Gravity Center Model Research Articles

Spatial correlation between traditional villages and religious cultural heritage in the Hehuang region, Northwest China

ABSTRACT As a typical religious cultural heritage, Tibetan Buddhist monasteries in the Hehuang region of northwest China have strong connections with surrounding villages that practice Tibetan Buddhism. This article investigates the spatial distribution correlation between the two entities using methods such as kernel density, spatial quantity relationship model, gravity center model, and qualitative description. It analyzes the relationship between Tibetan Buddhist monasteries and traditional Tibetan villages at three levels: macro, meso, and micro, exploring the spatial correlation and influence factors. The study results are as follows: Firstly, the spatial distribution of traditional villages and Tibetan Buddhist monasteries in the Hehuang region exhibits a positive correlation with a moderate spatial correlation. Secondly, the distribution of traditional villages and Tibetan Buddhist monasteries in the Hehuang region demonstrates a high spatial balance. Yet, there are instances where certain counties have an abundance of monasteries but lack traditional villages, particularly in Minhe County, Guide County, Hualong County, and Ledu County. Various factors such as economic, policy, and cultural integration contribute to this phenomenon. Thirdly, the location relationship between traditional villages and Tibetan Buddhist monasteries in the Hehuang region can be categorized into three types: Villages separated from Tibetan Buddhist monasteries, Tibetan Buddhist monasteries in villages, and Tibetan Buddhist monasteries near villages. Finally, it is proposed to protect traditional villages in the area based on the principle of protecting cultural diversity. To safeguard Chinese traditional villages in the future, it is essential to comprehensively analyze the spatial relationship between villages and religious architectural heritage, and prioritize the preservation of significant villages located within the influence zone of these religious architectural heritage by incorporating them into the list of protected traditional villages. This study aims to enhance theoretical research on traditional villages in ethnic minority regions and provide a scientific basis for the comprehensive protection and coordinated utilization of traditional villages and religious architectural heritage in the Hehuang region and other ethnic regions.

Spatiotemporal evolution and driving factors of vegetation net ecosystem productivity in Henan Province over the past 20 years

Net ecosystem productivity (NEP) is a crucial parameter for assessing the carbon cycle dynamics in terrestrial ecosystems. This study analyzed the spatial and temporal evolution characteristics and future trends of NEP in Henan Province over the past 20 years based on MOD17A3HGF, meteorological, and land-use data, employing the frequency counting method, trend test, Hurst index, and the center of gravity model. Various areas of changes in vegetation carbon sequestration were explored, and the driving factors were quantitatively assessed through correlation analysis, Sankey diagrams, and Geodetector. The results demonstrate that: 1) Continuous temporal changes in NEP in Henan, with annual average values fluctuating between 272.84 and 451.39 gC·m-2·a1, exhibiting an overall upward trend. 2) Spatially, there is a distinct distribution of NEP, concentrating more in the south and less in the north. While the study area generally experiences a dominant gradual enhancement of vegetation carbon sequestration capacity, the middle and north of Zhengzhou City exhibit a significant decline, which is expected to persist in the future. The migration of the centers of gravity of NEP over the past 20 years is characterized by stage-specific differentiation. 3) Among the various land cover types, forests have the strongest carbon sequestration capacity; however, cropland emerges as the province’s main source of NEP due to its extensive size. 4) The driving factors for spatial differentiation in NEP exhibit some temporal variability. Overall, climate factors and atmospheric pollution exert stronger influences, with the interactive explanatory power of the two-factor interaction being higher than that of the single factor. The results of this study can serve as a scientific theoretical basis for ecological policy-making and sustainable development in Henan Province.

Analysis of Land Use Gravity Center Change and Carbon Emission Impact in Chengdu Plain of China from 2006 to 2022

As the economic center and major grain-producing area in Southwest China, the calculation of the carbon budget and the protection of cultivated land in the Chengdu Plain are of vital significance for China to achieve a carbon peak strategy and ensure food security. For the purpose of clarifying the trend of land use focus and carbon emissions in the Chengdu Plain, the carbon peak level of land use in 33 counties in the Chengdu Plain was explored. Based on the gravity center model and IPCC carbon emission coefficient method, the changing trend of land use gravity center and carbon emission in Chengdu Plain from 2006 to 2022 was clarified. PLS regression model and LMDI model were used to explore the main influencing factors of the carbon emission of cropland and the carbon emission of building land. PLUS model was used to simulate future land use patterns and carbon emissions. (1) The center of gravity of cropland, building land, water, and other and unused land shifted to the northeast by 4.23 km, 5.46 km, 8.44 km, and 31.58 km, respectively, and that of forest and grass shifted to the southeast by 11.12 km and 3.41 km, respectively. For major food crops, the centers of gravity of rice and maize moved northeastward by 15.47 km and 7.52 km, respectively, while wheat moved southwestward by 17.77 km. (2) From 2006 to 2022, carbon emissions from land use in the 33 counties of the Chengdu Plain are all on the rise, with a total increase of 13.552 million tons, and carbon sinks in the 31 counties continue to decline, with a total decrease of 0.691 million tons. (3) Under the natural scenario, carbon sink scenario, and carbon reduction scenario, the carbon emissions from land use decrease by 0.5391 million tons, 3.4728 million tons, and 4.5265 million tons from 2022, respectively. Among the 33 counties in the Chengdu Plain, 11 counties did not achieve carbon peak under the natural scenario, 5 counties did not achieve carbon peak under the carbon sink scenario, and all the counties achieved carbon peak under the carbon sink scenario. During the study period, there was a serious loss of cropland in the Chengdu Plain, mainly to building land in the central part of the Chengdu Plain and to forests within the Longmen Mountain, Longquan Mountain, and Leshan City, and there is a need to strengthen cropland protection in this region in the future. Under the natural scenario, carbon sink scenario, and carbon reduction scenario, land use in the Chengdu Plain region can achieve carbon peak, and the carbon reduction model will be more helpful for the counties to achieve carbon peak.

Exploring new methods for assessing landscape ecological risk in key basin

Scientific assessment of landscape ecological risk (LER) aims to optimize land use patterns and mitigate regional ecological hazards. However, accurate LER assessment requires the selection of a feasible spatial analysis scale. This study identified the optimal spatial scale by analyzing high-resolution data from 2006, 2012, and 2019. Within the “production-living-ecological” spatial (PLES) perspective, this study employed six methods to depict the pattern changes and spatiotemporal variations of LER. These included the Markov transfer matrix model, the geoscience information atlas–gravity center model (GIAGC), the LER index model, Min/Max Autocorrelation Factors, the Sequential Gaan simulation (MAF-SGS) multivariate geostatistical model, and spatial autocorrelation. The results are as follows: 1) A granularity of 10 m and a magnitude of 200 m are the most effective parameters for LER assessment. 2) From 2006 to 2019, there was a shift in the structure of the landscape pattern from “ecological space” to “productive space”, accompanied by a tendency for the center of gravity to shift towards the southwest. 3) The non-structural spatial factors contributing to LER are gradually increasing, and the maximum variability is steadily rising. Medium-low risk areas dominate the basin, and the spatial distribution of LER exhibits an overall pattern: high in the center, low in the southwest, and low in the northwest. Specifically, a low-low spatial clustering pattern is predominant; however, there is a general upward trend in LER. In summary, this study provides a scientific basis for adjusting basin land use structures, resolving ecological risks, and promoting high-quality sustainable development.

Rural Industrial Integration and New Urbanization in China: Coupling Coordination, Spatial–Temporal Differentiation, and Driving Factors

Understanding the coupling coordination status between rural industrial integration (RII) and new urbanization (NU) is critical for the Chinese government to optimize policies that promote the synergetic and sustainable development of RII and NU. Based on constructing evaluation index systems, this paper uses the entropy value method, coupling coordination degree model, exploratory spatial analysis method, gravity center model, and geographical detector model to reveal the characteristics of the spatial–temporal differentiation of the coupling coordination and its driving factors in China. The results show that: (1) The regional differences in the coupling coordination degree between RII and NU are obvious, and the coupling coordination degree of China’s three economic regions are all in an increasing trend, but the mean values in the central and western regions are always below the national average. (2) The coupling coordination degree has significant spatial agglomeration characteristics, but the regional differences are gradually decreasing. The whole country is still dominated by the low–low agglomeration, and the provinces with the high–high agglomeration are mainly located in the eastern region. (3) The gravity center of the coupling coordination degree has moved in both the east–west and north–south directions from 2011 to 2021, but the movement trend in the north–south direction is more obvious. (4) The economic development level, industrial structure, transportation conditions, government support capacity, financial support level, and agricultural mechanization level are important factors driving the spatial–temporal variation, and their interactions will enhance the differentiation. The results can provide a theoretical basis and decision-making reference for relevant government departments in China to promote the sustainable development of RII and NU.

Exploring the destination network in the context of tourism mobility: a multi-scale analytical framework

ABSTRACT Tourist mobility has attracted considerable attention from tourism academics and industry practitioners. This study explores the destination network, which is constructed based on tourists’ digital footprint data collected from online travel diaries, by proposing a multi-scale analytical framework. In particular, to analyze the tourism destination network comprehensively, the proposed framework integrates traditional quantitative analysis (gravity center model, statistics of flow directions) and three scales of network analysis (macroscopic, mesoscopic and microscopic network metrics), to reveal the structural patterns of the underlying pattern characteristics; furthermore, by using the multiple regression quadratic assignment procedure (MRQAP), the framework also explores the formation mechanism of the destination network by measuring the correlation and causality between the destination network and the corresponding transportation network, combining other potential driving factors. Based on illustrative case study data, which contains 18, 939 travel diaries and 51, 603, 044 transportation records from Chengdu-Chongqing economic circle in China, the empirical results show that the destination network is dynamically changed during four-year period, and the transportation network has great potential in explaining the formation of destination network. The dynamic characteristics of destination network and the exploration of formation mechanism offer the opportunities for improving destination planning and management.

Study on the Coordinated Development of Tourism Industry–Regional Economy–Ecological Environment in the Yili River Valley

This study aims to clarify the relationship among the three systems of tourism industry, regional economy, and ecological environment in the Yili River Valley, which is essential for the sustainable development of the region. We explore the spatio-temporal evolution characteristics and influencing factors of the tourism–economy–ecosystem in the Yili River Valley using the center of gravity model, spatial mismatch index model, spatial variance model, and obstacle degree model, based on panel data from 2010 to 2019. The study shows that (1) the comprehensive development indices of the tourism industry, regional economy, and ecological environment in the Yili River Valley exhibit varying degrees of growth trends. Smaller increases are observed in ecological environment indices, while larger increases are found in regional economy and tourism industry indices. Both the regional economy and tourism industry indices share a strong correlation and similar development trends. (2) At the macro-regional scale, during the study period, the centers of gravity of the tourism industry, regional economy, and ecological environment in the Yili River Valley have consistently been separated from the spatial geometric center of the region. The degree of misalignment of the centers of gravity of the three systems as a whole has gradually reduced, indicating that the level of coordinated development of the region has continuously improved. (3) At the micro-regional scale, during the study period, most of the spatial misalignment indices of the Yili River Valley regions showed positive and negative fluctuations, and the types of misalignment varied to different degrees. However, the gap in spatial misalignment indices between different regions gradually narrowed, and the divergent characteristics of “east-west concentration, north-south dispersion” were gradually broken, with the overall indices showing a balanced development trend. (4) The spatial dislocation index of each region in the Yili River Valley is affected by multiple systems and factors, and the overall spatial dislocation factors are mainly the comprehensive utilization rate of general solid waste, exhaust gas emission, dust removal amount, etc., which mostly originate from the ecological environment system.

Patterns and Dominant Driving Factors of Carbon Storage Changes in the Qinghai–Tibet Plateau under Multiple Land Use Change Scenarios

Revealing the spatial–temporal evolution of carbon storage and its driving mechanisms in the Qinghai–Tibet Plateau could provide support for decision making in the protection of regional ecosystems and the achievement of regional dual-carbon goals. In this study, the spatial–temporal evolution of carbon storage in the Qinghai–Tibet Plateau was analyzed under various scenarios using PLUS-InVEST and a gravity center model, and the driving mechanisms of carbon storage were clarified with Geodetector. The results are as follows: (1) During 2000–2020, the areas of coniferous forest, evergreen broad-leaved forest, closed shrub, temperate shrub desert, multi-tree grassland, and grassland showed an increasing trend, while the areas of deciduous broad-leaved forest and mixed forest showed a decreasing trend. (2) During 2030–2060, there was a decreasing trend in the total carbon storage of the Qinghai–Tibet Plateau under three different scenarios. (3) During 2030–2060, the area of the Qinghai–Tibet Plateau was mostly represented by carbon balance (56%), while the areas of carbon sources and carbon sinks showed a scattered distribution. (4) The precipitation and topographic factors with a q value of 0.888 played a dominant role in affecting the spatio-temporal variations in carbon storage in the Qinghai–Tibet Plateau. (5) In future ecological protection and restoration efforts, more high-quality farmlands should be protected and constructed, which could contribute to the achievement of dual-carbon goals. In addition, the hydrothermal conditions should be improved to aid the carbon cycle process in the Qinghai–Tibet Plateau.

Spatiotemporal Changes and Hazard Assessment of Hydrological Drought in China Using Big Data

The intensification of the regional water cycle resulting from climate change, coupled with the influence of human activities, has brought about alterations in the frequency, scale, and intensity of droughts. In this study, based on hydrological big data and the standardized runoff drought index (SRI), the multi-scale spatiotemporal evolution of hydrological drought in China from 1948 to 2014 was analyzed using the run-length theory and gravity center model. Meanwhile, the hydrological drought hazard index was constructed to analyze the distribution of the hazard levels of drought in China. The results showed that, during 1948~2014, there was an opposite spatial distribution between the average intensity and the average coverage–duration–frequency of drought in the Yellow River Basin, Haihe River Basin and southeastern river basins. The drought situation in most river basins in China has shown an aggravating trend, among which the southeastern river basins, Haihe River Basin, Songliao River Basin and Pearl River Basin have generally shown an aggravating trend. The drought situation in China was severe in the 1950s and 1960s, gradually reduced in the 1970s, 1980s, and 1990s, and the drought situation was the mildest in the 1990s. After entering the 21st century, the drought situation began to worsen sharply. Meanwhile, from 1948 to 2014, the hazard level of drought generally presented a pattern of high in the west and north, and low in the east and south. The hazard levels of drought in the northwest and northeast were generally higher, and those in the southwest and southeast regions were generally lower. In general, the hazard levels of drought were relatively high in most areas of China.

Changes in the Vegetation NPP of Mainland China under the Combined Actions of Climatic-Socioeconomic Factors

Under the combined impact of climatic, socioeconomic, and environmental factors, the vegetation NPP change process and its responses to drive factors in the sub-regions of Mainland China are not clear. This study analyzes the changing pattern of vegetation NPP in China from 2000 to 2022 from the perspective of zoning and clarifies its response mechanism to climate-human interaction based on the gravity center model, third-order partial correlation coefficient and geographical detector. The results showed that: (1) There was an overall decreasing trend of vegetation NPP in China from the southeast to the northwest; (2) The vegetation NPP gravity center in Northeast, Northwest, and North China migrated southwards, while that of Southwest, Central South, and East China showed northward migration.;(3) Human activities played a dominant role in zones with increasing vegetation NPP from 2000 to 2010, while climate change greatly contributed to the increase in vegetation NPP during 2011–2022; (4) Human activities, such as deforestation and overgrazing, in Northeast and North China should be reduced to prevent vegetation ecosystem degradation, and the negative impact of human activities should be reduced to maintain the growth of vegetation NPP. This study was conducted to support decision-making for the precise restoration of ecosystems.

Analysis of spatial and temporal changes and driving forces of arable land in the Weibei dry plateau region in China

Arable land is the lifeblood of food production, it is of great significance to promote the protection of arable land and ensure national food security by accurately understanding the change law of cultivated land and its driving mechanism. This study takes the Weibei dry plateau region of China as an example, explores its spatial and temporal change characteristics through the center of gravity shift and land use shift matrix, and couples the geographic probe model to reveal the driving mechanisms affecting arable land change. The results show that in the past 25 years, the total arable land area in the Weibei Dry Plateau Region of China has decreased by 5.58%, and the stability of arable land resources in the whole region has weakened. The center of gravity of arable land shifts to the northeast, and the standard deviation ellipse of arable land mainly undergoes the change process of "increase (1995–2015)-decrease (2015–2020)", and the spatial distribution of arable land tends to be dispersed. In the LISA frequency mapping, the proportion of stable constant and low-frequency areas is as high as 89.58%, and the spatial pattern of cultivated land is relatively stable. Medium and high frequency areas. The transformation mode is mainly "low-low" aggregation, "low–high" aggregation is not significant, and the decline of cultivated land in the study area is more obvious. In the past 25 years, a total of 1017.26 km2 of arable land was converted to construction land. The explanatory power of the influencing factors varies in each period (0.299 to 0.731), with total agricultural machinery power has the strongest explanatory power of 0.694, 0.592, and 0.731, respectively. The interaction between slope and annual average temperature and other factors being the highest, both greater than 0.8. Through the construction of LISA frequency mapping, combined with the center of gravity model and standard deviation ellipse, the spatial evolution trend of regional arable land is more comprehensively and dynamically grasped. By using the geodetector model, the driving mechanism of the changes of arable land is revealed comprehensively, which provides a theoretical basis for the scientific management and effective protection of arable land resources and a basis for decision-making.

Spatial and Temporal Patterns of Green Energy Development in China

The development of non-conventional energy sources is not only an important guarantee for national energy security but also a key support for the realization of carbon peaking and carbon neutrality goals. However, there is limited knowledge of the spatial and temporal patterns and changing characteristics of green energy development in China. Here, based on the energy production and consumption data of the last decade, we combined the gravity center model and statistical model to assess the spatial and temporal patterns of non-conventional energy in 31 provinces of China. The research results show: (1) under the impetus of the development of green low-carbon and ecological civilization strategy, the rate of increase in the production of non-conventional energy in China and the proportion of it increase year by year, and the energy structure obviously presents the characteristics of being low-carbon and cleaner. (2) For the spatial patterns of non-conventional energy development, due to the development of wind power and photovoltaic constraints by natural resource conditions and technology, their development trend is best in northeast, north, and northwest China. (3) The generation of PV and wind power is dominated by northwest China and north China, and the generation of nuclear power is dominated by southeast China, whereas the consumption is dominated by east China and central China; there is an obvious spatial imbalance between non-conventional energy production and consumption. (4) The proportion of photovoltaics in non-conventional energy production has increased significantly over the 2010–2020 period, which is the main driver of the overall shift in the gravity center of non-conventional energy production towards the northwest region of China. (5) In recent years, the gradual transfer of industries from the east to the central and western regions of China and the improvement in the economic level of the western regions have led to an increase in energy production and consumption, promoting a shift in the gravity center of energy production and consumption to the west. Overall, the structural transformation of China’s energy production and consumption (from a high-carbon black structure to a low-carbon and carbon-free green structure) is progressing, and some provinces have achieved significant results, presenting a non-conventional energy industry in accordance with local conditions and the development trend of the non-conventional energy industry.

Spatiotemporal Pattern Evolution of Food and Nutrient Production in China.

Ensuring food and nutrient supply is a crucial aspect of achieving food safety. With rapid population growth, urbanization, and social and economic development, the challenges related to China's food and nutrient production have become increasingly prominent. This paper analyzed the characteristics of the spatiotemporal pattern evolution of food and nutrient production in China from 1995 to 2020, utilizing the conversion of various food nutrients and the establishment of a gravity center model. The results showed that: (1) Food production exhibited increasing trends in China, six regions, and 90% of the provinces. Notably, the structure of food production underwent significant changes in China, East China, Central-South China, Southwest China, Northwest China, and 60% of the provinces. (2) The output of all categories of food nutrients demonstrated increasing trends in China, six regions, and most provinces. At three different geographical scales, the changes of six food nutrients production structure showed significant differences. (3) Natural, political, social, economic, and technological factors played pivotal roles in influencing the gravity centers of food and nutrient production in China. The gravity centers of cereal production shifted northeast, while those of root and tuber, oil crops, and stimulants production moved westward. Additionally, the gravity centers of sugar crop, pulse, vegetable, fruit, and aquatic product production moved southwest and those of livestock and poultry production shifted northward. (4) Affected by the food production, the gravity centers of food energy, food protein, and food carbohydrate production shifted northward, while those of food fat, food vitamins, and food minerals production shifted northwest, southwest, and westward, respectively. The results of this study are of great significance for policy adjustments pertaining to the distribution pattern of food production, food security stability, and sustainable development in China.

A framework of Economic-Social-Natural sustainability evaluation based on multidimensional land-use ecological niche theory: Evidence in Shendong CEBs, China

Coal-electricity base cities (CEBs) are coal-based electric energy centralized and sustained production and output cities built following China’s strategic energy layout, in regions with abundant coal resources, and by the integrated coal-electricity production model. However, CEBs are mainly located in the ecologically fragile area, and coal mining activities and anthropogenic pressures caused a series of land ecological effects such as dramatic land resources change, the alleviation of land supply and demand conflict, and land damage surrounding mining area. Currently, there is not enough research on land use in CEBs, and less attention has been paid to variation ecological system response. Aiming at this problem, the research constructed a modeling framework for evaluating the spatial and temporal evolution of land use characteristics and ecological response of CEBs land use from the perspective of “Economic-Social-Natural” by adopting methods of land transfer matrix, cluster analysis, ecological niche theory, and center of gravity model. Shendong mining area was accordingly chosen as the research region to explore the multidimensional land use dynamic evolution by bringing into the evaluating framework. Therefore, the Shendong area was accordingly chosen as the research region, and land is used as the spatial carrier to explore the evaluation effect of the model framework. The result showed that grassland played a considerable role in the procedure of land transformation with the greatest utilization degree, followed by cultivated land and used land. For ecological niche, mining land and water area dominated the core economic niche, mining land, and construction land occupied the social niche, mining land controlled mostly natural niche and comprehensive niche value. In terms of ecologically integrated and comprehensive quantitative evaluation response, the production functional area, living functional area, and ecological functional area of CEBs were also quantitatively depicted and evaluated. Ecological management should focus on the downtown area of Shenmu and optimize land use patterns by increasing vegetation cover. This study combines different types of indicators to derive regional differences in ecological niches, providing an assessment method for decision makers and stakeholders to optimize land use structure and improve the ecological benefits of CEBs.

Crop Mapping and Spatio–Temporal Analysis in Valley Areas Using Object-Oriented Machine Learning Methods Combined with Feature Optimization

Timely and accurate acquisition of crop planting areas and spatial distribution are deemed essential for grasping food configurations and guiding agricultural production. Despite the increasing research on crop mapping and changes with the development of remote sensing technology, most studies have focused on large-scale regions, with limited research being conducted in fragmented and ecologically vulnerable valley areas. To this end, this study utilized Landsat ETM+/OLI images as the data source to extract additional features, including vegetation index, terrain, and texture. We employed the Random Forest Recursive Feature Elimination (RF_RFE) algorithm for feature selection and evaluated the effectiveness of three machine learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and Rotation Forest (ROF)—for crop extraction. Then, based on the optimal classifiers, the main crops in the Huangshui basin for the years of 2002, 2014, and 2022 were extracted. Finally, the transfer matrix, the gravity center model, and the Standard Deviation Ellipse (SDE) model were used to analyze the spatio—temporal changes of crops over the past 20 years in the Huangshui basin. The results showed that the spectral, vegetation index, and terrain features played a crucial role in crop extraction. Comparing the performance of the classifiers, the ROF algorithm displayed superior effectiveness in crop identification. The overall accuracy of crop extraction was above 86.97%, and the kappa coefficient was above 0.824. Notably, between 2002 and 2022, significant shifts in crop distribution within the Huangshui basin were observed. The highland barley experienced a net increase in planting area at a rate of 8.34 km2/year, while the spring wheat and oilseed rape demonstrated net decreases at rates of 16.02 km2/year and 14.28 km2/year, respectively. Furthermore, the study revealed that highland barley exhibited the most substantial movement, primarily expanding towards the southeast direction.

Spatial matching relationship between health tourism destinations and population aging in the Yangtze River Delta Urban Agglomeration

In order to address population aging and the healthy China strategy, this paper takes three provinces and one city in the Yangtze River Delta urban agglomeration as the empirical target. Firstly, using the 2010 and 2020 census data, and taking the aging coefficient and the density of the elderly population as the basic research indexes, this paper adopts the center of gravity migration model and the standard deviation ellipse to outline the spatial evolution path of the aging coefficient and the density of the elderly population. Second, using the data of recreational tourism sites in each prefecture-level city of the Yangtze River Delta urban agglomeration from 2016 to 2022, the closest neighbor index is used to judge the overall distribution characteristics of recreational tourism sites, and the judgment results are further verified with the help of Tyson polygonal analysis. Finally, based on the cross-section data of the elderly population in 2020, the spatial distribution of recreation and tourism sites and the elderly population are matched by the geographic concentration index, the center of gravity model and the matching coefficient. The results show that (1) the degree of population aging is deepening, and the characteristics of spatial Agglomeration are obvious, but the development speed among regions is inconsistent; (2) the distribution of health tourism destinations is wide and uneven between regions, showing the characteristics of ‘overall dispersion and local concentration’; (3) the spatial distribution of health tourism destinations and the elderly population shows a certain matching relationship, but the matching degree is not high. With the Yangtze River as the boundary, the distribution of health tourism destinations is ‘high in the south and low in the north’ and assumes a ladder shape from south to north, with obvious regional differences. Overall, health tourism lags behind the development process of aging.

The Spatiotemporal Variations in Soil Erosion and Its Dominant Influencing Factors in the Wenchuan Earthquake-Stricken Area

Earthquakes have obvious influences on the spatiotemporal changes in soil erosion intensity in earthquake-stricken areas. However, fewer studies have been conducted to evaluate the spatiotemporal changes in soil erosion before and after the Wenchuan earthquake and its dominant factors in different periods. In order to explore the above issue, this study quantitatively analyzed the spatiotemporal variation characteristics of soil erosion in the Wenchuan earthquake-stricken area from 2000 to 2019 based on the RUSLE model, gravity center model, and its dominant factors in different periods were determined using Geodetector. The research results indicated that: (1) The amount of mean total erosion in the Wenchuan earthquake-stricken area during 2000–2019 was 10.05 × 108 t, with an average soil erosion modulus of 2038.2 t/(km2·a), indicating mild erosion. (2) The spatiotemporal patterns of soil erosion changed greatly in the Wenchuan earthquake-stricken areas during 2000–2019. Areas with intensified soil erosion were mainly distributed in Lixian, Wenchuan, Xiaojin, and other areas near the Longmenshan fault zones. (3) Landslides, debris flows, and floods caused by the Wenchuan earthquake contributed to aggravating the soil erosion intensity in the stricken area. (4) During 2000–2019, the soil erosion intensity showed an overall decreasing trend, while the soil erosion intensity showed an increasing trend around 2008 due to the Wenchuan earthquake. (5) During 2000–2019, soil erosion in the Wenchuan earthquake-stricken area has been greatly affected by vegetation, terrain, and land use types. The research results could provide important decision-making support for soil erosion prevention and ecosystem restoration in the Wenchuan earthquake-stricken area. In addition, these results would be conducive to revealing and understanding the interactive process of “Water–Soil–Vegetation” in mountainous regions all over the world.

Will the southward center of gravity migration of population, floor area, and building energy consumption facilitate building carbon emission reduction in China?

Due to a considerable imbalance in the levels of social and economic development and urbanization in different regions of China, factors such as population, floor area, and building energy consumption have gradually undergone regional structural changes, and further show a specific center of gravity migration trend. The impact of this center of gravity migration on building carbon emissions deserves further exploration. Based on center of gravity model and comprehensive carbon emission reduction effect analysis model, this study depicts the center of gravity migration trajectory of China's population, floor area, building energy consumption, and elucidates the reduction effect of the center of gravity migration on building carbon emissions. Finally, the theoretical and essential reasons for the building carbon emission reduction effect are further discussed. The results showed that the center of gravity of China's population, floor area, building energy consumption, and building carbon emissions moved from north to south, with that for building energy consumption being most obvious (moved south by 1.22°). A total reduction of 32.7 million tCO2 in building carbon emissions was facilitated by the southward migration of the three centers of gravity. This occurred essentially because the southward migration of the center of gravity led to relatively cleaner building energy consumption across the country, which in turn weakened the overall energy consumption intensity and carbon emission factor. This study expands and deepens the theoretical mechanism of building carbon emission reduction, and provides a decision-making basis for government policymakers to balance regional differences to formulate differentiated building carbon emission reduction strategies.

Spatial-Temporal Evolution and Driving Mechanism of Urban Land Use Efficiency Based on T-DEA Model: A Case Study of Anhui Province, China

As China’s urbanization has shifted from high-speed to high-quality development, Urban Land Use Efficiency (ULUE) has become an important scale for evaluating urban connotative development. However, existing research has paid less attention to errors caused by different urban environmental factors and random disturbances in ULUE. Therefore, the purpose of this study is to eliminate the impact of environmental factors and random disturbances on ULUE measurement results by placing different cities under the same environmental conditions. First, a three-stage DEA envelopment analysis (T-DEA) model is introduced to calculate the ULUE of 16 prefecture-level cities in Anhui Province from 2001 to 2020. On this basis, the kernel density estimation model, gravity center model, and geographic detector models are used to study the spatial and temporal evolution and driving factors. The results show that (1) the ULUE increases nonlinearly with time, with an increase of 12.74%; (2) the overall peak of ULUE is on the rise, and changes from a single peak to a multi-peak, indicating that ULUE is constantly improving and that there is multi-level differentiation between different cities; (3) during the study period, the center of gravity of the ULUE value moved 22.66 km to the northwest; the overall moving distance was small, and the moving rate was slow; and (4) the influence of the interaction of double driving factors on ULUE is significantly greater than that of a single driving factor, and the factors of urban built-up area and degree of openness, as the key driving factors affecting ULUE, also have a degree of duality. In addition, to achieve efficient urban land use and to coordinate the environmental differences faced by different cities, the government must formulate systematic policies and development strategies considering the spatial characteristics of urban land use efficiency and the complexity of the driving factors.

Exploring quantification and analyzing driving force for spatial and temporal differentiation characteristics of vegetation net primary productivity in Shandong Province, China

Exploring the spatiotemporal changes of vegetation net primary productivity (NPP) and its driving mechanism is crucial for green and low-carbon development. Based on the MOD17A3HGF data, this study introduced the gravity center model, wavelet analysis, coefficient of variation, Hurst index, correlation analysis, and Thornthwaite Memorial model to explore the spatiotemporal patterns of NPP and its driving factors in Shandong Province from 2000 to 2019. The following results were attained. (1) Between 2000 and 2019, Shandong’s yearly average NPP showed an upward trend. The first main cycle of the NPP’s interannual cycle lasted 14 years. NPP was predicted to experience a short-term decline in the near future. (2) In Shandong, the NPP displayed a geographical pattern with high values in the east and low values in the west, high values in the south and low values in the north, and progressively declining values from the coast to the interior. The growth rate and increment of NPP in 2000–2019 were the largest in the northeast direction in the Southwest Plain, while those in the Jiaodong Hills, the Central and Southern Mountains, and the Northwest Plain were the largest in the northwest direction. Hurst index analysis showed that NPP would show weak anti-continuity changes in the Central and Southern Mountains and the Jiaodong Hills in the future. (3) Shandong’s NPP exhibited a “three zones and two lines” pattern of the effect of climate change and human activities. This research offers a scientific theoretical foundation for environmental protection and carbon management.