Regularity of rural settlement changes driven by rapid urbanization in North China over the three decades

Unequal impacts of global urban-rural settlement construction on cropland and production over the past three decades

The world has experienced a rapid expansion of human settlements in both urban and rural areas in recent decades, yet the unequal impacts of this construction on global food security remain unclear. In this study, we delineated the global-scale expansion of urban-rural settlements at a fine resolution from 1985 to 2020 and quantified their uneven impacts on food security, focusing on the relationships between settlement types, cropland categories, and disparities in crop production. Our results showed that despite dramatic urbanization, rural settlements still constituted the majority of human settlement areas in 2020. Globally, cropland loss due to the expansion of rural settlements was 1.2 times greater than that caused by urbanization, while the associated yield loss was 1.5 times higher. Notably, urban-rural settlement expansion in Asia accounted for 61% of cropland loss and 64% of yield loss. Moreover, future scenarios predicted that Asia's urban-rural settlement expansion will continue to have the most significant impacts on the loss of cropland and yield throughout the 2030s. These results provide systematic evidence of the unequal impacts of urban-rural settlement construction on global cropland and food security.

Optimizing land use spatial patterns to balance urban development and resource-environmental constraints: A case study of China's Central Plains Urban Agglomeration

The unprecedented urbanization of the Central Plains Urban Agglomeration (CPUA) has significantly improved human well-being but has also led to severe land degradation and environmental challenges. Spatial zoning is a crucial tool for advancing sustainable land management in urban agglomerations. However, spatial zoning has become increasingly challenging due to the diversity associated with future land-use changes and the vulnerability of the ecological environment. This study applies a Self-Organizing Map (SOM) neural network model to emphasize the dual pivotal role of future land-use scenarios and resource-environment carrying capacity in optimizing sustainable land management zoning. Focusing on the CPUA in China, the study reveals several key findings: (1) Under the natural evolution scenario, the proportion of cultivated land decreases from 58.76 % to 55.58 %, resulting in a reduction of 9146 km2, while construction land expands from 14.72 % to 21.96 %, with an increase of 23,100 km2 and an average annual growth rate of 1.17 %. (2) The resource-environment carrying capacity across the CPUA is generally low to medium, with an average index value of 35.28. Spatially, the surrounding areas concentrate higher carrying capacity, while the central regions exhibit lower values. The western, northern, and southern edge regions show relatively higher capacities. (3) Based on comprehensive assessments of land-use patterns, ecological quality, and resource-environment carrying capacity, the CPUA is divided into nine distinct sustainable land management zones. Each zone requires tailored strategies that consider its specific resource endowments, ecological conditions, agricultural productivity, and urban development potential. Coordinated infrastructure development and resource-sharing initiatives are essential for promoting sustainable land management throughout the urban agglomeration. The proposed zoning optimization strategy strikes a balance between urban development demands and resource-environment constraints, offering a practical framework for refining land management policies and advancing sustainable development goals in large urban agglomerations.

Global urban and rural settlement dataset from 2000 to 2020

Accurate mapping of global urban and rural settlements is crucial for understanding their distinct expansion patterns and ecological impacts. However, existing global datasets focus mainly on urban settlements and ignore the delineation of rural settlements. Therefore, this study proposed a framework for delineating between urban and rural settlements based on dynamic thresholds defined by area and light brightness and constructed the first global 100-meter resolution urban and rural settlements dataset (GURS) spanning from 2000 to 2020, integrating GHS-BUILT-S R2023A, NPP-VIIRS-like nighttime light, and OpenStreetMap data. An accuracy assessment of 44,474 independent samples showed that GURS achieved an overall accuracy of 91.22% with a kappa coefficient of 0.85, outperforming nine multi-scale reference datasets in delineating global urban and rural settlements. GURS offers deep insights into the dynamics of global settlements, facilitating urban-rural comparative studies on socio-economic characteristics, environmental impacts, and governance modes, thereby enhancing the sustainable management of settlements.

Human-earth system dynamics in China's land use pattern transformation amidst climate fluctuations and human activities

Amid rapid environmental changes, the interplay between climate change and human activity is reshaping land use, emphasizing the significance of human-earth system dynamics. This study, rooted in human-earth system theory, explores the complex relationships between land use patterns, climate change, and human activities across China from 1996 to 2022. Using a comprehensive analytical framework that combines Geographical Detector (GeoDetector), Random Forest (RF) model, Data Envelopment Analysis (DEA), Spearman's rank correlation, and k-means clustering, we analyzed data from national land surveys, climate records, and nighttime light observations. Our findings indicate a significant, though regionally varied, transformation in land use: arable land decreased by 1.67 %, driven by intense urbanization and policy shifts, particularly in rapidly urbanizing Jiangsu province where arable land diminished by 19.19 %. In contrast, construction land in the northern regions increased by 225.91 million hectares. Climatic influences are apparent, with rising temperatures positively correlating with arable land expansion in the Northeast and Northwest, and urban land in Jiangsu province increasing by 35.51 %. Variations in precipitation patterns were linked to changes in forested areas. This study highlights the dynamic and intricate interactions within the human-earth system, stressing the urgent need for sustainable land management and climate adaptation strategies that improve land use efficiency and resilience. Our research offers a solid foundation for informed policy-making in land management and climate adaptation, advocating a human-earth system science approach to address future environmental and societal challenges.

Exploring the evolution of ecosystem health and sustainable zoning: A perspective based on the contributions of climate change and human activities

Maintaining ecosystem health (EH) in watersheds is crucial for building a national pattern of ecological security. However, a comprehensive diagnosis of watershed EH and an exploration of its driving mechanisms are still lacking. This study proposed an EH assessment model from a vitality-organization-resilience-service-environment (VORSE) perspective. Taking the Yellow River Basin of Shaanxi Province (YRBS), China, as a research object, the spatiotemporal evolution trend of EH from 2000 to 2020 was quantified. At the same time, we also quantified the respective contributions of climate change (CC) and human activities (HA) to the EH dynamics based on residual analysis. The results showed that EH in the YRBS increased by 11.80 % from 2000 to 2020, and the spatial distribution of the EH was higher in the southern region than in the northern part. At the pixel scale, areas with improving trends accounted for 90.57 % of the YRBS, while 9.43 % deteriorated, with the improving areas mainly in northern Shaanxi and the deteriorating areas in the Guanzhong region. The correlation between the EH and precipitation was primarily positive, while the correlation between the EH and temperature was mainly negative. The residual analysis showed that the contribution rate of CC to EH changes was 78.54 %, while that of HA was 21.46 %, indicating that CC was the dominant driver of EH changes in the YRBS. Specifically, 82.64 % of the improvement in EH was attributed to CC and 17.36 % to HA. Conversely, 65.30 % of the deterioration in EH was attributed to CC and 34.70 % to HA. Furthermore, CC, HA, and CC&HA dominated EH changes in 26.85 %, 3.77 %, and 69.38 % of the YRBS area, respectively. In addition, the Hurst exponent analysis identified six types of future EH development scenarios, each requiring different restoration strategies. This study provides valuable insights for future EH diagnosis, EH restoration efforts, and the formulation of sustainable development goals in other watersheds.

Perceptible landscape patterns reveal invisible socioeconomic profiles of cities

Urban landscape is directly perceived by residents and is a significant symbol of urbanization development. A comprehensive assessment of urban landscapes is crucial for guiding the development of inclusive, resilient, and sustainable cities and human settlements. Previous studies have primarily analyzed two-dimensional landscape indicators derived from satellite remote sensing, potentially overlooking the valuable insights provided by the three-dimensional configuration of landscapes. This limitation arises from the high cost of acquiring large-area three-dimensional data and the lack of effective assessment indicators. Here, we propose four urban landscapes indicators in three dimensions (UL3D): greenness, grayness, openness, and crowding. We construct the UL3D using 4.03 million street view images from 303 major cities in China, employing a deep learning approach. We combine urban background and two-dimensional urban landscape indicators with UL3D to predict the socioeconomic profiles of cities. The results show that UL3D indicators differs from two-dimensional landscape indicators, with a low average correlation coefficient of 0.31 between them. Urban landscapes had a changing point in 2018-2019 due to new urbanization initiatives, with grayness and crowding rates slowing, while openness increased. The incorporation of UL3D indicators significantly enhances the explanatory power of the regression model for predicting socioeconomic profiles. Specifically, GDP per capita, urban population rate, built-up area per capita, and hospital count correspond to improvements of 25.0%, 19.8%, 35.5%, and 19.2%, respectively. These findings indicate that UL3D indicators have the potential to reflect the socioeconomic profiles of cities.

Coupled Pacific Rim megadroughts contributed to the fall of the Ming Dynasty's capital in 1644 CE

Historical documents provide evidence for regional droughts preceding the political turmoil and fall of Beijing in 1644 CE, when more than 20 million people died in northern China during the late Ming famine period. However, the role climate and environmental changes may have played in this pivotal event in Chinese history remains unclear. Here, we provide tree-ring evidence of persistent megadroughts from 1576 to 1593 CE and from 1628 to 1644 CE in northern China, which coincided with exceptionally cold summers just before the fall of Beijing. Our analysis reveals that these regional hydroclimatic extremes are part of a series of megadroughts along the Pacific Rim, which not only impacted the ecology and society of monsoonal northern China, but likely also exacerbated external geopolitical and economic pressures. This finding is corroborated by last millennium reanalysis data and numerical climate model simulations revealing internally driven Pacific sea surface temperature variations and the predominance of decadal scale La Niña-like conditions to be responsible for precipitation decreases over northern China, as well as extensive monsoon regions in the Americas. These teleconnection patterns provide a mechanistic explanation for reoccurring drought spells during the late Ming Dynasty and the environmental framework fostering the fall of Beijing in 1644 CE, and the subsequent demise of the Ming Dynasty.

Exploring trade-offs between residential and industrial functions in rural areas and their ecological impacts across transitioning agricultural systems: Evidence from the metropolitan suburbs of China

The rapid transition of agricultural systems substantially affects residential and industrial land use systems in rural areas, often generating spatiotemporal trade-offs between residential and industrial functions and producing considerable ecological impacts, which has thus far not been well understood. We conduct an indicator-based assessment of transitioning agriculture systems, and then links the transitioning agricultural systems to trade-offs between residential and industrial functions from 2005 to 2020 by using a case study-the metropolitan suburbs of Beijing, China. Also, the associated ecological impacts of the trade-offs are characterized based on the calculation of the ecological quality index (EQI) and ecological contribution rate. The results show that trade-offs between residential and industrial functions in the metropolitan suburbs have gradually adapted to the different agricultural systems in transition, which can be characterized by increasing industrial function as well as declining residential function, together with the diversification of land use into a mixed pattern. Additionally, along with the transitioning process comes a U shape of the ecological quality curve, which indicates that relentless industrial sprawl into regions where the agricultural system has a low capacity for technology, as well as decay in rural areas attributed to a rural exodus and industrial decline in semi-subsistence agricultural areas, even cause ecological degradation. In general, trade-offs between residential and industrial functions (especially for the non-agricultural production function) in rural areas could partially and temporally generate unfavorable ecological impacts, but it seems to be a favorable phenomenon to promote ecological quality in the long term. Therefore, to achieve rural sustainable planning, it is necessary for land use management to observe the trade-offs between residential and industrial functions while avoiding negative impacts, such as low-density land use patterns, disordered land use functions, and eco-environmental deterioration. Such effective strategies can contribute to the feasible implementation of policies aiming to achieve the compatible development of liveable residences, highly efficient industrial production, and eco-friendly operations in rural areas.