Chengdu has experienced a rapid urbanization in the past two decades, and its land spatial pattern has undergone severe changes. It’s meaningful to investigate the tempo-spatial evolution of land spatial pattern and then contribute to high-quality development in Chengdu. Based on the Landsat-series satellite imagery and land use/cover datasets, this paper investigates Chengdu’s land function change concerning Production, Living and Ecological (PLE) land. The methods of land dynamics degree, landscape pattern index and Pearson correlation were be employed to analyzes the tempo-spatial evolution of landscape pattern in Chengdu, and some suggestions were finally made. We found that there were severe dynamic degree of PLE land in Chengdu and the production and ecological land were decrease obviously before 2015. Contrastingly, the dynamic degree is decrease after 2015, high dynamic degree regions are move to the northeast from 2000-2019. In addition, the change of production land is the main factor affecting the landscape pattern of Chengdu. In general, we put forward the macroscopic strategy and suggestions of “one core, two belts, four regions, and one direction” to support the high-quality development of Chengdu.

The entire land of Southern Iran faces problems arising out of various types of land degradation of which vegetation degradation forms one of the major types. The Qareh Aghaj basin (1 265 000 ha), which covers the upper reaches of Mond River, has been chosen for a test risk assessment of this type. The different kinds of data for indicators of vegetation degradation were gathered from the records and published reports of the governmental offices of Iran. A new model has been developed for assessing the risk of vegetation degradation. Taking into consideration nine indicators of vegetation degradation the model identifies areas with “Potential Risk” (risky zones) and areas of “Actual Risk” as well as projects the probability of the worse degradation in future. The preparation of risk maps based on the GIS analysis of these indicators will be helpful for prioritizing the areas to initiate remedial measures. By fixing the thresholds of severity classes of the nine indicators a hazard map for each indicator was first prepared in GIS. The risk classes were defined on the basis of risk scores arrived at by assigning the appropriate attributes to the indicators and the risk map was prepared by overlaying nine hazard maps in the GIS. Areas under actual risk have been found to be widespread (78%) in the basin and when the risk map classified into subclasses of potential risk with different probability levels the model projects a statistical picture of the risk of vegetation degradation.

To study the mechanism by which the thickness of covering soil effects crop growth in an ecological restoration project of bare rock and gravel land, the physiological characteristics of summer maize were observed during 2010-2015. This experiment was set up on exposed rock land, which had been covered by soil with six different thicknesses: 30 (C30), 40 (C40), 50 (C50), 60 (C60), 80 (C80) and 100 cm (C100). During the experiment, soil physical properties and the physiological traits and yields of crops were recorded. The results indicated several effects. 1) With the same thickness level, soil bulk density of the covering soil increased in successive planting years. There was a logarithmic relationship between soil bulk density and covering thickness. There was also a strong algorithmic relationship between covering thickness and sedimentation coefficient (R²=0.91). 2) The thickness of covering soil had a significant influence on both the height of summer maize, and soil and plant analyzer development (SPAD) values. In each treatment, the growth rates of the crops during the jointing and booting stages were higher than that in the booting to grain filling stage. After two years of land-use, the mean height of the crop in the C50 treatment was 8.16%, 3.32%, 3.31%, 9.86% and 7.55% higher than that for the C30, C40, C60, C80 and C100 treatments, respectively. The differences between treatments were significant (p < 0.05). SPAD values were highest at the heading stage. The highest value for the C50 treatment was 298.41 after two years of land-use. 3) Soil thickness significantly affected yields and the water use efficiency (WUE) of summer maize. The highest average crop yield and WUE value during the experimental period for the C50 treatment were 4614.12 kg hm^-2 and 13.57 kg hm^-2 mm, respectively. For the C50 treatment the multi-year average water use efficiency was significantly higher than that of the other treatments in 2010-2015. In conclusion, a soil thickness of 50 cm covering the bare exposed rock was adequate as a tillage layer for the crop, and all crop growth indexes in this treatment were better than for other soil thicknesses. The results provide a scientific basis for the land remediation and ecological restoration of bare rock and gravel land. At the same time, for Africa, where one-third of the land is desert, arable land resources are relatively scarce and agricultural ecology is fragile, can serve as a significant reference to improve the ecological environment, develop arable land resources and increase agricultural income.

This study aimed to explore whether reductive soil disinfestation (RSD) is an effective method of controlling continuous cropping obstacle of watermelon. Samples of watermelon continuous cropping soils were treated by RSD in laboratory tests and pot experiments in August 2015 and from December 10, 2016 to April 10, 2017. The soil samples for the laboratory test were divided into 16 groups, and each group comprised three parallel samples of 100 g (dry soil weight). Except for the original and control (CK) samples, the 14 other groups of soil samples were treated with different combinations of 1% or 3% alfalfa powder, 1% or 3% ammonia (NH₃) water, and 1% or 3% acetic acid. The soil samples were placed inside size-five self-styled plastic bags and incubated in a constant-temperature biochemical incubator at 35°C for 14 days after blending, flooding, and sealing. Seven groups of soil samples were designed for the pot experiments based on the laboratory test results. Each group consisted of 30 parallel samples of 3 kg (dry soil weight). These samples were incubated outdoors for 4 months after mixing with alfalfa powder and/or NH₃ and/or acetic acid according to the experimental design, blending, flooding, and sealing. Watermelon seedlings were planted in the air-dried soil samples from May to July in 2017. The results showed that the pH of the soil samples treated by RSD were elevated except for those samples with acetic acid. In addition, the electrical conductivities of the soil samples treated by RSD were effectively adjusted. The presence of soil-borne pathogenic Fusarium oxysporum f.sp. niveum was significantly suppressed (p < 0.05) in soil samples treated by RSD, and the incidence and mortality rate of watermelons planted in these samples were remarkably lower than those planted in the CK and flooded CK soil samples. Therefore, continuous cropping obstacle of watermelon can be controlled by RSD.

As an important part of resource and environment carrying capacity (RECC), land resource carrying capacity (LRCC) has focused on the limiting factors on regional development from the scale of land resources for more than two hundred years. After a brief review of the origin and early development of LRCC, the progress of LRCC is summarized as a progression from land resource population carrying capacity (LPCC) to land resource comprehensive carrying capacity (LCCC), and the hot issues of LRCC have changed from the simple human-grain relationship to more complex social and economic activities-land resources relationships. The corresponding research methods also evolved, from static research to dynamic research, and the assessment factor have evolved from a single factor to a comprehensive index system. Agro-ecological zoning (AEZ), system dynamics (SD), ecological footprint (EF), and comprehensive evaluation methods have come to be viewed as the most representative methods of LRCC in recent years. As a focus of conventional LRCC research, the human-grain relationship still plays a significant role in LRCC evaluation because grain remains the top limiting factor of land resources and is the most significant criterion in the balance between regional population and land resources, especially for very populous countries. More attention should be paid to the accurate calculation of arable land and average food consumption levels to improve the scientific basis of LRCC evaluation. The development of science and technology and the variation of lifestyle are also important factors that influence regional LRCC. As a new topic of LRCC, LCCC has expanded the research field of LRCC in an attempt to reveal the limiting effects of land resource under open systems, but some issues such as carrying mechanism research and the combination of theoretical and applied research are needed in future studies to promote the further development of LCCC.

Spatial differentiation in forest transition was measured in terms of space transition and function transition using the exploratory spatial data analysis method (ESDA) and data from 2004—2014 for Zunyi city, Guizhou province, China. The validity of factors affecting forest transition was analyzed by constructing radial basis function neural networks (RBFNN) based on the data processing system (DPS). Our results will provide references for scientific understanding of the potential mechanism underlying forest transition in mountainous areas. We found that Global Moran’s I of space transition and function transition of forest land was 0.0336 and 0.2323, respectively. This suggests a significant positive correlation in spatial distribution of space transition and function transition of forest land, and significant spatial aggregation. The Global Moran’s I of function transition was higher than that of space transition, and the spatial aggregation characteristics of function transition were more significant than for space transition. The Global Moran’s I at each time period tended to increase, and the spatial aggregation degree of the function transition and space transition was further enhanced. Hot and cold spots of space transition of forest land stably evolved, suggesting a minor spatial difference in forest land among different administrative units at the county level. The number of hot spots at the county level in function transition increased. Hot spots were intensively distributed at the western edge and continuously distributed in the northeast. The space transition and function transition of forest land were both greatly influenced by urbanization rate and second and third industries. The development of urbanization and industrialization was the main factor driving forest transition, suggesting a positive role of economic growth on forest transition in mountainous areas. The development of urbanization and industrialization is an effective approach to forest transition in mountainous areas.

Small-scale household agricultural production has been in conflict with China’s agricultural modernization. In the context of vigorously promoting rural land circulation and moderate scale management nationwide, research on the relationship between farm size and scale efficiency has become increasingly important. In this paper, we use the “DEA-OLS” two stage method to analyze data from 368 surveys of rice farming households in the Jianghan Plain. The scale efficiency of rice farming was calculated, and the relationship between farm size and scale efficiency investigated. The results indicate that (1) the rice farm size is generally small in Jianghan Plain, with an average of 0.77 ha. The average scale efficiency is 0.88, and it is the main factor limiting an increase in comprehensive technical efficiency. Moreover, 88.32% of households are in the stage of increasing returns to scale. (2) There is a stable inverted “U” type relationship between rice farm size and scale efficiency. Considering characteristics of the householder, the household and land quality, the maximum scale efficiency corresponds to a household with 5 ha of rice farm. (3) Among householder characteristics, age has a significant negative influence on scale efficiency, and scale efficiency is lower for a household whose householder is engaged in non-farm work than for one whose householder is devoted to farming. As for land quality, there was a significant positive effect of irrigation on scale efficiency. Among family characteristics, the application of a machine during the seeding process increased scale efficiency by 3.07%. Therefore, we suggest that local government should actively promote rural land circulation, implement a staged-scale management subsidy, and other forms of support for the purchase of agricultural machinery and technical popularization. Increased investment in irrigation improvements and mechanical facilities and encouragement of farmers to enlarge their farm size could improve scale efficiency and farming profit and lead to the development of moderate scale management.

This paper analyzes panel data from 2003-2012 to identify the factors driving the expansion of construction land in Ningbo city; it uses panel data, regional-level, and year-by-year regression models. The results indicate the following: (1) For each 1% increase in the size of the economy, urban population, and industrial structure adjustment coefficient, the amount of construction land increased by 0.35%, 0.52% and -1%, respectively. (2) The factors driving the expansion of urban construction land differed across regions. In more highly developed areas such as Yuyao, Cixi, Fenghua and the downtown area, population growth was the most obvious driving factor with coefficients of 4.880, 1.383, 3.036 and 0.583, respectively, in those areas. Here, the impact of industrial structure adjustment was lower than that of population growth (with coefficients of 1.235, 0.307, 0.145 and -0.242), while economic development was an increasingly insignificant factor (with coefficients of -0.302, 0.071, 0.037 and 0.297). On the other hand, economic development was the most important factor for the expansion of construction land in relatively less developed areas such as Xiangshan and Ninghai counties with coefficients of 0.413 and 0.195, respectively. Here, population growth (with coefficients of -0.538 and 0.132) and industrial structure adjustment (with coefficients of -0.097 and 0.067) were comparatively weaker driving factors. (3) The results of the year-by-year regression indicate the increased impact of economic development as a driving factor (from -1.531 in 2005 to 1.459 in 2012). The influence of the population growth factor slowly declined (from 1.249 in 2005 to 0.044 in 2012) and from 2009 on was less influential than the economic development factor. The industrial structure coefficient remained negative and its influence diminished from year to year (from -5.312 in 2004 to -0.589 in 2012).

China announced plans on April 1, 2017 to create Xiong’an New Area, a new economic zone about 110 km southwest of Beijing. The new area of national significance covers the three counties of Xiongxian, Rongcheng and Anxin in Hebei Province, and is home to Baiyangdian, a major wetland in northern China. It will cover around 100 km² initially (called “Starting Zone”) and will be expanded to 200 km² in the mid-term and about 2000 km² in the long term. In this context, it is important to assess the land use pattern for the new area’s planning and development. Based on remote sensing interpretation of Landsat OLI images, we examine the current land use features, the potential for built-up land saving and intensive use, and the spatial variation of arable land quality. The results indicate that the arable lands, built-up lands and wetlands account for around 60%, 20% and 10%, respectively. The potential for rural built-up land saving and intensive use is quite large. The arable land quality and use intensity in Rongcheng and Anxin counties are much better than that of Xiongxian. The pros and cons for three potential options for the Starting Zone are listed and compared. The eastern area of Rongcheng county, to the north of Baiyangdian, is believed to be the most suitable Starting Zone. Policy recommendations for built-up land expansion, farmland saving and flood risk mitigation for Xiong’an New Area are also proposed in this paper.