Figure 1 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
A map of the six geographical regions: East China (EC), North China (NC), Northeast China (NEC), Northwest China (NWC), South Central China (SCC), and Southwest China (SWC). The map represents the spatial distribution pattern of nationwide cropland and urban area in China in 2015. The cropland and urban data were provided by Natural Resources and Environment Center, Chinese Academy of Sciences (http://www.resdc.cn/Default.aspx).
Source publication
It is crucial to assess the effects of urban expansion on croplands to allow sustainable urbanization and cropland supply. However, owing to the complexity of land conversion and various land policies in China, it is difficult to quantify the cropland dynamics and implications of urban expansion throughout the whole accelerated stage of urbanizatio...
Contexts in source publication
Context 1
... regions have been used to analyze various aspects of regional characteristics, including land use change and its impacts [22]. In this study, to focus on our study object, only pixels depicting croplands and urban areas in the years 1990, 1995, 2000, 2005, 2010, and 2015 were selected (Figure 1). ...
Context 2
... regions have been used to analyze various aspects of regional characteristics, including land use change and its impacts [22]. In this study, to focus on our study object, only pixels depicting croplands and urban areas in the years 1990, 1995, 2000, 2005, 2010, and 2015 were selected ( Figure 1). ...
Context 3
... two maximum regions were NWC and SWC, with area proportions of 30.9% and 25.4%, respectively. The two minimum regions were EC and NEC, with area proportions of 9.0% and 7.9%, respectively ( Figure 1). Because the original areas and geographical conditions are different in the six regions, the cropland area over the study period followed the order (from greatest to least): EC > SCC > NEC > NC > SWC > NWC, but the maximum amounts of variation in cropland area appeared in NEC ( Figure 3). ...
Context 4
... two maximum regions were NWC and SWC, with area proportions of 30.9% and 25.4%, respectively. The two minimum regions were EC and NEC, with area proportions of 9.0% and 7.9%, respectively ( Figure 1). Because the original areas and geographical conditions are different in the six regions, the cropland area over the study period followed the order (from greatest to least): EC > SCC > NEC > NC > SWC > NWC, but the maximum amounts of variation in cropland area appeared in NEC ( Figure 3). ...
Similar publications
Land, nature, and the social environment in contiguous poor regions are harsh and difficult to change. The poor adaptive capacities of the socio-ecological systems of these regions are the main causes of deep, persistent poverty. In February 2016, the Chinese government issued a policy proposing to promote poverty alleviation by relocation (PAR) by...
Citations
... As delineated in earlier chapters, cities within advanced economies underwent expansion under diverse economic conditions, resulting in a myriad of development trajectories . The spatial heterogeneity observed in contemporary urbanization justifies the application of quantitative approaches to identify novel relationships between form and function (Li et al., 2019). Transitioning toward a land-use perspective that centers on settlement structure, Chapter 4 introduces a quantitative approach that measures settlement compactness (or dispersion) based on the density of detached buildings in the total stock. ...
... The encroachment of low-density settlements into cropland and forests raises critical questions about sustainability and land-use planning (Theobald, 2001;Bren d'Amour et al., 2016;Cui et al., 2019). The transformation of natural landscapes into a mixed urban fabric underscores the complex interplay between human settlements and the environment (Piña and Martínez, 2014;Rees and Wackernagel, 2014). ...
Departing from conventional narratives centered on economic stagnation and social secularism, this book offers a fresh perspective on Mediterranean urbanities. It posits their correlation with housing and welfare regimes, societal transformations, local governance structures, and deficiencies in spatial planning. The analysis within delves into the neglected potential for mitigating regional disparities, conducting a meticulous examination of environmental disparities, economic imbalances, and overarching social inequalities in Southern European regions. The outcome aims to furnish an integrated, and potentially holistic, understanding of spatial divisions between cities and their surrounding territories.
... (Theobald, 2001;Bren d'Amour et al., 2016;Cui et al., 2019). The transformation of natural landscapes into a mixed urban fabric underscores the complex interplay between human settlements and the environment (Piña and Martínez, 2014;Rees and Wackernagel, 2014). ...
... According to the Chinese construction statistics yearbooks, the urban land in mainland China increased eight folds from nearly 7000 km 2 to over 58,000 km 2 , between 1978 and 2020. Urban expansion in China will accelerate in the coming years, with the projection of urban land probably reaching over 80,000 km 2 by 2030 (Cui et al., 2019). Excessive expansion of urban land has led to certain issues including regional incoordination, destruction of urban nature, air pollution, and natural ecosystem degradation, which lower the urban land use efficiency and constrain urban sustainability (Chen et al., 2018;Liu et al., 2020;Peng et al., 2021;Song et al., 2022). ...
Green development is essential for improving urban land use efficiency (ULUE) as it seeks to optimize resource utilization and minimize waste and pollution. However, a long-term evolution of ULUE and its determinants under the context of green development are less discussed in existing studies. Drawing on remote sensing and statistical data and utilizing the super efficiency slack-based model (SBM) and the geographically and temporally weighted regression (GTWR) model, this study evaluates green development-oriented ULUE and its spatiotemporal associations with determinants across 284 cities and eight economic zones in China from 2005 to 2019. We found that the green development-oriented ULUE in China generally increased in 15 years (from 0.404 to 0.55), with higher levels in coastal and northwestern regions than in central regions. Besides, per capita GDP, investment in technology and science, and degree of openness generally contributed to ULUE (over 75% observations showed positive coefficients), while investment in real estate had a negative impact on ULUE. The impact of industrial structure on ULUE experienced a transition from positive to negative in northern and eastern cities, with the highest coefficient decreasing from 0.194 in 2005 to −0.032 in 2019. Population density contributed to ULUE in southern and northwestern cities during 2005–2010 (coefficients ranging from 0.008 to 0.198), while it negatively influenced ULUE in most cities since 2015 (coefficients ranging from −0.009 to −0.283). The correlation between nighttime light, per capita road, and ULUE showed noticeable south-north differentiation. Our study provides valuable guidelines for Tailor-made strategies of efficient urban management towards sustainable urbanization.
... Socioeconomic data include GDP, population density, land rent and transport accessibility data. The grid data of GDP spatial distribution kilometers network [39], and the raster data of population spatial distribution [40] are from the Center for Resource and Environmental Science and Data of the Chinese Academy of Sciences. The ground rent data comes from Tuliu.com, and the traffic accessibility data comes from the Carbon Cycle Room of the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (CAS) [41]. ...
Urban agriculture provides a new strategic idea for solving the problem of urban food demand. The main objective of this study is to develop a spatial model for land suitability evaluation of urban agricultural development under different investment demands (urban agriculture 1.0 and 2.0), based on prospect theory and using GIS and TOPSIS analysis techniques. As a whole, we have developed a land suitability evaluation system for urban agricultural development under different investment needs (urban agriculture 1.0 and 2.0). We constructed a land suitability evaluation system for urban agriculture including ecological environment, social demand and investment cost. The results of the land suitability analysis for urban agriculture 1.0 show that the most suitable area is located in Changle. Compared with urban agriculture 1.0, the most suitable area for urban agriculture 2.0 is in Gulou. It is worth noting that Cangshan ranks second in both scenarios and can be used as a potential solution to balance the ecological environment, social demand and investment cost. Determining appropriate land suitability priorities for urban agriculture will facilitate future agricultural investment management and land use planning.
... Since LUCC research has received extensive attention, a variety of LUCC research methods have been proposed in previous studies. For example, basic statistics have been used often to analyze the structural composition of land use in a given year, and comprehensive land use indicators have been proposed to evaluate the intensity of land development and use within a study area [11]. Furthermore, to compare changes in land use structure in different years, the concepts of land use dynamics and two-way change dynamics of land use have been proposed [12,13]. ...
The processes of land use and cover change (LUCC) are highly diverse and complex, being heavily influenced by natural factors, economic factors, and other related factors. These changes have a significant impact on ecological environments and landscapes, and serve as a reflection of human activity, limited by natural factors. As a result, LUCC has been widely studied across multiple scientific disciplines. In particular, considerable progress has been made with regard to traditional methods of analyzing land use structures, which focus on the overall differences in the land use structure in each spatiotemporal snapshot. However, these methods have overlooked the continuity in the evolution of each land use unit between different snapshots, impeding the development of a comprehensive model for the spatiotemporal evolution of land use processes. In this work, land use change process (LUCP)—constructed using multiple land use data points from different points in time—was employed as the basis to develop a method to measure the spatiotemporal distance between irregular land patches in evolution sequences based on LUCP. Furthermore, the spatiotemporal distribution model was analyzed using Monte Carlo simulation and measurements of the shortest spatiotemporal distance of LUCP. This work employs land use data for Huainan in China, a typical coal resource city, from 2008 to 2017 for an empirical study. A typical kind of spatiotemporal evolution of LUCP (evolution from farmland to grassland within any two years) is evaluated. Taking into account the shape of land use units, the spatiotemporal distances between irregular evolutionary sequences are measured using buffer-based superposition. The results show that the expected mean nearest neighbor distance for the irregularly evolving sequence of land use units is 0.085 in the completely random CSR model, whereas the mean nearest neighbor distance is 0.037 in the real observation model. These results indicate that such LUCPs have generally shown a spatiotemporal aggregation pattern over the past 10 years. However, since the z-score is 1.03, which is in the range of −1.65 to 1.65, this aggregation pattern is not statistically significant. These experiments demonstrate the validity of using the method proposed herein to study similar problems. The results of this work provide valuable insight into the spatiotemporal evolution process of land use units, which could be instrumental in exploring the potential spatiotemporal model of LUCP evolution.
... About 13.36% of the earth's surface is composed of deserts, including the Gobi Desert [1][2][3][4]. Northwest China is a large region with a wealth of untapped resources in uncultivated soil. Xingjiang belongs to the temperate continental climate, the temperature difference between day and night is large, but the sunshine time is sufficient, with little precipitation, and dry climate. ...
This study aims to provide information and theoretical support for the development planning of facility agriculture in desert areas. Using sensor monitoring, USB cable, and computer connection record, we measured the temperature, humidity, and heat transfer distribution of ordinary brick wall greenhouse (G1), composite wall greenhouse (G2), and assembled solar greenhouse (G3) in the Aksu desert area of Xinjiang. The results showed that G3 had the highest average temperature among the three types of greenhouses in the cold season; no difference was detected between G1 and G2 in the night temperature, while G3 has the characteristics of fast heating and cooling. On a sunny day, the heating rate of G1, G2, and G3 is 3.62, 4.4, and 4.77 °C/h, respectively. The cooling rate for G1 is 2.66 °C/h; 2.96 °C/h for G2; and 3.93 °C/h for G3. The heating rate for each greenhouse is nearly identical when it is cloudy outside, and the cooling rate of G1, G2, and G3 is 2.71, 4.2, and 4.34 °C/h, respectively. Moreover, the G3 north wall’s thermal insulation performance has clear advantages. Its wall surface can reach a temperature of 59.1 °C (G1 is 42.7 °C and G2 is 41.6 °C). This study showed that G3 possesses the virtues of effective thermal insulation; the rear wall has a small footprint and preserves the arable land; it also achieves the necessary environmental conditions for crop growth without the use of auxiliary heating.
... To address issues such as protecting forest ecosystems while increasing food production in sustainable development, achieving a transition to more environmentally friendly and sustainable land use, and formulating policies that coordinate development with nature protection [6,7], it is necessary to master the use of land resources and data regarding their change. As an important artificial landscape type, the utilization expansion, abandonment, and conversion of cropland with other types will change both the material flow and energy flow of the cultivated land, affecting the Earth system's climate, hydrology, biological cycle, and other global change processes [8][9][10][11]. Therefore, in the context of the continuously increasing world population, the decrease in per capita cropland, and the great challenge of food security, it is of great significance to quickly grasp the quantity, spatial distribution, and spatiotemporal characteristics of the existing cropland resources for the study of sustainable development, global environmental change, and strategic decisions regarding food security internationalization [12][13][14][15]. ...
Cropland cover datasets is of great significance for research on agricultural monitoring. The existing investigations on the inconsistency of different cropland datasets have mainly focused on first-class cropland and only analyzed the causes of this inconsistency in terms of cartography. To date, investigations have neglected the importance of fine cropland types in studies such as global food security assessment, and a comprehensive analysis of the causes of inconsistency from the perspectives of both cartography and geography is lacking. Moreover, the verification samples of existing studies have primarily been collected based on Google Earth. So, we examined the cropland resources of Cambodia using areal, spatial consistency, elevation classification, and field survey data assessment methods for the Global Food Security-support Analysis Data at 30 m for Southeast Asia, Global Land Cover Fine Surface Cover30-2015, Finer Resolution Observation and Monitoring of Global Land Cover2015, and SERVIR-Mekong datasets and comprehensively investigated the causes of inconsistency in terms of geography and cartography. The results revealed that the consistency of the extracted areas of first-class cropland among the four datasets was high. But, the cropland areas and statistical results from the Food and Agriculture Organization (FAO) of the United Nations are quite different. The overall accuracy (OA) for the first-class cropland of GFSAD30SEACE, GLC_FCS30-2015, and SERVIR-Mekong datasets were >82%. For fine cropland types, however, the OA of the SERVIR-Mekong dataset was relatively high, at 74.87%, while the accuracy levels of the global-scale GLC_FCS30-2015 and FROM_GLC2015 datasets were
... Following a once-and-for-all upheaval in Chinese history -nationalized land ownership in the early 1950s-the current regime has successfully carried out a series of social and political campaigns to convert an agricultural country into a modern industrialized nation. Unfortunately, such effort has been at the cost of depleting natural resources, land conversion, and environmental contamination by applying a nature resource-and-carbon extensive emission developmental model, driven by the policy of establishing a world manufactory for the goods labeled Made in China (Cui et al., 2019;Li, 2018;Pan et al., 2016). ...
Evolutionary and historical development and current profiles are essential to generating a tangible conservation strategy. It also is critical to distinguish the regions with vigorous potential growth from those meeting evolutionary development bottlenecks and those whose development has been severely devastated. We used two sizeable national data repositories of terrestrial fauna and flora of China to approach the issues. The results indicate that the Southwest and Coastal regions have the most significant terrestrial faunal-floral biodiversity (TFFB). Thus, they should be prioritized in conservation for great potential promotions. Although there has been remarkable evolutionary development, Central has severely been devastated. A solution is to uphold a balanced association between social-economic development and TFFB sustainability. As for the Northeast and the western Northwest, there is no need to invest heavily in conservation measures. This study sheds light on exploring more practical conservation strategies regionally, nationally, and globally to achieve pragmatic goals.
... The cropland cover type is the basis for the survival of human society, and its utilization state, spatial distribution, and dynamic change have an important impact on economic development and climate change [1][2][3][4]. At present, with a large population in the world, food security will face great challenges. ...
Information on the area and spatial distribution of cropland resources is very important for agricultural monitoring and sustainable development. The existing evaluation and analysis of cropland resources mainly focus on the first-class cropland types, and the spatial resolution of cropland cover products studied is low (<30 m), which cannot meet the needs of food security assessment and sustainable analysis of cropland resources. Therefore, in this paper, four published cropland cover products with a spatial resolution of 30 m (GFSAD30SEACE, GLC_FCS30-2015, FROM-GLC2015, and SERVIR MEKONG) are evaluated for consistency and accuracy through area validation, comparison of spatial pattern distribution, and fieldwork data. The results showed that (1) the area and spatial pattern of the four first-class cropland cover types were consistent, especially the GFSAD30SEACE product. However, the area and spatial consistency among different products decreased significantly for the finer type of secondary cropland cover, and the area percentage of rice field was only 3.03%. (2) The spatial inconsistency areas of cultivated land for the four products have different distribution rules under different topographic factors, mainly distributed in the range of elevation (<300 m), slope (2°-15°), and topographic relief (0-10 m). (3) The GFSAD30SEACE product had the highest overall accuracy of 88.33% for the primary type of cropland cover. The overall accuracy was lower for all secondary types of cropland cover, with the SERVIR MEKONG product having the highest overall accuracy (71.64%) and the other products having an overall accuracy of less than 62%. Therefore, future land cover mapping of cropland needs to focus on technical solutions for the classification of fine cropland types.
... The land use data of 30 m spatial resolution in 2000, 2005, 2010 and 2015 were collected from Center for Resource and Environmental Science Data, Chinese Academy of Sciences (https://www.resdc.cn/). This dataset included 6 primary types and 25 subclasses of land use, and the overall accuracy of secondary classification was more than 90% Cui et al., 2019). Considering the modelling efficiency and information richness, those land use maps were resampled to 100 m × 100 m by utilizing bilinear interpolation. ...
Water scarcity greatly hinders sustainable development goal agenda and regional agriculture development in dryland regions. As we know, land use and cover changes are strongly responsible for spatial-temporal evolutions of water resource. However, there is little explicit understanding of how spatial patterns of future dryland use will affect the water supply-demand risk. To answer this question, this study took Yulin city of China, a typical dryland region, as a case study area, and firstly estimated its 2020-2050 land use patterns under three different scenarios, covering Natural Increased Scenario (NIS), Food Security Scenario (FSS) and Economic Development Scenario (EDS), with the help of the path-generating land use simulation (PLUS) model as well as Markov-chain model. Furthermore, this study employed InVEST model to explicitly investigate spatial-temporal evolutions of water supply, water demand and water supply-demand risk in all scenarios. The estimated results indicated that the largest expanding/shrinking land use types were grasslands/croplands in NIS, croplands/grasslands in FSS and built-up lands/croplands in EDS during 2020-2050, respectively. By 2050, all projected land use changes only slightly affected regional water supply (the fluctuation of ∼5% compared to that in 2020), but greatly increased by ∼57% regional water demand. Particularly, strong land use changes would likely put nearly 90% regions of Yulin city at endangered water supply-demand risk in 2020-2050. Ecological land and built-up land would easier suffer from critically endangered water supply-demand risk. In view of these modeled and analyzed results, some potential mitigation strategies of water resource utilization, such as developing water-efficient eco-agriculture, adjusting agricultural structures and enriching revegetation diversity, were suggested to coordinate future areal human-nature relationships. This study could provide some valuable information for dryland agricultural development, water-environment management and regional policy decision-making.
