northeast clustering direction; Qingdao is a high-high clustering area, and Heze is a low-high clustering area with low uniformity of spatial distribution and obvious spatial divergence. 3) Tourist attractions show an obvious "N" type high-density distribution belt and nuclear density distribution across the three existing agglomeration centers in the Jining-Tai'an intersection, Binzhou-Dongying intersection, and Qingdao Jiaozhou Bay coast. 4) Topography, climate conditions, history and culture are intrinsic factors affecting the spatial distribution of tourist attractions, while socioeconomic and transportation conditions are external requirements for the development thereof; collectively, they constrain the spatial distribution of high-quality tourist attractions.
| S-EPMC10348535 | biostudies-literature
Project description:China's food security has always been a high priority issue on the political agenda with rapid urbanization affecting agricultural land, and it is challenged by several factors, such as human activities, social politics and policy. Shandong is an important grain-producing province and the second most populous province in China. In this paper, the spatiotemporal characteristics of grain yield and their potential influencing factors were explored at the county level in Shandong by using panel data over a 19-year period. The location Gini coefficient (L-Gini) and exploratory spatial data analysis (ESDA) were used to study the spatial agglomeration characteristics of grain yield, and spatial regression methods (SRMs) were used to analyse the influencing factors. The results indicated that grain yield increased from 38.3 million metric tons to 53.2 million metric tons in 2000-2018, with a growth rate of approximately 28.0%. The increase in grain yield in Shandong was due to the driving effect of radiation from high-yield counties to surrounding moderate-yield counties. This revealed an upward trend of spatial polarization in Shandong's grain yield. In 2000-2018, the L-Gini and global Moran's I increased from 0.330 to 0.479 and from 0.369 to 0.528, respectively. The number of counties in high-high (HH) and low-low (LL) agglomeration areas increased, and the spatial polarization effect was significant. SRMs analysis showed that irrigation investment and non-grain attention have significant positive and negative effects on grain production, respectively. The spatial relationship between grain yield and its influencing factors was explored to provide a reference for formulating scientific and rational agricultural policies.
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Project description:Youth soccer specialty schools are the primary project to strengthen the foundation of soccer talents, improve the level of soccer development, and achieve the dream of Chinese soccer. Taking 32,775 soccer specialty schools in China as the research sample, ArcGIS spatial analysis technology is used to explore the spatial distribution characteristics of soccer specialty schools and their influencing factors. The analysis shows that the overall distribution of the country forms five quantity concentration area and eight high-density core areas, with a high degree of spatial concentration and significant differences between the East and West. The factors influencing soccer specialty schools include nine factors in four dimensions: historical development, geographical environment, socio-economic, and educational resources. It was found that geographic environment and socio-economy provide the foundation and background for developing educational resources. However, the direct role of educational resources is more significant in a specific educational program, such as soccer specialty schools, followed by socio-economy and geographic environment. This study comprehensively analyzes and interprets soccer specialty schools' spatial distribution characteristics and influencing factors. These results enrich the research on the spatial layout of sports, providing necessary theoretical support and practical references for the layout and high-quality development of related industries in China and other countries or regions.
| S-EPMC11480466 | biostudies-literature
Project description:The pandemic of coronavirus disease 2019 (COVID-19) has posed serious challenges. It is vitally important to further clarify the epidemiological characteristics of the COVID-19 outbreak for future study and prevention and control measures. Epidemiological characteristics and spatial-temporal analysis were performed based on COVID-19 cases from 21 January 2020 to 1 March 2020 in Shandong Province, and close contacts were traced to construct transmission chains. A total of 758 laboratory-confirmed cases were reported in Shandong. The sex ratio was 1.27: 1 (M: F) and the median age was 42 (interquartile range: 32-55). The high-risk clusters were identified in the central, eastern and southern regions of Shandong from 25 January 2020 to 10 February 2020. We rebuilt 54 transmission chains involving 209 cases, of which 52.2% were family clusters, and three widespread infection chains were elaborated, occurring in Jining, Zaozhuang and Liaocheng, respectively. The geographical and temporal disparity may alert public health agencies to implement specific measures in regions with different risk, and should attach importance on how to avoid household and community transmission.
| S-EPMC7360956 | biostudies-literature
Project description:To explore the sustainable mechanism of land use and habitat quality, the present study examined the land cover data of Shandong Province from 1980 to 2020 to understand the spatial-temporal evolution characteristics of land use. The "Integrated Valuation of Environmental Services and Trade-off" (InVEST-HQ) model and spatial auto-correlation model were further employed to evaluate the habitat quality and analyze the relationship between its spatial distribution pattern and land use type. Our results suggested that cultivated land was the dominant land use type in Shandong Province from 1980 to 2020. During this period, the area of water and URL (urban and rural industrial and mining residential land) were gradually increased, while other land types decreased progressively. Political and socio-economic factors were the dominant factors for the evolution of land use types, which exhibited significant stage variation characteristics, and the most drastic change was observed from 2010 to 2020. We further found that habitat quality in Shandong Province was dominated by moderate degradation, whose degree of degradation was positively correlated with the degree of land use development. Moreover, the average habitat quality decreased obviously over the past 40 years, and the fastest decreased period was similar to the phase change characteristics of land use types. In addition, habitat quality was significantly clustered in spatial distribution. Hot spots (high-value areas) were mainly natural ecosystems, while cold spots (low-value areas) were mainly ecosystems that were significantly affected by human activities, such as cultivated land and URL. Our findings suggest that administrators should formulate differentiation policies, solve the development dilemma of low-level habitat quality areas and build land space security pattern to promote the ecological quality.
| S-EPMC9475025 | biostudies-literature
Project description:The agglomeration and dispersion of tourist attractions in space greatly affect the development of regional tourism resources and the consumption choice of tourism market. At present, the research on the spatial distribution characteristics of tourist attractions and their influencing factors mainly adopts induction and investigation, and there is a lack of effective statistical models for the research on the spatial distribution of tourist attractions and their influencing factors in some historical and cultural ancient cities. This paper uses Internet technology to obtain the spatial distribution data of tourist attractions in Shaoxing city, and uses mean nearest neighbor analysis, nuclear density analysis, imbalance index analysis, standard deviation ellipse and other spatial statistical analysis techniques and geographical detector methods to study the spatial distribution characteristics and influencing factors of tourist attractions in Shaoxing City. This paper studied the distribution characteristics of tourist attractions in Shaoxing city, such as spatial aggregation, distribution equilibrium and spatial orientation, and applied geographical detector to study the influencing factors of the spatial distribution of scenic spots. It was concluded that the spatial distribution pattern of scenic spots was affected by various factors such as natural environment, social environment and economic environment. The explanatory power of two-factor interaction is obviously stronger than that of single factor. The research results provide scientific basis for the planning, layout and development of tourist attractions in Shaoxing and its similar cities, and then promote the high-quality development of tourism in Shaoxing and its similar historical and cultural ancient cities.
| S-EPMC11410182 | biostudies-literature
Project description:This paper examines the spatial distribution pattern and influencing factors of Martial Arts Schools (MASs) based on Baidu map data and Geographic Information System (GIS) in China. Using python to obtain the latitude and longitude data of the MASs through Baidu Map API, and with the help of ArcGIS (10.7) to coordinate information presented on the map of China. By harnessing the geographic latitude and longitude data for 492 MASs across 31 Provinces in China mainland as of May 2024, this study employs a suite of analytical tools including nearest neighbor analysis, kernel density estimation, the disequilibrium index, spatial autocorrelation, and geographically weighted regression analysis within the ArcGIS environment, to graphically delineate the spatial distribution nuances of MASs. The investigation draws upon variables such as martial arts boxings, Wushu hometowns, intangible cultural heritage boxings of Wushu, population education level, Per capita disposable income, and population density to elucidate the spatial distribution idiosyncrasies of MASs. (1) The spatial analytical endeavor unveiled a Moran's I value of 0.172, accompanied by a Z-score of 1.75 and a P-value of 0.079, signifying an uneven and clustered distribution pattern predominantly concentrated in provinces such as Shandong, Henan, Hebei, Hunan, and Sichuan. (2) The delineation of MASs exhibited a prominent high-density core centered around Shandong, flanked by secondary high-density clusters with Hunan and Sichuan at their heart. (3) Amongst the array of variables dissected to explain the spatial distribution traits, the explicative potency of 'martial arts boxings', 'Wushu hometowns', 'intangible cultural heritage boxings of Wushu', 'population education level', 'Per capita disposable income', and 'population density' exhibited a descending trajectory, whilst 'educational level of the populace' inversely correlated with the geographical dispersion of MASs. (4) The entrenched regional cultural ethos significantly impacts the spatial layout of martial arts institutions, endowing them with distinct regional characteristics.
| S-EPMC11878914 | biostudies-literature
Project description:BackgroundLittle comprehensive information on overall epidemic trend of notifiable respiratory infectious diseases is available in Shandong Province, China. This study aimed to determine the spatiotemporal distribution and epidemic characteristics of notifiable respiratory infectious diseases.MethodsTime series was firstly performed to describe the temporal distribution feature of notifiable respiratory infectious diseases during 2005-2014 in Shandong Province. GIS Natural Breaks (Jenks) was applied to divide the average annual incidence of notifiable respiratory infectious diseases into five grades. Spatial empirical Bayesian smoothed risk maps and excess risk maps were further used to investigate spatial patterns of notifiable respiratory infectious diseases. Global and local Moran's I statistics were used to measure the spatial autocorrelation. Spatial-temporal scanning was used to detect spatiotemporal clusters and identify high-risk locations.ResultsA total of 537,506 cases of notifiable respiratory infectious diseases were reported in Shandong Province during 2005-2014. The morbidity of notifiable respiratory infectious diseases had obvious seasonality with high morbidity in winter and spring. Local Moran's I analysis showed that there were 5, 23, 24, 4, 20, 8, 14, 10 and 7 high-risk counties determined for influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella, respectively. The spatial-temporal clustering analysis determined that the most likely cluster of influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella included 74, 66, 58, 56, 22, 64, 2, 75 and 56 counties, and the time frame was November 2009, March 2008, January 2007, February 2005, July 2007, December 2011, November 2009, June 2012 and May 2005, respectively.ConclusionsThere were obvious spatiotemporal clusters of notifiable respiratory infectious diseases in Shandong during 2005-2014. More attention should be paid to the epidemiological and spatiotemporal characteristics of notifiable respiratory infectious diseases to establish new strategies for its control.
| S-EPMC8403828 | biostudies-literature
Project description:Carbon emissions from energy consumption of Shandong province from 1995 to 2012 are calculated. Three zero-residual decomposition models (LMDI, MRCI and Shapley value models) are introduced for decomposing carbon emissions. Based on the results, Kendall coordination coefficient method is employed for testing their compatibility, and an optimal weighted combination decomposition model is constructed for improving the objectivity of decomposition. STIRPAT model is applied to evaluate the impact of each factor on carbon emissions. The results show that, using 1995 as the base year, the cumulative effects of population, per capita GDP, energy consumption intensity, and energy consumption structure of Shandong province in 2012 are positive, while the cumulative effect of industrial structure is negative. Per capita GDP is the largest driver of the increasing carbon emissions and has a great impact on carbon emissions; energy consumption intensity is a weak driver and has certain impact on carbon emissions; population plays a weak driving role, but it has the most significant impact on carbon emissions; energy consumption structure is a weak driver of the increasing carbon emissions and has a weak impact on carbon emissions; industrial structure has played a weak inhibitory role, and its impact on carbon emissions is great.
| S-EPMC3996966 | biostudies-other
Project description:As in other countries, short-term rentals for tourism services are growing rapidly in China's tourist cities, which are mainly operated through Airbnb. This paper explores whether the spatial distribution of Airbnb in China's rapid urbanization process exhibits characteristics, paths, and drivers that are different from those of cities in other countries. Airbnb is a model for the global sharing economy, but it is increasingly influenced by other functions and facilities in cities as it grows. In this paper, the zero-expansion negative binomial regression was used to study the factors affecting the spatial distribution of Airbnb in Nanjing, China. The results showed that the spatial distribution of Airbnb listings was correlated with the distribution of cultural attractions, universities, public transport accessibility, shopping centers, and business apartments. By analyzing the driving forces of Airbnb's development in Nanjing, this paper found that a large number of business apartments developed in cities were essential providers of Airbnb listings, and affected its spatial distribution. The gap between short-term and long-term rentals was also correlated with the distribution of Airbnb. In addition, similar to the previous literature findings, the increase in the proportion of professional hosts changes the original intention of Airbnb for sharing and communication. Our empirical results applies to the current situation of Airbnb in Chinese cities, which is conducive to the government's more intelligent management and effective promotion of the Airbnb market. Our findings also provide positive references for urban renewal policies and public participation methods in China.
| S-EPMC7971524 | biostudies-literature