The increasing complexity of oil flow within oil trade networks has become a key factor affecting oil supply security. Here,we constructed China's oil trade network to analyze the overall features and patterns of oil flow using complex network theory. From 1990-2015,the influence of China on network trade partners gradually increased,while exporting countries followed the opposite pattern. The transmission efficiency of China’s trade network followed a downward trend and then slightly increased. China's main oil import sources transferred from the Asia-Pacific region to the Middle East（51%）,Africa（19%）,Russia and Central Asia（15%）and the Americas （13%）in 2015. We estimated oil supply security from 1993-2015 using different evaluation models and found it was 23 in 1993 and 47 in 1999,peaking at 48 in 2004 before falling to 42 in 2015. The political risk rating of exporting countries was the most important factor affecting China's oil supply security. We simulated attenuation in supply security across China's oil trade network under two different attacks scenarios：a random attack and targeted attack. We found that China's oil trade network is fragile to targeted attacks and would experience a rapid decline in oil supply security;the network is robust to a random attack. Accordingly,the key for China safeguarding its oil supply security is how to prevent a targeted attack. These findings have significant implications on the implementation of oil import diversification policy,for example,increasing oil imports from Russia,Kazakhstan,Azerbaijan and the Americas,that are critical to assuring China's oil supply security in coming decades.
Establishing a new path of development in order to realize four modernizations （urbanization,industrialization,informatization and agricultural modernization）implies energy-saving. Simple indices such as urbanization rate or the fraction of industrial added value in GDP have been the focus of previous research. Simple construction of the indices cannot reflect new pattern development of the four modernizations. The implication of the new-pattern means other factors,such as energy consumption,environmental disruption and conservation need to be considered. This study investigated the effects of new pattern development of the four modernizations on energy intensity in order to assess the regional development of China,employing provincial level data from 2011 to 2014. First,we constructed four new type indices using principal component analysis and then presented the distribution of the indices among 30 provinces of China. The results show that the development of the four modernizations basically coincides with the economic development of China. Then,we use panel data model to estimate the effect of four new type indices on energy intensity. The results show that the development of new-type urbanization,informatization and agricultural modernization significantly improve energy intensity （i.e. decrease the energy consumption per production）. However,we show that the impact of new-type industrialization on energy intensity is minor. In addition,the marginal contribution of the new-type index has a decreasing effect on energy intensity. Specifically,improving one facet of the four modernizations will have minor effect on energy intensity under high-development of the other three dimensions of modernization. These results indicate that the effect of modernization on energy intensity will be convergent at some point. Therefore,it is very important to decrease China's energy intensity by improving regional resource allocation efficiency and the new pattern four modernizations of underdeveloped provinces.
Land circulation is an important to realizing agriculture moderate scale management and increasing farmer income in China. However,the aging of the agricultural labor force,which has traditionally inhibited land circulation,is intensifying in rural areas. Here,Logit models were established using data from 8051 farm households under the Chinese Household Income Project （CHIP2013）conducted by the China Institute for Income Distribution in 2013 to reveal the relationship between the age and farmland transfer. We found that the land transfer rate was about 30% in 2013,and family decisions on whether to participate in land transfer could be rationalized. We found that families with a higher proportion of elderly laborers were not willing to participate in land transfer,and ageing laborers may inhibit the land circulation. On the other hand,families with a higher proportion of young and middle-aged laborers were willing to participate in land transfer;the former tended to rent out farmland and the latter tended to rent in farmland. In addition,we found that the comparative advantages of household laborers based on labor age were the root that determined whether how the household participated in land transfer. Policy implications are that the old-age security system of rural supporting should be established and perfected in order to reduce aging population’s dependence on farmland. Professional training for non-agricultural employment should be provided to enhance farmland transfer intention. Financial and technical support should be provided to develop moderate scale management for farm households that rent in land.
As a new type of agricultural management,family farms have strong practical significance in promoting modern agricultural development and rural land resource distribution. Scale merit is a distinctive feature of family farms,which is an important prerequisite for the development of family farms into moderate pieces of land available for a stable period of time. Under the current legal and policy framework,land transfer is an important way for family farms to concentrate required land. Based on surveys of 265 randomly sampled households in Xinyu city,Jiangxi,we used normative and empirical methods and binary logistic regression modeling to study the impact of developing family farms on the land transfer willingness of farmers. We found that family farm development influences farmers' willingness for inward and outward land transfer. The more family farms in a village,the more that farmers in the village are willing to transfer out land,but less willing to transfer in land. Local government economic subsidies for family farms increase the willingness for transferring land in and decrease willingness for transferring land out. Sex,non-agricultural income as a proportion of total household income, pieces of land,and average yield of agricultural land affect willingness to transfer out agricultural land. Age, non-agricultural income as a proportion of total household income,level of education and the average yield of agricultural land affect willingness for transferring in land. We conclude that the development of family farms promotes resident land transfer willingness and we discuss policies and suggestions for the development of family farms and agricultural land transfer.
The livelihood capital standard of contracted households determines their dependence on land,especially cultivated land. Accurately calculating cultivated land transfer-out potential of these households and ordered circulation schemes helps provide a basic means of production of land for developing new types of agricultural management subjects and deepening industrial convergence. Here,we take Fengsi Village in Hechuan district,Chongqing as a case study and use sustainable livelihood quantification to measure the livelihood capital of households,calculate cultivated land transfer-out potential,document understand spatial differentiation,and design differentiated scale management patterns for the agricultural industry of the village. We found significant differences in the contribution of different livelihood capital to land transfer-out potential,among which human capital,financial capital and social capital play positive roles and natural capital and physical capital play negative roles. The whole village’s cultivated land transfer-out potential is 82.45hm2 （accounting for 28.11% of the total cultivated land of the village area）,representing a gradual decrease from southeast to the northwest and dividing the village into three cultivated land transfer districts. Specifically,the advance area will be built as an agricultural enterprise drive type integrating production,processing,sales and the service function all-in-one;the secondary area will be built as a family farm and specialized household radial type;and the last stage area will be built as a cooperative link type.
Land fragmentation and land quality are important factors that influence the efficiency of agricultural production. Based on a survey of 354 rice farmers from the Jianghan Plain we used the stochastic frontier production function with efficiency loss to explore the effects of different combinations of land fragmentation and land quality on grain production technical efficiency in different models. We found that land fragmentation has a negative impact on grain production but positive impact on technical efficiency. Land fragmentation intensifies agriculture production labor,which also holds back the development of capital intensive agriculture. In other words,a high degree of land fragmentation and reducing agricultural labor input makes asset allocation unreasonable,and affects production efficiency severely. Land quality has a significant positive influence on food production and efficiency,the higher the level of land quality the better grain production and production efficiency. Excessive chemical substance input of farmers may harm land quality in the future,but makes no difference to production. Few farmers have this kind of cognitive or even regulate planting behavior. We conclude that to ensure grain security and improve farmer income the government should guide land circulation as the base of modern capital intensive agriculture;improve mechanical and technical service levels to create production conditions;encourage and promote new and sustainable planting pattern to reduce agricultural material waste;and strengthen agricultural infrastructure construction to improve the planting environment.
Construction land expansion and urban population aggregation are two critical and interactive processes during urbanization. The spatial imbalance between them has become a constraint of healthy urbanization. This study analyzed the characteristics of the spatial imbalance between construction land and the urban population on the West Coast of the Taiwan Strait Area,using spatial distribution index,comparative advantage index,and deviation coefficient modeling. Driving forces of the spatial imbalance were explored based on OLS and GWR models. We found that the main sticking points driving the spatial imbalance between construction land and the urban population were spatial sprawl,uneven distribution and violent fluctuation of construction land. The imbalanced spatial distribution has experienced a phased process,and the gap expanded at first and then narrowed. Construction land shows significant central city oriented spatial aggregation,and spatial aggregation far outstripped spatial aggregation of the urban population. This spatial imbalance exhibited significant regional differences and a spatial polarization pattern,and was closely related to city development. Along with city development,the imbalance evolved from aggressive expansion of construction land to aggressive aggregation of urban population and eventually to the balance of spatial patterns. Changes in industrial structure,land urbanization level,economic efficiency of land and geographical positions were identified as main driving forces of the spatial imbalance between construction land and urban populations. These findings will help optimize the allocation of land resources,and facilitate implementation of new urbanization.
Nonlinearity is one of important frontier issues in the field of modern hydrology. It is of great significance to discover the variation and the complexity of the hydrological system. On the basis of hydrological and meteorological data in the headwater region of the Kaidu River from 1960 to 2012,multi-scale characteristics of runoff variability were analyzed using the ensemble empirical mode decomposition method to investigate nonlinear change characteristics of runoff at different time scales and multi-scale responses to climate fluctuation. We found that in the past 50 years,the overall runoff of Kaidu River in Xinjiang has exhibited a significant non-linear increasing trend,and changes have manifested at quasi-2~3 and quasi-4~5 year inter-annual scales and showed quasi-10~11 and quasi-26~27 year inter-decadal scales. Variance contribution rates of each periodic component showed that inter-annual change held a dominant position in the long-term change of runoff,and inter-decadal change also played an important role in the overall runoff change for Kaidu River. Reconstructed inter-annual variation describes the fluctuation state of original runoff during the study period,that is to say the trends of both are basically the same. The reconstructed inter-decadal variability shows that the runoff of Kaidu River underwent a significant transition in 1995 from low to high,namely the state of runoff anomaly shifting from a negative phase to a positive abundance water period. In addition,we found that the correlation between runoff and precipitation is more relevant and significant at both the inter-annual and inter-decadal scales compared to the correlation between runoff and temperature and potential evaporation,indicating that precipitation is the decisive factor for changes in runoff. Corrections between runoff and precipitation,temperature and potential evaporation are more significant and relevant at the inter-decadal scale than inter-annual scale,suggesting that the inter-decadal scale is more suitable for investigating responses of runoff dynamics to climate fluctuation.
Improving industrial green water efficiency is important to alleviating water resource shortage and water environmental pollution in China. Here we incorporated industrial water resource consumption and water pollution emissions into a unified analysis framework and EBM modeling with characteristics of radial and non-radial modeling. Our aim was to measure industrial green water efficiencies in 11 provinces from the Yangtze River Economic Zone and investigate the spatial-temporal differences from 2005 to 2014. The contribution rate of inefficiency for each input was measured by decomposition of overall industrial green water inefficiency from an input perspective. The reason for regional disparities in the Yangtze River Economic Zone industrial green water efficiency was investigated using the Theil index decomposition method,and the potential for industrial water conservation and industrial water pollution reduction were measured according to the gap between target and actual values of inputs. Panel Tobit modeling was done investigate the factors influencing industrial green water resource efficiency. We found that industrial green water efficiency in the zone is relatively low and regional difference are significant,indicating a large potential for industrial water conservation and industrial water pollution reduction. Decreasing the efficiency gap between upstream,midstream and downstream and the efficiency internal gap of upstream provinces is a key measure for the zone’s industrial green water efficiency. Economic development,increasing industrialization degree,increasing industrial water intensity,technological progress,environmental regulation and regional differences all have an effect on industrial green water resource efficiency. These data can help provinces in the Yangtze River Economic Zone utilize industrial water resource efficiently and greenly.
The spatial agglomeration of tourism industry status is seen as an important dynamic factor for tourism urbanization,and is a significant way to influence transformation and development of rural areas. Research has focused on tourism industry agglomeration at large and medium scales,and data is lacking for tourism industry status and its measurement at rural scales. Based on participatory rural assessment,GIS spatial analyses and remote sensing,from the perspectives of land use we analyzed the evolution and mechanisms of tourism industry agglomeration at Gouge village within the Yesanpo tourism area of Hebei,China. We found that tourism industry evolution is a process in itself whereby industry status continues to increase and cluster. Based on scale expansion and grade promotion of the core lodging industry status,this process is along with extended industry status and peripheral industry status implants and gathers continuously. All kinds of industry status agglomeration prefer location choices strictly,core industry status and extended industry status have strong inclinations to landscape and transportation location choice and gather along the Juma River and main road close to the village entrance. Peripheral industry status is more sensitive to transportation location and it gathers along main roads close to the village rear. Tourism industry agglomeration is the result of interactions between natural geography and stakeholders （tourists,tourism farmers,foreign investors and government）and scale economic effects. Because tourism consumption is space consumption,changes in tourism land use provide a new perspective for the study of tourism industry agglomeration characteristics. A comparative study of the characteristics of tourism industry agglomeration across different kinds of rural settlements should be the focus of future work.
Urban tourism plays an important role in optimizing the structure of employment,improving infrastructure construction and broadening employment channels. With rapid tourism development in our country,the government attaches great importance to improving tourism efficiency. We employed a Bootstrap-DEA model to analyze tourism development efficiency and changes in total factor productivity in 21 cities Guangdong,China during 2001-2014. We analyzed spatial-temporal characteristics of urban tourism efficiency through spatial statistical analysis using Moran's Index and Geary’s Ratio,and using a geographically weighted regression model including spatial heterogeneity. The results show that it is necessary to solve the problem using Bootstrap-DEA. From the point view of the mathematical features of efficiency,urban tourism efficiency levels were different in Guangdong：the province as a whole has relatively high urban tourism efficiency,but the efficiency is becoming inefficient. The spatial-temporal characteristics of urban tourism efficiency of Guangdong have evolved from irrelevant to relevant from 2001 to 2014. A key finding was that there is an obvious local clustering trend for urban tourism efficiency. The GWR model based on a bi-square weighted function exhibited better explaining ability. The Moran scatter plots of urban tourism efficiency were used as a reference. Compared with the traditional ordinary least square model based on ‘stationary hypothesis embedding’,the geographical weighted regression model based on ‘non-stationary’ revealed profound spatial differentiation factors. The GWR model based on bi-square weighted function exhibited better model goodness and explaining ability. The scheme of spatial strategic pattern optimization of urban tourism,namely,‘five sections of tourism in Guangdong’ is discussed and a differentiation development strategy constructed. These findings reveal that geographical weighted regression can reconstruct the spatial-temporal nonstationary growth mechanism of urban tourism efficiency.
Rapid development of urbanization and economy has been significant characteristics in China. The relationship between urbanization and economic development is now an important scientific issue. Decoupling methods were used here to analyze the relationship among urbanization（population urbanization,land urbanization）and economic growth（GDP,non-agricultural industry GDP,tertiary industry GDP）in 13 cities in Jiangsu Province,China from 1997 to 2015. Regular pattern of dynamic change,and time and space differences in decoupling status and characteristics were researched. We found that the population urbanization development level was high and distribution difference. Land urbanization development was comparatively steady,and southern regions were ahead of other regions. The annual decoupling coefficient between population urbanization and GDP before 2006 and land urbanization and GDP before 2009 fluctuated greatly. Decoupling types contained strong decoupling,weak decoupling,expansion negative decoupling and expansion connection. The coordinated level between population urbanization and GDP in the southern and central regions was low; northern regions have low urbanization. The decoupling state of land urbanization and GDP were balanced distribution. Up to 96.58% of data were stable and in a weak decoupling state. The dependence of economic growth on population urbanization and land urbanization was diminishing. The decoupling of population urbanization,land urbanization and GDP were consistent from 1997 to 2009,2009-2015 and 1997-2015,and the fluctuation was not as severe as for annual data. All southern regions and most other regions were in a weak decoupling area. The decoupling status among urbanization and GDP were balanced and ideal. The decoupling state changes of urbanization and GDP,non-agricultural industry GDP,and tertiary industry GDP were relatively consistent. The tertiary industry GDP decoupling effect was weaker than non-agricultural industry GDP.
Under the context of deteriorating agricultural resources and environments,accelerating the popularization and application of green technology is of great significance in order to realize the green transformation of agriculture and its sustainable development. Based on household survey data for 281 farmers in three cities in Hubei province,China,we analyzed the factors affecting the paradox between willingness and behavioral adoption of organic fertilizer using Logistic-ISM modeling. We also analyzed the logical relationships between various influencing factors. We found that from the results of Logistic regression,the paradox between willingness and behavior for farmer organic fertilizer adoption is mainly affected by gender,age,herd mentality,soil fertility,planting scale,ecological and environmental protection policy cognition,fertilizer reduction action cognition and awareness of the importance of green production. Differences in green cognition between farmers is one of the important drivers of this paradox. From the results of interpretation structural model,ecological and environmental policy cognition and fertilizer reduction action cognition are direct influencing factors. Awareness of the importance of green production occupies the middle layer and plays an intermediary role. Gender,age,herd mentality,soil fertility and planting scale are core influencing factors.
China has the second largest mango acreage in the word,and the planting area of mangos has followed a trend of sustained growth. Remote sensing has proved very useful in collecting information about the area of cereals and forest,but has rarely been applied to mango orchards. To utilize remote sensing in mango data collection,we attempted to estimate the acreage of mango orchards in China. Data from SPOT-6 and ASTER GDEM covering the study area was used. The boundary mask and sample points were used for acreage estimation. Vegetation coverage （FVC）and SLOPE factors were used to extract information about mango orchards using the object-oriented method. We found that mango orchard producer’s accuracy obtained by object-oriented classification and FVC and SLOPE data segmentation is as high as 92.81%;user accuracy is as high as 97.19%. Compared with maximum-likelihood classification and object-oriented classifi-cation without FVC and SLOPE data segmentation,object-oriented classification with FVC and SLOPE data segmentation has a higher accuracy for mango orchard extraction：producer accuracy increased by 19.28% and 3.62%,and user accuracy increased by 8.62% and 3.86%,respectively. Therefore,object-oriented classification with auxiliary data improves the accuracy of mango orchard extraction and this method provides an effective technical reference for other artificial orchards.
The emissivity of natural surfaces is a major parameter determining land surface temperature（LST）. In addition,the surface cover type influences emissivity and soil moisture is closely related to emissivity. Here,methods for obtaining the emissivity of bare soil using the MODIS generalized split-window algorithm and Landsat mono-window algorithm were improved. According to the empirical logarithm linear formula between soil moisture and soil emissivity,based on remote sensing data and ground observation data from the Soil Moisture Experiment 2004 （SMEX04）- Arizona study area,we discuss if the accuracy of land surface temperature retrieval can be improved when surface emissivity acquisition methods consider effects of soil moisture. We found that the accuracy of both improved algorithms considering soil moisture effects were better than algorithms not considering soil moisture effects. The mean error of LST retrieved by the improved MODIS generalized split-window algorithm reduced 1.0~1.5K,and the root mean square error reduced by 0.4~0.8K. Moreover,the mean error of LST retrieved by the improved Landsat mono-window algorithm reduced by 0.7K,and the root mean square error reduced by 0.9K. As a whole,the accuracy of land surface temperature retrieval can be improved when surface emissivity acquisition methods consider the effects of soil moisture,especially areas where vegetation coverage is less. Sensitivity analysis results show that the influence of remote sensing soil moisture data with a 0.04cm3/cm3 error on LST retrieval algorithms considering soil moisture effects is not obvious.
One of the key links in the study of the relationship between rice and climate is the selection of the time scale. To evaluate climate suitability of rice under short-term disaster scenarios,we considered factors such as air temperature and sunshine duration in Liaoning Province from 1961 to 2010 and assigned weights to these factors according to path analysis theory and climate yield data. A daily model was constructed to represent climate suitability for rice production,and climate suitability assessment criteria were developed for different climate regions. Comparing this newly developed daily model with a 10-day model expounds the climate suitability of different time scale models under short- to medium-term disaster weather. The results showed that the daily climate suitability model was able to provide an accurate representation of climate conditions and their effect on rice growth. The daily model also indicated that climate suitability during the vegetative growth period is related to plant height,with a correlation coefficient R of 0.722. Climate suitability during the reproductive growth period is also related to rice yield,with a correlation coefficient R of 0.669. The degree of suitability of each climatic region was determined using climate suitability assessment criteria established in this paper. The results indicate that,in the case of unexpected flooding,the daily model performs better than the 10-day model at evaluating climate suitability during the rice growth period. Besides climatic conditions,the agricultural production of rice is also related to many factors,so it is necessary to further study the comprehensive suitability evaluation model of rice production combining climate and topography and soil type and popularize it across a wider range of space.
