Land circulation is an important measure that can be utilized to enable agricultural management at a moderate scale. It is therefore imperative to explore spatiotemporal changes in land circulation and the factors that drive these variations in order to maintain and increase the vitality of the land rental market. An initial analysis of spatiotemporal patterns in land circulation is presented in this study on the basis of data from 169,511 farm households between 2003 and 2013. The rural fixed observation point system advocated by the Chinese Ministry of Agriculture was utilized for this analysis, and Heckman two-stage models were developed and estimated in order to identify the drivers of regional differences in land circulation at the national scale and at the levels of different terrains. The results of this study show that the rate of land circulation in China rose from 15.09% to 25.1% over the course of the study period, an average rate of 0.8%. More specifically, data show that the rate of land circulation in the south of China has been higher than in the north, that the average land rental payment was 4256.13 yuan per ha, and that 55.05% of households did not pay such a fee during the land circulation process. In contrast, the average rent obtained was 3648.45 yuan per ha nationally even though 52.63% of households did not obtain any payments from their tenants. The results show that land quality, geographic location, transaction costs, and household characteristics have significantly affected land circulation in different regions of China. Specifically, the marginal effects of land quality and geographic location were larger in the plain regions, while transaction cost was the key factor influencing land circulation in the hilly and mountainous regions. The signal identified in this study, rent-free land circulation, is indicative of a mismatch that has led to the marginalization of mountainous regions and higher transaction costs that have reduced the potential value of land resources. Thus, as the opportunity cost of farming continues to rise across China, the depreciation of land assets will become irreversible and the phenomenon of land abandonment will become increasingly prevalent in hilly and mountainous regions in the future. The transaction costs associated with the land rental market should be reduced to mitigate these effects by establishing land circulation intermediaries at the township level, and the critical issues of land abandonment and poverty reduction in hilly and mountainous regions should arouse more attention.
This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014. Multiple theoretical perspectives on housing demand, supply, and market, are combined to establish a housing price model to explore the impact of land prices on housing prices. The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique. Finally, the influencing mechanism of land prices on housing prices is discussed. The main conclusions are as follows. (1) Housing prices have a pyramid-ranked distribution in China, where higher housing prices are linked to smaller urban populations. (2) Land prices are the primary driver of housing prices, and their impacts on housing prices vary over different administrative levels. To be specific, the effect of land prices is the strongest in the urban districts of provincial capital cities. (3) The internal influence mechanisms for land prices driving housing prices are: topographic factors, urban construction level, the agglomeration degree of high-quality public service resources, and the tertiary industrial development level. The urban land supply plan (supply policies) is the intrinsic driver that determines land prices in cities; through supply and demand, cost, and market mechanisms, land prices then impact housing prices.
Health inequality is an increasing concern worldwide. Using the coefficient of variation, Theil index, exploratory spatial data analysis, and spatial panel econometric model, we examined the regional inequality, spatio-temporal dynamic patterns, and key factors in the health status of Chinese residents from 2003 to 2013. We found that China’s residential health index (RHI) decreased from 0.404 to 0.295 in 2003-2013 at an annual rate of 2.698%. Spatially, resident health status, based on the RHI, has improved faster in the western region than in the eastern and central regions. Inequality in resident health status continued to increase between 2003 and 2013; inequality between regions decreased, but health status inequality expanded within regions. Furthermore, disparities in health status grew faster in western regions than in the eastern and central regions. The spatial distribution of resident health status formed a “T-shaped” pattern across China, decreasing from east to center then to the west with a symmetric decrease north and south. Using the change in Moran’s I from 2003 to 2008 and 2013, we found that the distribution of resident health status across China has narrowed. All the hot spots and cold spots have decreased, but they are also stable. Resident health status formed a stable cold spot in the western regions, while the east coastal area formed a stable hot spot. Selected explanatory variables have significant direct impacts on resident health status in China: increasing per capita GDP, per capita spending on health, and urbanization, and improving environmental quality all lead to better resident health status. Finally, we highlight the need for additional research on regional inequality of resident health status across multiple time, spatial, and factor domains.
Using counties as the basic analysis unit, this study established an evaluation index system for farmland function (FF) from economic, social, and ecological perspectives. The method combining entropy weighting and multiple correlation coefficient weighting was adopted to determine the weights, and the FF indices were calculated for each county. Subsequently, the spatio-temporal characteristics of farmland function evolution (FFE) were analyzed and the coupled relationships between the sub-functions were explored based on a coupling coordination model. At the same time, the dynamic mechanism of FFE was quantitatively analyzed using a spatial econometric regression analysis method. The following major conclusions were drawn: (1) The farmland economic function generally exhibited a declining trend during 1990-2010, and it is essential to point out that it was stronger in underdeveloped and agriculture-dominated counties, while it continuously weakened in developed areas. Farmland social function decreased in 60.29% of the counties, whereas some counties, which were mostly located in north of Zhengzhou and west of Dezhou and Cangzhou, Yantai, and Weihai, clearly increased. A dramatic decline in farmland ecological function occurred around Beijing, Tianjin, and Jinan. Areas located in the northern part of Henan Province and the central part of Shandong Province saw an increase in ecological function. (2) There was a significant spatial difference in the coupling degree and coordination degree of the sub-functions, and the decoupling phenomenon highlighted this. The changes in social function and ecological function lagged behind economic function in developed areas, but these were highly coupled in some underdeveloped areas. (3) FFE in the Huang-Huai-Hai Plain (HHHP) is resulted from the comprehensive effects of regional basic conditions and external driving factors. Furthermore, the transitions of population and industry under urbanization and industrialization played a decisive role in the evolution intensity and direction of farmland sub-systems, including the economy, society, and the ecology. According to the results mentioned above, promoting the transformation from traditional agriculture to modern agriculture should be regarded as an important engine driving sustainable development in the HHHP. Taking different regional characteristics of FFE into account, differentiated and diversified farmland use and management plans should be implemented from more developed urban areas to underdeveloped traditional agricultural areas.
Until 2015, China had established 2740 nature reserves with a total area of 1.47 million km2, covering 14.8% of China’s terrestrial land surface. Based on remote sensing inversion, ecological model simulation and spatial analysis methods, we analyzed the spatial and temporal variations of fractional vegetation coverage (FVC), net primary production (NPP), and human disturbance (HD) in habitats of typical national nature reserves (NNRs) during the first 15 years of the 21st century from 2000 to 2015. And then the three indicators were compared between different NNR types and varied climate zones. The results showed that (1) the average 5-year FVC of NNRs increased from 36.3% to 37.1%, and it improved in all types of NNRs to some extent. The annual average FVC increased by 0.11%, 0.84%, 0.21%, 0.09%, 0.11% and 0.08% in NNRs of forest ecosystem, plain meadow, inland wetland, desert ecosystem, wild animal and wild plant, respectively. (2) The NPP annually increased by 2.06 g·m-2, 1.23 g·m-2, 0.28 g·m-2 and 0.4 g·m-2 in NNRs of plain meadow, inland wetland, desert ecosystem and wild animal, respectively. However, it decreased by 3.45 g·m-2 and 2.35 g·m-2 in NNRs of forest ecosystem and wild plant respectively. (3) In the past 15 years, besides the slight decreases in the NNRs located at the Qinghai-Tibet Plateau and the south subtropical zone, HD enhanced in most of NNRs, especially HD in the warm temperate humid zone increased from 4.7% to 5.35%.
Leaf carbon content (LCC) is widely used as an important parameter in estimating ecosystem carbon (C) storage, as well as for investigating the adaptation strategies of vegetation to their environment at a large scale. In this study, we used a dataset collected from forests (5119 plots) and shrublands (2564 plots) in China, 2011-2015. The plots were sampled following a consistent protocol, and we used the data to explore the spatial patterns of LCC at three scales: plot scale, eco-region scale (n = 24), and eco-region scale (n = 8). The average LCC of forests and shrublands combined was 45.3%, with the LCC of forests (45.5%) being slightly higher than that of shrublands (44.9%). Forest LCC ranged from 40.2% to 51.2% throughout the 24 eco-regions, while that of shrublands ranged from 35% to 50.1%. Forest LCC decreased with increasing latitude and longitude, whereas shrubland LCC decreased with increasing latitude, but increased with increasing longitude. The LCC increased, to some extent, with increasing temperature and precipitation. These results demonstrate the spatial patterns of LCC in the forests and shrublands at different scales based on field-measured data, providing a reference (or standard) for estimating carbon storage in vegetation at a regional scale.
Climate change is a global phenomenon but is modified by regional and local environmental conditions. Moreover, climate change exhibits remarkable cyclical oscillations and disturbances, which often mask and distort the long-term trends of climate change we would like to identify. Inspired by recent advancements in data mining, we experimented with empirical mode decomposition (EMD) technique to extract long-term change trends from climate data. We applied GIS elevation model to construct 3D EMD trend surface to visualize spatial variations of climate change over regions and biomes. We then computed various time-series similarity measures and plot them to examine spatial patterns across meteorological stations. We conducted a case study in Inner Mongolia based on daily records of precipitation and temperature at 45 meteorological stations from 1959 to 2010. The EMD curves effectively illustrated the long-term trends of climate change. The EMD 3D surfaces revealed regional variations of climate change, while the EMD similarity plots disclosed cross-station deviations. In brief, the change trends of temperature were significantly different from those of precipitation. Noticeable regional patterns and local disturbances of the changes in both temperature and precipitation were identified. The trends of change were modified by regional and local topographies and land covers.
In this paper we bring up a Monte Carlo theory based method to measure the ground vegetation parameters, and make quantitative description of the error. The leaf area index is used as the example in the study. Its mean and variance stability at different scales or in different time is verified using both the computer simulation and the statistics of remotely sensed images. And the error of Monte Carlo sampling method is analyzed based on the normal distribution theory and the central-limit theorem. The results show that the variance of leaf area index in the same area is stable at certain scales or in the same time of different years. The difference between experimental results and theoretical ones is small. The significance of this study is to establish a measurement procedure of ground vegetation parameters with an error control system.
Elevated CO2 level in the atmosphere is expected to improve the tree growth rates and intrinsic water-use efficiency (iWUE). Although current results inferring from tree rings found the tree growth decline in water-limited area, it is still unclear whether spruce trees in humid southwestern China benefit from the increasing CO2. In this study, tree-ring width data were used to investigate the tree radial growth rate of Chuanxi spruce (Picea likiangensis var. balfouriana). Moreover, combining with the tree-ring carbon isotope date, we analyzed the physiological responses of Chuanxi spruce to rising CO2 concentrations in the atmosphere (Ca) associated with climatic change in southwestern China. From 1851 to 2009, iWUE of Chuanxi spruce rose by approximately 30.4%, and the ratio of atmospheric CO2 to leaf intercellular CO2 concentration (Ci/Ca) showed no significant trend in the study area. The result suggested that Chuanxi spruce used an active response strategy when Ca was significantly increased. iWUE showed a significant increasing trend in parallel with tree radial growth, indicating that the increasing iWUE resulted in an increase in radial growth. These results suggest that spruce forests in southwestern China have not shown declining trends under increasing Ca and climate change scenarios, in contrast to trees growing in water-limited areas. Therefore, spruce forests benefit from the increasing CO2 in the atmosphere in the humid areas of southwestern China.
The synergistic relationship between urban functions and street networks has always been a focus in the field of urban research and practice. From the perspective of street networks, by adopting space syntax, this study analyzed the deep structural characteristics and potential evolution rules of commercial blocks attached to street networks in different periods, as well as the corresponding economic, political, and cultural characteristics of ancient Beijing city over the past 800 years. By combining these with changes in the street network, we further explained the function mechanism of layout and level adjustment in commercial blocks, and the influence of the street network on commercial blocks in the process of historical change. The main conclusions included the following: (1) The urban centripetal-centrifugal siphon effect: the layout form, topological structure, and traffic mode changes in the street network had corresponding guidance for the layout and hierarchical system of commercial blocks, while the centripetal development of the street network could guide the agglomeration effect of commercial blocks, although centrifugal development caused commercial blocks to display outward evacuation. (2) Stage transformation from mutation node to smooth development: the layout of commercial blocks came to depend on the ability to cross the commuting flow center, which originally relied on the accessibility of transportation nodes as local centers. Changes in traffic modes mainly affected the adjustment of the first-level commercial blocks, which easily led to overall layout mutation. Traffic levels have an obvious positive hierarchical relation with the second- and third-level commercial blocks. (3) The adaptation of traditional commercial blocks to the needs of a modern city: affected by the different emerging times and unevenness of the original commercial foundation, commercial blocks have formed various developmental models that meet the needs of modernization, and reach a balance between cultural continuity and functional adaptation.
