Gravity Center Model Research Articles

Quantitatively determine the dominant driving factors of the spatial-temporal changes of vegetation-impacts of global change and human activity

Abstract The differences in spatial-temporal distribution patterns and dominant driving factors of vegetation evolution among sub-regions during different historical periods were not clear. Therefore, this study introduced the gravity center model and geodetector to analyze the spatial-temporal change characteristics and dominant driving factors of normalized difference vegetation index (NDVI) in China during 1981–2019 from the perspective of geographic divisions. Results showed that (1) during 1981–2019, the average vegetation coverage in China showed an increasing trend and zones with obviously increasing vegetation NDVI were mainly distributed in the middle reaches of the Yellow River basin and the upper reaches of the Yangtze River. (2) During 1981–2019, the gravity center of national vegetation NDVI was mainly concentrated in Yan’an City and Tongchuan City, showing a southward migration trend as a whole, which indicates that the increment and growth rates of the southern part were greater than those of the northern part. (3) The growth of vegetation in southern China was primarily affected by the temperature, while that of northern China was largely influenced by precipitation. (4) During 1981–2019, the dominant interactive factors of vegetation change for all subregions changed greatly: natural factor (climate or terrain) ∩ other factors → landuse ∩ other factors.

The Changes of Spatiotemporal Pattern of Rocky Desertification and Its Dominant Driving Factors in Typical Karst Mountainous Areas under the Background of Global Change

There are significant differences in the dominant driving factors of rocky desertification evolution in different historical periods in southwest karst mountainous areas. However, previous studies were mostly conducted in specific periods. In this study, taking Bijie City as an example, the spatial and temporal evolution pattern of rocky desertification in Bijie City in the recent 35 years was analyzed by introducing the feature space model and the gravity center model, and then the dominant driving factors of rocky desertification in the study area in different historical periods were clarified based on GeoDetector. The results were as follows: (1) The point-to-point B (bare land index)-DI (dryness index) feature space model has high applicability for rocky desertification monitoring, and its inversion accuracy was 91.3%. (2) During the past 35 years, the rocky desertification in Bijie belonged to the moderate rocky desertification on the whole, and zones of intensive and severe rocky desertification were mainly distributed in the Weining Yi, Hui, and Miao Autonomous Region. (3) During 1985–2020, the rocky desertification in Bijie City showed an overall weakening trend (‘weakening–aggravating–weakening’). (4) From 1985 to 2020, the gravity center of rocky desertification in Bijie City moved westward, indicating that the aggravating degree of rocky desertification in the western region of the study area was higher than that in the eastern region. (5) The dominant factors affecting the evolution of rocky desertification in the past 35 years shifted from natural factor (vegetation coverage) to human activity factor (population density). The research results could provide decision supports for the prevention and control of rocky desertification in Bijie City and even the southwest karst mountainous area.

Temporal and spatial evolution of drought in Haihe River Basin from 1960 to 2020

The Haihe River Basin is an important grain-producing area in China. It is of great significance to explore and grasp the temporal and spatial evolution of drought for drought prevention and disaster mitigation, water security, and food security. In this study, based on the standardized precipitation evapotranspiration index (SPEI), gravity center model, standard deviation ellipse, and other methods, we analyzed the temporal and spatial evolution of drought in Haihe River Basin from 1960 to 2020. The results showed that during 1960 ∼ 2020, the frequency of drought in the Haihe River Basin had an upward trend, and light drought and moderate drought occurred frequently. Light drought was prone to occur in winter (January, February, December), and moderate drought mainly occurred in March (The first month of spring). The frequency of severe drought and extreme drought has increased significantly since 1990, and the monthly impact is spreading. The annual drought barycenters are distributed in plain areas such as Beijing, Hebei province, and showed a northeast to southwest zonal distribution in the basin, with a general trend of moving toward southwest. The monthly drought barycenters are mainly distributed in the central part of the basin around Baoding, and their migratory direction is mainly northeast and southwest.

Research on Spatiotemporal Association between Tourism and Transportation Based on CGS Model.

Tourism and transportation generally have an inseparable association. However, there are still many limitations in the existing research on it. For example, most scholars only adopt one single model method, which fails to consider geospatial elements. Moreover, some researchers simply use socioeconomic data for analysis and research and ignore the solid spatial characteristics between tourism and transportation, which leads to deviations in the results. To solve these problems, this article proposed a spatiotemporal association model by comprehensively using coupling coordination degree, gravity center model, and spatial coincidence degree. Based on the tourism economic and attraction spatial data, and the transportation and its network spatial data, the association between tourism and transportation can be revealed by the proposed model. This study conducted a quantitative analysis on the tourism and transportation industry in Jiangxi Province, China, from 2005 to 2019, and the results show that: (1) the coupling coordination degree of tourism and transportation increases year by year; (2) the change in gravity center of tourism and transportation is subtle. The mean value of spatial overlap is 80.33 km, while the mean value of inter-annual variation consistency is 0.56; (3) the spatial coincidence degree of tourism and transportation in Jiangxi Province indicates a steady upward trend and reaches 0.78 in 2019; and (4) based on the evolution trend in the coupling coordination degree, gravity center coupling model, and spatial coincidence degree of tourism and transportation, it can be seen that the slopes of their trend functions are similar and consistent—the slopes are 0.0239, 0.0253, and 0.0319, respectively—and the standard deviation of the slopes of the three is only 0.000018.

Effects of land use/cover change (LUCC) on the spatiotemporal variability of precipitation and temperature in the Songnen Plain, China

Understanding the effects of land use/cover change (LUCC) on regional climate is critical for achieving land use system sustainability and global climate change mitigation. However, the quantitative analysis of the contribution of LUCC to the changes of climatic factors, such as precipitation & temperature (P&T), is lacking. In this study, we combined statistical methods and the gravity center model simulation to quantify the effects of long-term LUCC on P&T in the Songnen Plain (SNP) of Northeast China from 1980–2018. The results showed the spatiotemporal variability of LUCC. For example, paddy field had the largest increase (15 166.43 km2) in the SNP, followed by dry land, while wetland had the largest decrease (19 977.13 km2) due to the excessive agricultural utilization and development. Annual average precipitation decreased at a rate of –9.89 mm per decade, and the warming trends were statistically significant with an increasing rate of 0.256°C per decade in this region since 1980. The model simulation revealed that paddy field, forestland, and wetland had positive effects on precipitation, which caused their gravity centers to migrate towards the same direction accompanied by the center of precipitation gravity, while different responses were seen for building land, dry land and unused land. These results indicated that forestland had the largest influence on the increase of precipitation compared with the other land use types. The responses in promoting the temperature increase differed significantly, being the highest in building land, and the lowest in forestland. In general, the analysis of regional-scale LUCC showed a significant reduction of wetland, and the increases in building land and cropland contributed to a continuous drying and rapid warming in the SNP.

Spatial-temporal characteristics and influencing factors of food production efficiency based on WEF nexus in China

Water, energy, and food (WEF) are essential material bases for mankind's survival and development. At the same time, water and energy, as necessary inputs for food production, are of great significance to food security. Scientific understanding of the water-energy-food nexus (WEF Nexus) in food production is conducive to ensuring food security and sustainable utilization of basic resources. However, current research linking the WEF Nexus with food production is lacking. Therefore, we took the WEF Nexus as an entry point to quantify China's food production efficiency and considered the direct and indirect inputs of water and energy in food production in this paper. First, we constructed an evaluation index system of food production efficiency based on the perspective of input-output and used the stochastic frontier production function model to measure the absolute efficiency values of food production. Then, GIS spatial analysis, spatial autocorrelation analysis, and the gravity center model were used to reveal the spatial-temporal pattern, spatial autocorrelation characteristics and barycenter trajectory, respectively. Finally, the Tobit model was applied to analyze the main factors which influenced the spatial pattern changes of food production efficiency. The research results indicated that China's food production efficiency was on the rise and there were spatial differences between provinces. Per capita GDP, natural disaster losses and irrigated areas of food crops were the main factors influencing China's food production efficiency. This paper contributed a new theoretical reference to the study of food production efficiency, and provided a decision-making reference for regional resource management to ensure basic resource security and sustainable development in the future.

An analysis of the spatial evolution and influencing factors of rural settlements along the Shandong section of the Grand Canal of China

AbstractSince 1980s, the weakening of the transportation function of the Grand Canal and rapid urbanisation have generated significant changes in the spatial pattern of rural settlements along the Grand Canal. Analysing the changing characteristics of this spatial pattern, and exploring the natural, social, and economic factors influencing these changes are key to understanding the regional spatial structure and development law, and grasping the degree of influence of these factors. This study selected approximately 13,000 rural settlements in 27 county‐level units in the Shandong section of the Grand Canal, from 1980 to 2018, as the research object. The Grand Canal's distance buffer zone is divided into canal‐side, near‐canal, far‐canal, and further‐canal settlements. The correlation model with the canal is constructed through the controlled experiment. The distribution, scale, and form of the settlement are analysed quantitatively by applying the change of gravity centre model (CGC), average nearest neighbour analysis (ANN), landscape metrics (LM), and other methods. The quantitative analysis of geographic detectors in spatial pattern differentiation factors shows the relative importance and interaction within them. This study indicates that the spatial distribution shows ‘large dispersion and small concentration’ and ‘small‐scale agglomeration’ characteristics. The larger the scale of the settlement expands, the more the number of settlements decreases. The closer the settlement nears the river, the more complex the shape clusters. The total output value of agriculture, forestry, animal husbandry, fisheries, the total power of agricultural machinery, and the effective irrigation area are the main influencing factors. The grain area and the per capita disposable income of rural residents are the main auxiliary influencing factors.

Comprehensive Evaluation of Land Use Benefit in the Yellow River Basin from 1995 to 2018

Land resources are the basis of human survival and development. Land use benefit is the embodiment of land input-output ability. As an important economic zone and ecological barrier in China, it is important to calculate the land productivity in the Yellow River Basin. Using the center of gravity model and other methods, this study evaluated the land use benefit of the Yellow River Basin from 1995 to 2018 based on the selected indicators of geographic grid-scale and analyzed the regional disparity. The results revealed that the comprehensive benefits, economic benefits, and social benefits of land use were on the rise, but the ecological benefits changed in volatility. Land circulation had a great impact on the change of land use benefits. So reasonable land transfer policy should be particularly significant for land use in the Yellow River Basin. In addition, there were obvious spatial differences and agglomeration effects in land use benefit. The high values of benefits were concentrated in urban groups, which showed that areas with better economic and social development had better land use benefits. To narrow land use benefits’ spatial differences between regions, the less developed areas deserve more preferential policies to improve their economic and social levels. Besides, ecological benefits are generally not high. Thus, the land policy in the Yellow River Basin should take ecological priority as the basic principle while considering economic factors.

Changes pattern in the population and economic gravity centers since the Reform and Opening up in China: The widening gaps between the South and North

Since the Reform and Opening up, the regional development gaps have become increasingly prominent with the rapid development of China's economy and society. The gaps among the East, Center and West have been widely concerned, but the gaps between the South and North are less concerned. Under the background of the new era, the gaps between the South and North have become the prominent issues affecting the sustainable development of China's region, and reflected the evolution trend of overall pattern of land space development and utilization. This study used the regional gravity center model to analyze the changes pattern in the population and economic gravity centers, and used the geographic detector model to measure the impact of economic and social factors on population density and economic growth. Several key conclusions were reached. 1) The population gravity centers generally moved southwest, with the movement divided into three stages: moving southwest rapidly (1978–1999), moving southeast (1999–2010), moving southwest (2010–2018). 2) The economic gravity centers generally moved southwest, with the movement divided into four stages: moving northwest (1978–1991), moving southeast rapidly (1991–2003), moving northwest slightly (2003–2012), moving southwest rapidly (2012–2018). 3) The development gaps of population and economy between the South and North were becoming increasingly salient in China, and require more attention from government and academia. 4) The order of factors influencing China's population density is: urbanization > traffic convenience > external development > market prosperity > science and technology > industrialization > policy support. 5) The order of factors influencing China's economic growth is: industrialization > market prosperity > science and technology > policy support > external development > traffic convenience > urbanization.

Shade recognition of the color label based on the fuzzy clustering

In this article the task of determining the current position of pneumatic actuators is considered. The solution to the given task is achieved by using a technical vision system that allows to apply the fuzzy clustering method to determine in real time the center coordinates and the displacement position of a color label located on the mechatronic complex actuators. The objective of this work is to improve the accuracy of the moving actuator’s of mechatronic complex by improving the accuracy of the color label recognition. The intellectualization of process of the color shade recognition is based on fuzzy clustering. First, a fuzzy model is built, that allows depending on the input parameters of the color intensity for each of the RGB channels and the color tone component, to select a certain color in the image. After that, the color image is binarized and noise is suppressed. The authors used two defuzzification models during simulation a fuzzy system: one is based on the center of gravity method (CoG) and the other is based on the method of area ratio (MAR). The model is implemented based on the method of area ratio and allows to remove the dead zones that are present in the center of gravity model. The method of area ratio determines the location of the color label in the image frame. Subsequently, when the actuator is moved longitudinally, the vision system determines the location of the color label in the new frame. The color label position offset between the source and target images allows to determine the moved distance of the color label. In order to study how noise affects recognition accuracy, the following digital filters were used: median, Gaussian, matrix and binomial. Analysis of the accuracy of these filters showed that the best result was obtained when using a Gaussian filter. The estimation was based on the signal-to-noise coefficient. The mathematical models of fuzzy clustering of color label recognition were simulated in the Matlab/Simulink environment. Experimental studies of technical vision system performance with the proposed fuzzy clustering model were carried out on a pneumatic mechatronic complex that performs processing, moving and storing of details. During the experiments, a color label was placed on the cylinder, after which the cylinder moved along the guides in the longitudinal direction. During the movement, video recording and image recognition were performed. To determine the accuracy of color label recognition, the PSNR and RMSE coefficients were calculated which were equal 38.21 and 3.14, respectively. The accuracy of determining the displacement based on the developed model for recognizing color labels was equal 99.7%. The defuzzifier speed has increased to 590 ns.

Measurement of Urban Expansion and Spatial Correlation of Central Yunnan Urban Agglomeration Using Nighttime Light Data

The Central Yunnan Urban Agglomeration (CYUA) is an important zone of western development in China. The clarification of the spatial structure and changing trends in CYUA could help promote the coordinated development of the CYUA and enhance the overall competitiveness of the region. Based on data from the Yunnan Statistical Yearbook and the nighttime light data, this paper extracts the urban built-up area of the CYUA and analyzes the urban expansion and urban spatial connection intensity of the CYUA from 2000 to 2018 by using the urban gravity center model and the gravity model. The results show the following: (1) From 2000 to 2018, the urban built-up area of the CYUA expanded rapidly, and the urban built-up area increased by 369.35%, with Kunming accounting for 45.41% of the increased area. Kunming was the main contributor to the increase in the urban built-up area in the CYUA. From 2000 to 2018, the urban built-up areas of the CYUA were scattered in various mountain basins. (2) Overall, the urban gravity center of the CYUA has moved to Kunming, and the distance of the urban gravity center has increased since 2005, indicating that urban expansion has accelerated since 2005. (3) The development of the CYUA is extremely unbalanced. The urban spatial connection intensity between Kunming city, Yuxi city, and Qujing city, and Yi Autonomous Prefecture of Chuxiong is relatively strong, while the urban spatial connection intensity among cities other than Kunming is weak. Overall, the CYUA is characterized by stellar radiation with Kunming city as the core and Yuxi city as the secondary core.

Quantitatively determine the dominant driving factors of the spatial—temporal changes of vegetation NPP in the Hengduan Mountain area during 2000–2015

The Hengduan mountain area, located in the upper reaches of the Yangtze River of China, is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a whole. This paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity (NPP) from 2000 to 2015, which were determined by the use of MOD17A3 NPP products. Additionally, the dominant driving factors of the spatial—temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over 2000–2015. The results revealed that: (1) From 2000 to 2015, there was an increasing trend of vegetation NPP in the Hengduan mountain area. Throughout the whole study region, the vegetation NPP with a mean value of 611.37 gC·m−2·a−1 indicated a decreasing trend from southeast to northwest in terms of spatial distribution. (2) The gravity centers of vegetation NPP in 2000–2015 were mainly concentrated in Zhongdian County. During the study period, the gravity center of vegetation NPP moved northward, which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas. (3) The vegetation NPP showed a moderately positive correlation with temperature, accumulated temperature (>10°C), and sunshine, while there was an overall negative relationship between NPP and precipitation. (4) The dominant factors and interactive dominant factors changed in different sub-regions over different segments of the study period. The dominant factors of most sub-regions in Hengduan mountain were natural factors, and the climate change factors played an increasingly greater role over the 16 years of the study period.

Spatial–temporal evolution patterns of soil erosion in the Yellow River Basin from 1990 to 2015: impacts of natural factors and land use change

This study optimized the slope and slope length factor (LS) and crop management factor (P) of the RUSLE model and then introduced the gravity centre model to analyze the spatial–temporal variation patterns of soil erosion in Yellow River Basin from a new perspective. Results showed that: (1) The improved model of RUSLE with optimized factors of LS and P had better applicability in Yellow River Basin; (2) The average erosion intensity was 2777.5 t/a, which belonged to moderate erosion. The soil erosion intensity of the Yellow River Basin showed an overall trend of increasing firstly (1990–2005) and then decreasing (2005–2015). (3) During 1990–2015, the gravity centre of soil erosion moved to the southwest, indicating that the increment and increasing rate of soil erosion in the southwest parts of the Yellow River Basin were greater than that in the northeast parts. (4) The intensity of soil erosion aggravated with the increasing slope. The sandy soil, chestnut soil, light-grey calcium soil and fluvo aquic soil had severe erosion intensity due to the regional climate and their own physical–chemical structure. The woodland and shrubbery land were more susceptible to soil erosion.

Spatial-Temporal Characteristics in Grain Production and Its Influencing Factors in the Huang-Huai-Hai Plain from 1995 to 2018.

The Huang-Huai-Hai Plain is the major crop-producing region in China. Based on the climate and socio-economic data from 1995 to 2018, we analyzed the spatial–temporal characteristics in grain production and its influencing factors by using exploratory spatial data analysis, a gravity center model, a spatial panel data model, and a geographically weighted regression model. The results indicated the following: (1) The grain production of eastern and southern areas was higher, while that of western and northern areas was lower; (2) The grain production center in the Huang-Huai-Hai Plain shifted from the southeast to northwest in Tai’an, and was distributed stably at the border between Jining and Tai’an; (3) The global spatial autocorrelation experienced a changing process of “decline–growth–decline”, and the area of hot and cold spots was gradually reduced and stabilized, which indicated that the polarization of grain production in local areas gradually weakened and the spatial difference gradually decreased in the Huang-Huai-Hai Plain; (4) The impact of socio-economic factors has been continuously enhanced while the role of climate factors in grain production has been gradually weakened. The ratio of the effective irrigated area, the amount of fertilizer applied per unit sown area, and the average per capita annual income of rural residents were conducive to the increase in grain production in the Huang-Huai-Hai Plain; however, the effect of the annual precipitation on grain production has become weaker. More importantly, the association between the three factors and grain production was found to be spatially heterogeneous at the local geographic level.

Determining the contributions of climate change and human activities to the vegetation NPP dynamics in the Qinghai-Tibet Plateau, China, from 2000 to 2015.

Reflecting on the change in the global biodiversity pattern, the Tibetan Plateau, considered to be a "natural laboratory" for analyzing environmental change in China and around the world, has suffered profound changes in the vegetation ecosystem. This study introduces the gravity center model and geographical detectors to examine and discuss the spatial-temporal change pattern and the driving mechanism behind vegetation net primary production (NPP) in the Qinghai-Tibet Plateau from the year 2000 to 2015 while also quantitatively classifying the relative roles incorporated in the NPP change process. The study found that (1) from 2000 to 2015, the annual average NPP of the Tibetan Plateau demonstrated a declining trend from southeast to northwest. (2) The gravity center of vegetation NPP on the Qinghai-Tibet Plateau seems to have shifted eastward in the past 16 years, indicating that the level of vegetation NPP in the east depicts a greater increment and growth rate than the west. (3) In the arid regions, temperature and rainfall appear as the dominant factors for vegetation NPP, while slope and aspect parameters have constantly assumed dominancy for the same in the tropical rainforest-monsoon ecological zone in southeastern Tibet. (4) The structure of vegetation NPP exhibits an interaction between human and natural factors, which enhances the influence of single factors. (5) Considering the global ecological change and related human activities, certain differences are observed in the dominant and interaction factors for different study periods and ecological subregions in the Qinghai-Tibet Plateau. The research results could prove conclusive for vegetation ecological protection in the Qinghai-Tibet plateau.

Using Remote Sensing Data to Study the Coupling Relationship between Urbanization and Eco-Environment Change: A Case Study in the Guangdong-Hong Kong-Macao Greater Bay Area

Promoting the coordinated development of urbanization and eco-environment is essential for the development of urban agglomerations. As an emerging economic growth pole in China, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has become a research hotspot in recent years. However, relevant studies in this area have been largely constrained by the incomparability of statistical data between the inland part of the GBA and the two Special Administrative Regions (Hong Kong and Macao) of the GBA. This study used nighttime light data and the normalized difference vegetation index (NDVI) to evaluate the level of urbanization and eco-environment in the GBA, respectively. Then we adopted the gravity center model to analyze the overall coupling situation between urbanization and eco-environment change. We also adopted a coordination index to determine the spatial differentiation characteristics of this coupling in the GBA from 2000 to 2018. The results show that (1) the spatial pattern of urbanization and eco-environment both show an approximately circular structure, and the change rates of these two variables show significant spatiotemporal differentiation; (2) on the whole, urban development and eco-environment construction became more coupled in the GBA during 2000–2018, as indicated by the continuously decreasing distance between the gravity centers of urbanization and eco-environment; and (3) as for the spatial differentiation characteristic of this coupling, the GBA was generally dominated by slightly uncoupled units, while the spatial distribution of different coupling types transformed from a circular structure to a relatively random form.

Assessment of urban area dynamics in world's second largest megacity at sub-city (district) level during 1973–2016 along with regional planning

Unplanned and rapid urbanization leads to land-use heterogeneity, which is difficult to be captured in detail through city-level panoramic studies and thus warrants sub-city level assessment. The current study quantifies and assesses district-level urbanization in the world's second largest megacity, Delhi (India). The study extends on temporal scale from year 1973–2016 and utilizes urban expansion intensity, gravity centre model and landscape expansion index and regional context of planning. The findings of the present research are aligned with Master Plan of Delhi. The spatial patterns and level of urbanization is different in districts, thus, zonation of 11 districts into four categories is done for both individual and conjoint planning. The urban expansion in Delhi is observed mainly due to edge-expansion followed by outlying and infill. A tremendous increase in the number of urban clusters at outskirts is observed during year 1999–2005 and in subsequent years, expansion is observed in the area of existing urban clusters. The regions expanded by infill have shown congested and compact urban form. Over the years, urban land gravity centres of districts are found to move outwards in four directions whereas that of the city is moving in north-west direction and is expected to move in north-west or south-west in future. The more developed satellite towns are found in close proximity of the more urbanized districts of Delhi, thus indicating spatially distorted planning in Delhi national capital region (NCR). The findings are in accordance to the census data which has been used for validation. With unprecedented increasing urbanization across the world, this research has wider scope with various global cities, analysed at sub-city level to examine their spatial planning disparities and promote equitable development.

Regional differences in carbon emission of China’s industries and its decomposition effects

In order to better achieve the goal of carbon emissions, this paper combined the theory of gravity center and Logarithmic Mean Divisia Index (LMDI) model to analyze the regional emission differences in China. Researches have shown that the difference in economic development levels between the eastern and western regions is an important factor that causes the shift of the center of gravity of carbon emission and its intensity to the west. In decomposition effects, the economic output effect has the largest contribution (56%) to emissions, and the energy intensity effect has the best effect in suppressing emissions. Except for some industries in the East and Central South of China, energy structure in other regions is still dominated by high-carbon energy. In the energy intensity effect, the suppression effects in the East and Central South of China have reached −83,440 Mt and −78,850 Mt respectively, while the Northeast and Northwest of China areas are not significant. Vigorously developing low-carbon technologies and promoting clean energy can effectively reduce carbon intensity. It is recommended to implement the policy of adapting to local conditions according to the current situation of the region, and gradually phase out high energy-consuming industries under the guidance of the government, so as to strive to implement the emission reduction target.

Spatial–temporal change patterns of vegetation coverage in China and its driving mechanisms over the past 20 years based on the concept of geographic division

Based on the datasets of MODIS NDVI and SPOT VETGETATION NDVI from 1999 to 2018, this study has introduced the gravity centre model and time-lag analysis model to explore the spatial–temporal change patterns of the NDVI in China in different sub-regions and its response to climate factors. Results showed that: (1) In 1999–2018, there was an increasing trend in vegetation coverage in China on the whole, with a larger increase occurring in central south and northeast China. (2) The NDVIs of six land use types showed a similar change trend with temperature and precipitation with different time lags. (3) The maximum correlation coefficients between the NDVIs of different land types and climate factors appeared at Lag 0–1 (current month and previous one month) and Lag 0–2 (current month, previous one and two month), while the correlation coefficients were the lowest at Lag 3 (previous three month). (4) During the past twenty years, the gravity centres of the NDVI, temperature and precipitation moved northward as a whole with similar migration trajectories. These results could provide important decision supports for vegetation restorations and ecological protections in different sub-regions of China.

Change, mechanism, and response of pollutant discharge pattern resulting from manufacturing industrial transfer: A case study of the Pan-Yangtze River Delta, China

Abstract Manufacturing industrial transfer is an important approach to promote the optimization and upgrading of industry, as well as leads to the spatial response of environmental pollution. In this paper, we applied the gravity centre model to measure the changes in pollutant discharge patterns from 2005 to 2015 in the Pan-Yangtze River Delta, and then investigated the drivers of pollutant discharge patterns changes with an improved econometric model which integrated the push–pull theory and STIRPAT random regression model. The results revealed great changes in pollutant discharge patterns due to manufacturing industrial transfer, with the pollution gravity centre and total discharge transferring from east to west. We also found indications of a delayed response between the movement of industry and a corresponding reduction in pollutant emissions. The modelling results suggested that differences in regional economy, technological innovation, industrial upgrading, and environmental regulation influenced observed changes in pollutant discharge patterns. Specifically, regional economic conditions and more stringent environmental regulations can push pollution-intensive industry out of developed areas into developing areas. Meanwhile improved innovation milieu and industrial optimization provided resistance for pollution-intensive industries to stay in developed areas as well as encouraging movement into developing areas.