Highlights • Farming-pastoral ecotone (FPE) accounted for approximately 1/5 of China’s total land area. • FPE patterns and driving forces changed diversely in time and space. • The implementation of ecological protection policies has reversed the westward-shifting trend for FPE. Abstract The farming-pastoral ecotone (FPE), defined as the mosaic of transition zone between traditional farming and pastoral regions, is sensitive to climate change and human disturbance. Extensive farming activities within and along FPEs have led to alarming environment degradation in China in the past several decades. Many ecological protection policies have been deployed to improve the structure and function of current FPEs. However, the changes in national FPE patterns as a result of farming activities and ecological protection policies have rarely been quantified using a robust dataset. Therefore, in this study we quantified two-decades of FPE change patterns in China using spatial autocorrelation and spatial clustering methods, along with land use data at 10 year intervals from 1990 to 2010. The results show that the derived FPEs in the north, middle, and south sections along the Hu’s Line underwent remarkable spatio-temporal changes. The north and middle FPEs shifted from the southeast to northwest during the period of 1990–2000, mainly because of extensive farming activities. However, this trend slowed in the north FPE, and reversed in the middle FPE in the 2000s, mainly attributed to the deployment of ecological protection policies. As there are limited farming activities in mountainous terrains, the south FPE did not show notable changes compared with the north and middle FPEs. The PFE changes caused predominantly by extensive agricultural activities and ecological protection policies were then further quantified through transition matrix analyses between FPEs, farming areas (FA), and pastoral areas (PA). Our study suggests that new FPE maps derived from satellite remote sensing could provide a straightforward methodology to quantitatively evaluate the effect of agricultural activities and environmental policies on vulnerable FPE regions.

Abstract In the process of studying dust-storm events, we have to face an important scientific problem: How to define dust-storm intensity (DSI)? This study provides a comprehensive definition of DSI in terms of the frequency, duration, and visibility of dust storms, and uses it to measure the trend of annual changes in dust-storm activities. With dust-storm data from 186 meteorological observation stations in China, the trend in DSI was studied for the period 1980–2007. This trend differs from those based on the frequency of dust storms, which are often used in the literature. In this study, average DSIs after 2000 were underestimated using frequency alone to measure the dust activities, compared with those before 2000. According to the spatiotemporal distribution, there are four modes of change in DSI over the period, namely a significantly decreasing trend, an increasing trend, a mode in which dust storm activity remained constant, and a two-peak mode. Highlights • Re-define dust storm intensity (DSI) with frequency, duration and visibility. • This definition is easily used because the data used is available. • DSI was underestimated after 2000 using the traditional method in China. • There were four modes in the pattern of DSI changes in China in the past 30 years. • Temperature, wind speed and rainfall only explained 5.9% of changes in DSI.

Mountainous areas in China account for two‐thirds of the total land area. Due to rapid urbanization, rural population emigration in China's mountainous areas is very significant. This raises the question to which degree such population emigration influences the vegetation greenness in these areas. In this study, 9,753 sample areas (each sample measured about 64 square kilometers) were randomly selected, and the influences of population emigration (population pressure change) on vegetation greenness during 2000–2010 were quantitatively expressed by the multivariate linear regression (MLR) model, using census data under the condition of controlling the natural elements such as climatic and landform factors. The results indicate that the vegetation index in the past 10 years has presented an increasing overall trend, albeit with local decrease in some regions. The combined area of the regions with improved vegetation accounted for 81.7% of the total mountainous areas in China. From 2000 to 2010, the rural population significantly decreased, with most significant decreases in the northern and central areas (17.2% and 16.8%, respectively). In China's mountainous areas and in most of the subregions, population emigration has significant impacts on vegetation change. In different subregions, population decrease differently influenced vegetation greenness, and the marginal effect of population decrease on vegetation change presented obvious differences from north to south. In the southwest, on the premise of controlling other factors, a population decrease by one unit could increase the slope of vegetation change by 16.4%; in contrast, in the southeastern, northern, northeastern, and central area, the proportion was about 15.5%, 10.6%, 9.7%, and 7.5%, respectively, for improving the trend of NDVI variation.

In China, some people believe that urban land has a large potential for absorbing more of the urban population, while others think that urban population density is very high, and has already caused many urban problems. The population density of 135 major cities is studied by using the city population data (Shiren kou) from the Fifth Census of China in 2000. The data included the floating population who lived in cities for more than 6 months/year, so it could more closely reflect the real size of the urban population. Land-use data were obtained from a digital map interpreted from remotely sensed data collected in 2000. The results show that urban population density was fairly high in China and the average urban land per capita of these cities was only about 76 m2 in 2000, but that the corresponding value was 106 m2 if it was calculated with the non-agricultural population. Moreover, urban population density varied greatly between cities: from 4×103 to 22×103/km2. Regression results show the differences in urban population density were strongly related to six independent variables, including wage per capita, city size and shape index of urban land, etc. The policies derived from the results deserve more attention in the new land-use planning with the target year of 2020 in China.

In China, some people believe that urban land has a large potential for absorbing more of the urban population, while others think that urban population density is very high, and has already caused many urban problems. The population density of 135 major cities is studied by using the city population data (Shiren kou) from the Fifth Census of China in 2000. The data included the floating population who lived in cities for more than 6 months/year, so it could more closely reflect the real size of the urban population. Land-use data were obtained from a digital map interpreted from remotely sensed data collected in 2000. The results show that urban population density was fairly high in China and the average urban land per capita of these cities was only about 76 m2 in 2000, but that the corresponding value was 106 m2 if it was calculated with the non-agricultural population. Moreover, urban population density varied greatly between cities: from 4×103 to 22×103/km2. Regression results show the differences in urban population density were strongly related to six independent variables, including wage per capita, city size and shape index of urban land, etc. The policies derived from the results deserve more attention in the new land-use planning with the target year of 2020 in China.

Abstract City size is closely related to urban heat island intensity (UHII). To examine the relationship more accurately, it is necessary to eliminate the effects of landforms and climatic differences on urban heat islands (UHIs), through selecting settlement clusters in a large plain within a similar biome as the study area. This study selected 1124 land use clusters (cities, towns, and big rural settlements) and demarcated surrounding buffer areas; each buffer width equaled the radius of the clusters. The results showed that UHI increased with growth in cluster size, and the relationship could be described using a logarithmic function. For clusters with an area >2 km 2 , the city size accounted for about 60% of the variance in UHII during the night and only about 30% during the day. For clusters with areas of <2 km 2 , the uncertainty in the relationship increased significantly and the relationship became very weak. In addition, our study showed that daytime UHII was higher than nighttime UHII, particularly for large cities with a size >10 km 2 . Highlights • UHII: urban heat island intensity. • To examine the relationship under the ideal conditions between city size and UHII. • For cities over 2 km 2 , city size explained ∼60% of the variance in nighttime UHII. • Variations in daytime UHII were greater than those in nighttime. • To re-define the rural background of urban clusters.

Highlights • 5 megaregions witnessed rapid urban expansion in China, 1990–2010. • Significant differences in cluster growth across the 5 megaregions. • Urban clusters in the 5 megaregions all fitted closely to the rank-size rule. • Size distribution of the clusters became more uneven. • Policy implications for New Urbanization. Abstract Megaregions have become the principal geographic units for countries to participate in the global economy, which is often a composite of numerous urban clusters which are distributed in different cities. In China, a megaregion is regarded as a key urbanization platform, according to the National Plan on New Urbanization published in 2014. In this context, it is imperative to understand the spatial patterns of and the changes occurring in megaregions. For instance, what are the universal rules or differences related to urban cluster growth between different megaregions in the process of rapid urbanization, and are there differences in the growth of urban clusters with different sizes? Focusing on these issues, this study discusses the uneven growth of clusters in five of the largest megaregions in China using the rank-size rule, based on land-cover data interpreted from time-series satellite imagery during the period 1990–2010. The results show that the cluster size distribution of each of these megaregions obeyed the rank-size rule, and the size distribution of the clusters became more uneven and was tilted toward larger clusters between 1990 and 2010. These factors should be considered in the implementation of the National Plan on New Urbanization in China and the designation of urban macro planning and urban layout optimization in other countries those are experiencing rapid urbanization.

The land fallow policy was adopted by central and local governments to encourage the abandonment of water-intensive crops, such as winter wheat, in groundwater over-exploited areas. At the same time, since the 1990s, many households in the North China Plain (NCP) have chosen to replace the winter wheat and summer maize double-cropping system with the spring maize single-cropping system. Therefore, it is crucial to identify target land parcels for winter wheat abandonment and to design reasonable and proper standards for ecological compensation prior to the implementation of the land fallow policy in the NCP. In this study, multi-level logit models were used with household survey data in order to detect determinants across land parcel, household and village levels on household cropping system decisions; the opportunity costs for winter wheat abandonment were also calculated using cost–benefit analysis. The results show that: (1) land quality and irrigation condition at parcel level are two essential elements influencing household cropping system decisions. Nearly 70% of the total area of poor land and more than 90% of the total area of unirrigated land has suffered winter wheat abandonment. Target land parcels for the land fallow policy should be those that are irrigated and of high quality. (2) There were no significant differences between net profits from spring maize and summer maize under similar farming conditions, and the opportunity cost for winter wheat abandonment should be equal to the net profit of winter wheat. (3) The primary purpose of the land fallow policy is to induce groundwater recovery and restoration as a preliminary stage. A higher level of 350 yuan/mu is recommended as subsidy for ecological compensation at this stage. Later, the primary purpose of the policy should be a transition to a balance between exploitation and supplementation of water resources, and a lower level of 280 yuan/mu is recommended as a subsidy at this stage.

Highlights • Plot level and household level were both crucial in explaining farmers’ abandonment of winter wheat. • Winter wheat was more likely to be abandoned on plots with lower land quality and larger plot areas. • Winter wheat was less likely to be abandoned on plots with stable water availability. • Household non-agricultural income ratio played a positive role on farmers’ abandonment of winter wheat. • Household demographic characteristics also contributed significantly to farmers’ abandonment of winter wheat. Abstract Since the late 1990s, the North China Plain (NCP) has undergone large-scale shrinkage of area sown to winter wheat, accompanying with traditional double cropping system being replaced by spring corns. However, studies on the underlying determinants are rarely found. The goal of this paper is to detect the hierarchical determinants on farmers’ cropping system decisions. A case study was carried out in Xingzhuangzi village of Hebei province, and multi-level statistic models were constructed using household survey data. Results show that plot level and household level were both crucial in explaining farmers’ land use decisions: winter wheat was more likely to be abandoned on plots with lower land quality, unable to be irrigated, and with larger plot areas; at household level, both the non-agricultural income ratio and the land fragmentation played positive roles on farmers’ abandonment of winter wheat while the role of household agricultural labor availability was negative. There was also a nonlinear relationship between average age of households’ agricultural laborers and their cropping system decisions, and middle-aged farmers had a lower probability to abandon winter wheat. Overall, this paper provides empirical identification on hierarchical determinants of agricultural land use change in the NCP, and encourages policies aiming at adjustment of cropping systems, integration management of both surface and groundwater, and promotion of land transfer, in order to achieve the twin goals of ecological conservation and food security in water-scarce areas.

Highlights • DSI definition considers the frequency, visibility and duration of dust events. • Changes in NDVI did not synchronize with precipitation. • Implementation of the GGW program was observed to have improved vegetation density. • NDVI variable had a close negative relationship with DSI measurements. Abstract China launched its “Green Great Wall” (GGW) program in 1978. However, the effects of this program are subject to intense debate. This study compares changes in the vegetation index in regions where the GGW program has been implemented with those where it has not. Subsequently, a definition to measure dust storm intensity (DSI) was proposed that better calculates the intensity of dust events; it considers the frequency, visibility, and duration of dust events. The results show that in the GGW region, vegetation has greatly improved, while it varied dramatically outside the GGW region. In the mid-1980s, DSI decreased significantly, different from the changes in dust storm frequency in the study region. By discounting the effects of climatic change and human pressures, the results show that the GGW program greatly improved the vegetation index and effectively reduced DSI in northern China.

AbstractMountainous areas in China account for two‐thirds of the total land area. Due to rapid urbanization, rural population emigration in China's mountainous areas is very significant. This raises the question to which degree such population emigration influences the vegetation greenness in these areas. In this study, 9,753 sample areas (each sample measured about 64 square kilometers) were randomly selected, and the influences of population emigration (population pressure change) on vegetation greenness during 2000–2010 were quantitatively expressed by the multivariate linear regression (MLR) model, using census data under the condition of controlling the natural elements such as climatic and landform factors. The results indicate that the vegetation index in the past 10 years has presented an increasing overall trend, albeit with local decrease in some regions. The combined area of the regions with improved vegetation accounted for 81.7% of the total mountainous areas in China. From 2000 to 2010, the rural population significantly decreased, with most significant decreases in the northern and central areas (17.2% and 16.8%, respectively). In China's mountainous areas and in most of the subregions, population emigration has significant impacts on vegetation change. In different subregions, population decrease differently influenced vegetation greenness, and the marginal effect of population decrease on vegetation change presented obvious differences from north to south. In the southwest, on the premise of controlling other factors, a population decrease by one unit could increase the slope of vegetation change by 16.4%; in contrast, in the southeastern, northern, northeastern, and central area, the proportion was about 15.5%, 10.6%, 9.7%, and 7.5%, respectively, for improving the trend of NDVI variation.