Expansion of Rural Settlements on High-Quality Arable Land in Tongzhou District in Beijing, China

Spatial transformation of changes in global cultivated land

The spatial transformation of cultivated land is an important element in the study of land use transformation. Analyzing the characteristics and direction of the global spatial transformation of cultivated land is of great significance in clarifying the spatial extent and quality of global cultivated land and ensuring global food security. In this context, this paper uses the global spatial data of cultivated land from 1992 to 2015 to analyze the characteristics of global cultivated land spatial transformation from the perspectives of cultivated land quantity, cultivated land landscape pattern, and cultivated land management pattern, applying the Mann-Kendall trend tests, trend analysis, landscape pattern index measures, and global rural per capita cultivated indicators. The global cultivated land area increased, followed by a decrease, during the study period; there were three distinct phases of change, with the years 1995 and 2005 as turning points. During the first phase, the global cultivated land area increased at an average annual rate of 0.19 %, in the second phase, the increase rate was 0.30 %, and in the third phase, the increase rate was -0.003 %. Based on the trend of cultivated land change during the study period, the areas with a dramatic change in cultivated land area were classified into six typical hotspot areas, involving the increase and decrease of area change in 10 different countries. The two countries with the largest increases in cultivated land area are Sweden and Brazil (24.82 % and 24.43 %, respectively), whereas Ukraine's cultivated land area decreased throughout the study period.

Farmland change and its implications in the Three River Region of Tibet during recent 20 years

Farmland is a key resource for safeguarding the regional food security and social stability, particularly in Tibet where the farmland is very limited due to its high altitude. With quick economic development during recent decades, farmland changes are great in China, and thus have been extensively studied. These studies generally focused on eastern regions, and seldom for Tibet due to the lack of good quality and available data. To this end, taking the Three River Region (TRR) as the case area, this study obtained 1 m spatial resolution farmland data for 2000 and 2018 by visual interpretation of the Google Earth high resolution satellite images, and then analyzed the farmland change, its driving factors and impact on grain production between 2000 and 2018. The results showed that farmland in the TRR decreased by 8.85% from 219.29 k ha in 2000 to 199.89 k ha in 2018, averagely reduced by 0.51% per year, mainly driven by the economic development, agricultural progress, urbanization, and population growth. The farmland losses largely occurred in urban areas and their surrounding counties due to urban land occupation, and caused the grain production reduced by 9.38%. To control the quick farmland losses and to ensure the regional food security of Tibet, it should strengthen the supervision on non-agricultural occupation of farmland and increase agricultural investment to improve the land productivity in the TRR.

Multi-Dimensional Feature Recognition and Policy Implications of Rural Human–Land Relationships in China

Rural decline has become an indisputable fact and a global issue. As a developing country, China is simultaneously facing unprecedented rapid urbanization and severe rural decline. The coordinated development of its rural human–land relationship is therefore of great significance for ensuring the country’s food security and achieving both rural revitalization and sustainable development. Yet, the related research on this complex subject has mostly focused on a single element: rural settlements. Since studies of the rural human–land relationship tend to only discuss the coordinated change in rural populations vis-à-vis rural settlement area, their degree of spatial matching and intensive utilization level of rural settlements has been largely overlooked. To rectify this imbalance, using data on rural populations and rural settlement area in counties of Shandong Province in 2009 and 2018, this paper applied the methods of per capita rural settlement area, the Theil index, and Tapio’s decoupling model to quantitatively identify the rural human–land relationship along three dimensions: intensive utilization level, spatial matching degree, and change coordination degree. The results revealed that the per capita rural settlement area in Shandong Province was as high as 212.18 m2/person in 2018, which exceeded the standard to varying degrees in all cities, having an overall geographical pattern of being high in the north and low in the south. The Theil index for all cities was small, which indicates that the spatial matching between rural population and rural settlements is high. To sum up, there are small differences in the utilization of rural settlements among cities, and their extensive utilization of rural settlements is a common phenomenon. In addition, the relationship between the changes in the rural population size and rural settlement area corresponded to a discordant state, in the form of strong negative decoupling, expansive negative decoupling, and expansive coupling; however, among them, the strong negative decoupling type was the dominant type. It is worth noting that all of these three types will exacerbate the extensive utilization of rural settlements. Accordingly, this paper proposes policies and measures, such as the paid withdrawal of rural homesteads, an expanded scope of homestead transfer, cross-regional “increasing versus decreasing balance”, classified promotion of rural revitalization, and improved village planning.

Land Use Multi-Suitability, Land Resource Scarcity and Diversity of Human Needs: A New Framework for Land Use Conflict Identification

Land use conflicts are intensifying due to the rapid urbanization and accelerated transformation of social and economic development. Accurate identification of land use conflicts is an important prerequisite for resolving land use conflicts and optimizing the spatial pattern of land use. Previous studies on land use conflict using multi-objective evaluation methods mainly focused on the suitability or competitiveness of land use, ignoring land resource scarcity and the diversity of human needs, hence reducing the accuracy of land use conflict identification. This paper proposes a new framework for land use conflict identification. Considering land use multi-suitability, land resource scarcity and the diversity of human needs, the corresponding evaluation index system was constructed, respectively, and the linear weighted sum model was used to calculate the land use conflict index. Taking Jinan as the study area, the spatial distribution characteristics of land use conflicts are accurately identified and analyzed. The results show that: (1) Land use multi-suitability in Shanghe county and Jiyang district is high, but the intensity of land use conflict is not. This indicates that land use multi-suitability is the premise and basis of land use conflict, but it is not the only determinant, which is consistent with our hypothesis. (2) Land use conflicts in Jinan were dominant by medium conflict, accounting for 43.89% of the conflicts, while strong and weak land use conflicts accounted for 25.21% and 30.90% of the conflicts, respectively. The spatial distribution of land use conflicts is obviously different, with high conflicts in the north and low conflicts in the south. Strong land use conflicts are concentrated in the urban and rural transition zones of Tianqiao, Huaiyin and Shizhong districts and in the northern parts of Licheng and Zhangqiu districts. (3) Inefficient land use and land resource waste aggravated regional land use conflicts in Licheng and Zhangqiu districts. (4) The new framework for land use conflict identification proposed in this study can accurately identify land use conflicts, providing a scientific reference and new ideas for accurate identification of land use conflicts.

Urban Features in Rural Landscape: A Case Study of the Municipality of Skawina

Events associated with growing suburbanisation and transport infrastructure lead to changes in the use of rural land reaching further and further from the central city. The present research focuses on the impact of the location of the municipality of Skawina and the functioning of its rural areas in the impact zone of Kraków. The first step to determine the transformations in the municipality of Skawina caused by the growth of Kraków and its suburban zone was to investigate the internal conditions in the municipality, such as its spatial development or functional structure, and external conditions such as its demographic transformations. Next, the development of the settlement structure in recent years and land management changes were investigated. The paper focuses on the introduction of typical urban features and functions into rural areas to identify the transformations and their dynamics. The status of the space was diagnosed by interpreting the map documentation for the administrative boundaries of the municipality of Skawina, regarding the presentation of the spatial development in 2006 and in 2014 to 2016, by verifying the existing planning documentation, and by visiting the site. The conclusions can be the basis for guidelines to protect the traditional rural and cultural landscape near Kraków.

Uncertainty Problems in Image Change Detection

Image Change Detection (ICD) methods are widely adopted to update large area land use/cover products. Uncertainty problems, however, are well known in such techniques, and a transparent assessment is necessary. In this study, a framework was proposed for evaluating binary land change utilizing remote sensing images. First, two widely adopted ICD methods were used to establish change maps. Second, binary decisions on Change (C) and Non-Change (NC) classes were reached through thresholding on change maps. Then, results were evaluated using two sampling designs: random sampling and stratified sampling. Analysis of results suggests that (1) for random sampling, with an increasing threshold on change variables, the overall accuracy increases and shows a large variance, which is highly correlated with the C omission error; and (2) comparatively, for stratified sampling, in which two strata (i.e., C and NC) were set, the overall accuracy shows a smaller variance and is highly associated with the NC commission error. The significant trends in accuracy assessments indicate the trade-offs between the C and NC classification errors in a binary decision and can present superficial or perfunctory accuracy evaluation in certain circumstances that the causes of error sources and uncertainty problems in ICD are not fully understood.