The study of the spatio-temporal effects of urban rail transit on land-use change is significant for the collaborative simulation of land use and urban rail transit. In this paper, high-resolution remote sensing images and POIs data were combined to acquire fine-scale land use information. A stepwise regression model and a land function classification method were used to investigate the spatial and temporal effects of urban rail transit on land-use change. The results indicated that low density residential land would be converted to high density residential land and commercial land under the influences of urban rail transit. The influences of rail transit on land use vary over its various stages, including planning, construction and operation. In the planning and operation stages, such influences are mostly found in suburban areas with better transport infrastructure, while in the construction stage, they are related to available areas for land development. The land function around the urban central stations has changed slightly due to the restriction of land, while the land function around the suburban stations has changed significantly. The transitions of land function will emerge when metro stations go into operation.

The "Grain for Green" project has been initiated in the Loess Plateau since 1999, and would be continuously promoted in the future. Therefore, it is of important significance to assess the vegetation restoration and its potential in the Loess Plateau. In this paper, based on the SPOT VEG NDVI dataset, the trend analysis, Hurst exponent method, statistical methods and geographical spatial analysis technology were adopted. Results showed that NDVI from 1999 to 2013 had a significant upward trend and the vegetation of 2/3 of the area would continue to improve. In loessal areas, the analysis of vegetation response curve indicated that vegetation coverage had a significant exponential relationship with drought index. Such relationship of gentle slope was more obvious than that of steep slope. The best vegetation response function of soil and rock-mountainous areas was linear function. Its correlation coefficient was lower than that of loessal areas. In the future, the average vegetation restoration potential of the Loess Plateau could reach 69.75%, which was high in the southeast and low in the northwest of the plateau. The region with better vegetation restoration would have lower vegetation restoration potential index. The vegetation restoration potential was mainly concentrated in the northern sandy land as well as in the western hilly and gully area. Subsequently, the differences of vegetation restoration rate for this region under different precipitation thresholds were remarkable, among which the area with precipitation of 375-450 mm had fast vegetation restoration. The measures "adaptation to water conditions" should be taken so as to avoid soil drying for afforestation. The results provided scientific support for the construction of ecological civilization on the Loess Plateau.

Based on environmental records, archaeological findings, and isotopic data, the environmental changes and cultural exchange between East and West along the Silk Road in arid Central Asia during the Holocene have been studied. The results show that the cultural exchange is definitely influenced by geographic setting and environmental changes. Hexi Corridor is located at the marginal area of monsoonal Asia, characterized by monsoon-westerly transitional model. From Xinjiang to Central Asia, the environmental change demonstrated uniform trends during the Holocene: the early Holocene witnessed dry environment conditions and desert vegetation, while during the mid and late Holocene, steppe vegetation expanded when moisture increased. The cultural exchange between East and West along the Silk Road took advantage of moisture conditions during the mid to late Holocene. Benefited from the improvement of environmental conditions, the cultural exchange between East and West accelerated after 2000 BC. During 2500-2000 BC, Eastern and Western agriculture met and integrated along the Silk Road, representing the beginning of prehistoric "Silk Road" along the Tianshan Mountains. Furthermore, during 2000-1000 BC, a mixed economy characterized by wheat/barley-millet-husbandry appeared in the oases along the Silk Road, and expanded to the Eurasia steppe after 1500BC, being a sharp contrast to the surrounding animal husbandry and continuing to the historic periods. Such spatial differentiation is the result of integrated geographic setting and cultural exchange between East and West. During the prehistoric period, Eastern and Western agriculture oppositely spread along the oases in a leapfrogging forward way. While during the historic periods, political factors were the primary controlling upon the Silk Road, but environmental change was still a factor that cannot be ignored.

Several dynasty palaces in Kaifeng City were buried by flood sediments of the Yellow River, forming the unique spectacle of city overlapping city, which were taken as excellent and rare samples to assess heavy metal enrichment and pollution of historical cultural layers. Three sedimentary cores with a length of 25 m were drilled in April, 2012, of which two were located in the urban area of Kaifeng City (ZKsz and ZKyz), and the other one was located in the western suburbs of the city (ZKjm). Each core was split into 10 cm intervals mostly, for a total of 657 soil samples. Concentrations of Pb, Cd, Cu, Zn, Ni, Cr and Co in samples were measured by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), while Hg and As were analyzed with Atomic Fluorescence Spectrometer (AFS). The dating frameworks of all the cultural layers in different dynasties were established according to AMS¹⁴C dates, archaeological explorations and historical documents. The results showed that six cultural layers were found in all the three sedimentary cores, including the Warring States, Song-Jin Dynasty, early Ming Dynasty, mid-Ming Dynasty, late Ming Dynasty and Qing Dynasty. Enrichment factors (EF) were calculated to assess the enrichment of heavy metals in cultural layers. Enrichment of most heavy metals occurred in the cultural layers, and Hg contributed to the highest enrichment level. Enrichment levels of Hg in the cultural layers of the two urban cores (ZKsz and ZKyz) before the early Ming Dynasty were from significant to extremely high. Pollution load index (PLI) was used to identify pollution levels of heavy metals in cultural layers. Most cultural layers showed slight to moderate pollution, while Song-Jin cultural layers of the two urban cores were considered as moderate pollution. Mercury was the main pollutant of the two urban cores while Cu, Pb and Zn had minor effects on the pollution, due to the wide use of cinnabar with high Hg contents in the history. As for the cultural layers of ZKjm core, Cd, Cr, Hg and Pb made more contributions to the pollution. The results also showed the positive linear relationships between metal PLI of cultural layers and their corresponding population densities. The decreasing PLI values from the early Ming to late Ming Dynasty were influenced probably by the frequent floods of the Yellow River.

The economy of China has maintained rapid growth with an average annual GDP growth rate of 10.14% (in comparable price) from 2000 to 2012. During this period, China witnessed frequent landslide disasters, including 338,964 identifiable individual landslide disasters that resulted in 45,381 casualties, including 9,928 deaths. Analysis of the casualty events caused by landslides from 2000 to 2012 revealed that the spatial pattern of the casualty events was affected by terrain and other factors of the natural environment, which resulted in the distribution of casualty events being higher in the south region than in the north region. Hotspots of casualty events caused by landslides were in the western Sichuan mountain area and the Yunnan-Guizhou Plateau region, the southeast hilly area, the northern part of the loess hills, and the Qilian and Tianshan Mountains, among some others. However, their local distribution pattern indicated that they were also influenced by economic activity factors. To quantitatively analyze the influence of natural environment factors and human-economic activity factors, the binary logistic regression model was applied. The binary logistic regression model is a type of probabilistic nonlinear regression model describing the relationship between a binary dependent variable and a set of independent variables (explanatory factors). The explanatory factors used in this study included relative relief, mean annual precipitation, vegetation coverage, fault zones, lithology, soil type, GDP growth rate, industry type, and population density. The dependent variable used in this study was the presence (1) or absence (0) of casualty events caused by landslides in the county. For the logistic regression analysis, the continuous variables of relative relief, mean annual precipitation, vegetation coverage, GDP growth rate, and population density were substituted into the model. The categorical variables of fault zones, lithology, soil type, and industry type were transformed into binary dummy variables and then substituted into the model. The Probability Model of Casualty Events Caused by Landslide in China (CELC) was built based on the logistic regression analysis, and the confusion matrix and the receiver operating characteristic (ROC) curve were applied to assess the model performance. The results showed that all explanatory variables in the model were selected based on a significance level of 0.05. The coefficients of the explanatory variables showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density have a positive effect on casualty events caused by landslides. In contrast, vegetation coverage has a negative influence on casualty events caused by landslides. More specifically, the results showed that in terms of the influence degree of casualty events caused by landslides, the GDP growth rate ranks only second to relative relief. The probability of occurrence of casualty events caused by landslides will be 2.706 times that of the previous probability with an increase of GDP growth rate of 2.72%. In the evaluation of the model performance, the correct percentage in the confusion matrix is 75 % and the area under the ROC curve (AUC) is 0.826, revealing that the CELC model has good predictive ability. The CELC model was then applied to calculate the occurrence probability of casualty events caused by landslides for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events caused by landslides. The 27 counties can be divided into three categories: poverty-stricken counties, mineral-rich counties, and realty-overexploited counties, which are the key areas where great emphasis should be placed on landslides risk reduction.

The innovation of spatial poverty measurement method is the key to precisely allocate poverty alleviation resources and improve the quality of rural poverty alleviation. This paper summarized the three-dimensional analysis framework of spatial poverty and constructed the spatial poverty index system at county scale and the method of geographical identification. With Jingyuan county as a study case, the geographical identification of spatial poverty was carried out. The results can be obtained as follows. (1) Spatial poverty index (SPI) in different geographical areas is listed in the order: Plain Area in Valleys Formed by Erosion and Deposition of Rivers (PAVFEDR) (mean value 1.571) > Denudation Structure in Hilly Regions (DSHR) (mean value -0.199) > Erosion Structure in Mountainous Regions (ESMR) (mean value -0.334), indicating that the highest poverty degree is in ESMR, which should be the main area of poverty alleviation. The common feature of spatial poverty in the three geographical areas is economic disadvantage (C₄-C₇, C₁₇). The main differences are: for PAVFEDR, ecological disadvantage (C₂₅, C₁₆) > economic disadvantage (C₅) > location disadvantage (C₂₀) > political disadvantage (C₈); for DSHR, economic disadvantage (C₅-C₇, C₁₇) > location disadvantage > (C₁₈-C₂₀) > ecological disadvantage (C₁₆, C₂₃-C₂₅) > political disadvantage (C₈); for ESMR, economic disadvantage (C₄-C₇, C₁₇) > political disadvantage (C₈) > location disadvantage (C₁₈-C₂₀) > ecological disadvantage (C₁₆, C₂₁-C₂₅). (2) The rank of SPI for different ethnic villages is as follows: Han villages (mean value 1.484) > Hui villages (mean value 1.262) > Hui-Han mixed villages (mean value 1.033), indicating that Hui-Han mixed villages at county scale should be the key villages for poverty alleviation. The common feature of spatial poverty in different ethnic villages is the economic disadvantage resulting from the long distance to the nearest market (C₁₇), as well as the ecological disadvantage due to less arable land per capita (C₂₃) and small crop area, especially economical crop area (C₂₄). The main differences of spatial poverty in different ethnic villages are ecological disadvantage resulting from poor living conditions and high disaster loss rate in Han villages, as well as economic disadvantage caused by lack of loans (C₅). For Hui villages, it is economic disadvantage caused mainly by low level of knowledge (C₁₂, C₁₃) that leads to the high opportunity cost in entering the market. In Hui-Han mixed villages the differences of production and lifestyle resulted in difficulties in allocation of poverty alleviation resources, consequently the satisfaction rate of poverty alleviation policies (C₈) is the lowest for farmers, reflecting that the political disadvantage of spatial poverty is most significant. (3) There are significant differences in spatial poverty among different ethnic villages in the same physical geographical area. The mean values of SPI for Han, Hui, and Hui-Han mixed villages in PAVFEDR are 0.526, 2.557 and 1.644, respectively, which indicates that the Han villages have a high level of poverty and economic disadvantage (C₅); the mean values of SPI for Hui and Hui-Han mixed villages in DSHR are 0.321 and -1.934, respectively, which indicates that the poverty level for Hui-Han mixed villages is high, and economic disadvantage (C₂, C₆, C₇) and ecological disadvantage (C₁₆) are both significant; the mean values of SPI in Han, Hui and Hui-Han mixed villages in ESMR are 1.031, -0.029 and -0.842, respectively, which indicates that the poverty level of Hui-Han mixed villages is high, and economic disadvantage (C₅-C₇, C₁₇), political disadvantage (C₈), location disadvantage (C₁₈-C₂₀) and ecological disadvantage (C₁₆, C₂₅) are all present. Therefore, the Han-villages in PAVFEDR, Hui-Han mixed villages in both DSHR and ESMR should be the key villages of poverty alleviation.

The inversion models applied in hyperspectral prediction of soil heavy metals include multiple linear regression, partial least squares regression, artificial neural network, and wavelet analysis. They are mostly based on the presumed homogeneous influence of heavy metal contents on spectral reflectance in different locations. This presumption, however, ignores the spatial heterogeneity of the correlation between heavy metal and spectral variables. In comparison, GWR model effectively reveals the spatial heterogeneity among different variables, which is well evidenced in the studies involving the spatial prediction of soil properties. But no publications can be found so far on the application of this model in hyperspectral prediction of soil heavy metals. In this paper, Cd, Cu, Pb, Cr, Zn and Ni were studied to establish GWR model for soil heavy metal prediction, with 132 soil samples taken from Fuzhou, a major city in southeastern China. Increasing soil pollution emerges in this area as a result of dense population and developed industrial and agricultural sectors. And the spatial distribution of soil heavy metals in the area features great heterogeneity because of complex and fragmented terrains. At first, metal concentrations of the samples were determined through inductively coupled plasma-mass spectrometry (ICP-MS) analysis, and reflectance was measured with an ASD (Analytical Spectral Devices) field spectrometer covering a spectral range of 350-2500 nm. Then a series of transformations were conducted to enhance the spectral features of heavy metals, such as derivative transformation, reciprocal transformation, absorbance transformation, and continuum removal. And then an analysis was made on the correlation between heavy metal contents and the transformed spectral data, and sensitive spectral bands were selected according to the highest correlation coefficient. With heavy metal contents as dependent variables, and sensitive spectral bands as independent variables, a stepwise regression analysis was conducted to select variables with low multi-collinearity, which were then used to establish prediction models. At last, the applicability and limitation of GWR model in the hyperspectral prediction of heavy metals was assessed by comparing the outcome of predictions based on GWR and OLS regression respectively. Some conclusions can be drawn as follows: (1) The applicability of GWR model is dependent on the spatial heterogeneity level of heavy metal influence on spectral variables: For Cr, Cu, Zn and Pb, whose influence on spectral variables features high-level spatial heterogeneity, GWR-based prediction performance was evidently better than that of OLS. It was shown in an obvious increase of adjusted R² (by 2.69, 2.01, 1.87 and 1.53 times respectively) and an obvious decrease of AIC (by over 3 units) and RSS (by 74.67%, 69.91%, 52.78% and 13.16% respectively); For Cd and Ni, whose influence on spectral variables features low-level spatial heterogeneity, GWR-based prediction displayed an increase of adjusted R² (by 0.015 and 0.007 respectively), a decrease of RSS (by 5.97% and 4.18% respectively) and a rise of AIC (by 2.737 and 2.762 respectively), with less significant improvement in prediction performance; (2) Heavy metal spectral properties are intensified by different spectral transformations, among which reciprocal transformation is most effective. And reciprocal transformation and its derivative patterns improve the performance of heavy metal prediction models; (3) With spatial non-stationarity as the prerequisite of application, GWR model is applicable in hyperspectral prediction of heavy metals that feature obvious spatial heterogeneity with soil spectral variables.

The valley basins, the main grain output area and socio-economic center of Shaanxi Province, are experiencing population growth, rapid urbanization and industrialization. However, the eco-environment is suffering as a result of destructive human economic activities (forest and grassland clearance for farmland expansion, deforestation and vegetation damage) and is potentially facing a huge ecosystem crisis, from the likes of soil erosion and vegetation coverage reduction - all of which hinder local sustainable social and economic development. Because of complicated conditions and its significant location, the Guanzhong Basin, the economic center of Northwest China, and the Hanzhong Basin, an ecological preservation area in Shaanxi Province, were chosen for comparing and analyzing the spatial and temporal disparities between ecosystem services. In this study, we use several mathematical methods including the correlational analysis method, and the linear and power function regression methods to calculate the spatial and temporal differences between the two areas based on ecosystem services data from 1990 to 2010 (NPP, water conservation and food supply). From this, we find that NPP and water conservation have a synergistic relationship, and that there is also a trade-off between NPP and food supply, and between water conservation and food supply. In addition, between 1990 and 2010, this synergistic relationship shows a downward trend while the trade-off relationship demonstrates an upward trend. Furthermore, the rate of change in the Guanzhong Basin is faster than that in the Hanzhong Basin. In terms of the synergistic relationship between NPP and water conservation, the strongest evidence can be found in cultivated land in the east of the Guanzhong Basin and in the west of Ningqiang county and Lueyang county in the Hanzhong Basin; the lowest is observed in Tongchuan city and Xixiang city. When exploring the trade-off between NPP and food supply, we find that the strongest trade-off relationship is in Tongchuan city and the Qinling Mountains in Xi'an and the south of Xixiang county, while the weakest is in Baoji city and Lueyang county.

Central Asia is located in arid and semi-arid regions. This region contributes to dust aerosols because of desertification and land degradation. In order to better understand temporal variability, vertical distribution, and potential diffusion characteristics of salt dust and desert dust in Central Asia, we studied the intranasal changes in dust aerosol from the Aral Sea basin and Taklimakan Desert using MODIS aerosol data and CALIOP data, and analyzed its potential seasonal diffusion from 2005 to 2015 using the HYSPLIT model. Results showed that AOD of this region was high in spring and summer and low in autumn and winter. Over the 14 years, it showed an increasing trend. The mean values of the four seasons were: spring (0.412) > summer (0.258) > autumn (0.167) ≈ winter (0.159). The annual AOD high value areas were mainly concentrated in the Tarim Basin in southern Xinjiang and surrounding areas of Aral Sea. The annual average value of AOD in Aral Sea was 0.278, and annual amplification was 3.175%. It is indicated that the degradation of the Aral Sea had a direct impact on the AOD surrounding area. The annual average value of AOD in the Tarim Basin was 0.421, and annual amplification was 0.062%, which was mainly affected by temperature and wind speed, and the dominant factors were slightly different in different seasons. Dust aerosols were mainly concentrated in a range of 0-2 km. Aerosol depolarization ratio range in the desert (10%-45%) was slightly greater than that in the Aral Sea (15%-30%) and the aerosol color ratio range in the Aral Sea (0.3-0.8) was less than that of the desert (0.5-0.9). There were two high-frequency color ratios of 0.5 and 0.3 from the dust zone over 0-2 km and 4-6 km of salt dust. Compared to dust aerosols, salt dust aerosols had smaller irregularities and particle size, and higher impact of height range. As for the Aral Sea region, the potential distance and height of air parcel trajectories to the northeast were greater than to the west and south, whereas the air parcel trajectory proportion of the former was lower than that of the latter, which mainly affect Uzbekistan and Turkmenistan. Most of the dust in the Taklimakan Desert is still settling in the vicinity of the dust source region. The potential diffusion path to the eastern regions has impact on Qinghai, Gansu, Ningxia, Shaanxi and other regions.

Human-induced land use/cover change (LUCC) has significant effects on the climatic and ecological processes at both global and regional scales. It is an important driving force of global environmental change and has been one of hot topics of international concerns. Since the industrial revolution, the expansion of built-up areas (construction land) has been profoundly changing the status of LUCC. Construction land expansion has been the most dominant feature in land use changes. People's lifestyles and ideas have changed a lot accordingly. It is urgent to to seek solutions to some global issues especially those in fields such as resources, environment and ecology. Historical LUCC research plays a key role in these fields. Confined by the data availability, reconstructing historical construction land confronts with some difficulties. Current research rarely targets at construction land along the historical timeline. There is room for research efforts in extending contents of such reconstructed dataset, quantifying key factors, and improving spatial analytical precision. Therefore, it is sensible to establish a method to reconstruct a more effective, comprehensive, and finer-precision dataset for construction land along the historical timeline. Based on historical records and contemporary statistics on natural resources, this study aims to reconstruct the spatial distribution of construction land (urban land and rural settlement land) for several selected time intersections in the past 200 years in Jiangsu Province with a resolution of 200 m×200 m. The results show that: (1) areas of construction land are estimated to be 963.46 km² in 1820, 1043.46 km² in 1911, 1672.40 km² in 1936, 1980.34 km² in 1952 and 10687.20 km² in 1985; and (2) the spatial distribution of construction land are featured by a tendency to be close to water bodies and main roads as well as an effect of settlements’ polarization and diffusion. The validity of our research results has been proved indirectly by the trend test and the coordination analysis.

Land change has been a hot topic in geographical research. The overarching and convincing theories of land change science, however, have not emerged. Establishment of land use transition theory is of significance for the theory basis of land change science. This paper attempts to establish a research framework of land use transition based on summarizing the development and implications of land use transition research and clarifying the differences between land use transition and land use change. Results show that transition research of artificial ecosystems, such as cultivated land, rural housing land and urban land, is of significance. Land use transition is distinguished from land use change on several aspects, such as fundamental types, temporal scale, spatial scale, agents, driving forces, trajectory, and results or effects. Research framework of land use transition covers transition diagnosis, mechanism research and effects research. Key issues of transition diagnosis are the establishment of measuring indices and diagnosis principles of land use spatial and functional morphologies from the perspectives of quantity change, landscape pattern change and management pattern change, and of land use externality and land use policy development. Mechanism of land use transition behaves as cascading effects of underlying driving factors of land use change, including demographic, economic, technological, institutional, cultural, and location factors. Mechanism research should place emphasis on interaction between land use spatial transition and functional transition. Effects of land use transition covers at least 17 themes relating to social, economic and environmental dimensions. Cultivated land use transition in France in 1961-2011 confirms the research framework of land use transition and is beneficial to the innovation of cultivated land protection in China.

In order to realize equitable and reasonable utilization of transboundary water, the "Convention of the Law of the Non-navigational Uses of International Watercourses" is the first global legal framework which took more than 40 years to discuss, design, sign and approve, and finally entered into force in 2014. Because the Convention has few signatories, the power of the Convention will be affected because some rules are under dispute. In this paper, the locations of each of the Convention's parties in related international rivers were identified based on the maps of the "Global Transbounary Rivers Basin" published by UNEP in 2016. Combined with available water volumes and withdrawals, the importance of related international rivers and regional cooperation on transboundary water of the parties with their locations on the international rivers, the regional, locational and objective differences among the parties to approve the Convention were analyzed and discovered. Some major conclusions are as follows. (1) Up until now, only 36 states are parties to the Convention, which are located in Asia, Africa and Europe, meaning that the Convention will have limited influence. (2) When the Convention balances the rights and the obligations among the riparian states, it is more beneficial for the downstream states to seek water benefits, so that the downstream states have the strongest motivation to sign and approve the Convention, and the Convention's counterbalance affects the motives of the states on the middle reaches, the frontiers or the tributaries. (3) Under the stress of water shortages and the importance of transboundary waters, the riparian states are seeking ways to strengthen the controlling power on its transboundary waters, and ratifying the Convention is one option. (4) The riparian states' experiences with transboundary water cooperation are the basis to be a party to the Convention, as most of the parties gained experience mainly from water project cooperation, and downstream and midstream parties' experiences are from general framework agreements and water projects cooperation.

Field investigations were carried out along the upper reaches of the Hanjiang River, a major tributary of the Yangtze River in China. Three loess profiles on the first river terrace were selected for a detailed study. The characteristics of major elements and chemical weathering were analyzed systematically. Results are shown as follows. (1) The major elements are dominated by SiO₂, Al₂O₃ and Fe₂O₃, the total average content of which is 767. 3 g/kg, in the loess profiles of the region. The contents of the major elements are ranked in the following order: SiO₂>Al₂O₃>Fe₂O₃>K₂O>MgO>Na₂O>CaO. The elements Na, Ca, Mg and Si are leached to different degrees and Fe, Al and K relatively enriched in the chemical weathering processes. (2) The weathering and pedogenic intensity was the weakest in the Malan loess L₁, increased slightly in the transition loess L_t, became the strongest in the paleosol S₀, and decreased again in recent loess L₀. The results reveal that the climate was cold-dry in the Last Glacial (55.0-15.0 ka BP), turned into warm-wet gradually in the Early Holocene (15.0-8.5 ka BP), became the warmest and wettest in the Mid-Holocene Climate Optimum (8.5-3.1 ka BP), and turned into cool and dry in the Late Holocene (3.1-0.0 ka BP). (3) Based on the comparison with Luochuan, Wushan and Xiashu loess, we can find that the major elemental compositions and the UCC-normalized patterns of the loess are similar with those of Luochuan, Wushan and Xiashu loess to a higher degree, suggesting a similar sedimentary background of aeolian loess. But the chemical weathering intensity of these loess deposits changes significantly in different parts of China, with the sequence?of Luochuan loess < loess in the Hanjiang River < Wushan loess

China lags behind most of the developed countries in regional specialization of agricultural production. This backwardness has weakened its competitiveness of agricultural products in world market. It is generally recognized that household farmland area has been the key limiting factor, but it stemmed from qualitative analyses or experiences and lacked supports of empirical analyses. In this paper, we examined the relationship between household farmland area (HFA) and regional specialization at provincial level based on the specialization index of Hirschman-Herfindahl (SHHI) and agricultural statistical data. The data included planting area of crops and per capita area of land managed by households. The results suggested that enlargement of HFA was neither a sufficient condition nor even a necessary one for regional specialization. But it helped. In spatial dimension, the provinces with larger HFA were not at a higher level of specialization inevitably. The rank correlation coefficients between HFA and SHHI were not significant in the period from 2002 to 2012. In temporal dimension, SHHI did not increase or decrease with the HFA in most of the sample provinces. There were only 12 of the 29 sample provinces whose SHHI correlated significantly with HFA. The 12 provinces were those where major crops were more land-intensive. These results implied that enlargement of household farmland area can not improve regional specialization inevitably in China. There is a need for other effective ways to enforce China's regional specialization of agricultural production.