Urban-rural integration is an advanced form resulting from the future evolution of urban-rural relationships. Nevertheless, little research has explored whether urban and rural areas can move from dual segmentation to integrated development from a theoretical or empirical perspective. Based on the research framework of welfare economics, which offers an appealing paradigm to frame the underlying game between cities and villages, this study clarifies the ideal state of urban-rural integration. It then proposes a series of basic assumptions, and constructs a corresponding objective function and its constraints. Moreover, it assesses the possibility of seeing the transmutation from division to integration between urban and rural areas with continuous socio-economic development. The authors argue that the ideal state of urban-rural integration should be a Pareto-driven optimal allocation of urban-rural resources and outputs, and the maximization of social welfare in the entire region. Based on a systematic demonstration using mathematical models, the study proposes that urban and rural areas can enter this ideal integrated development pattern when certain parameter conditions are met. In general, this study demonstrates the theoretical logic and scientific foundations of urban-rural integration, enriches theoretical studies about urban-rural relationships, and provides basic theoretical support for large developing countries to build a coordinated and orderly urban-rural community with a shared future.
Cities are the key areas for human beings to achieve sustainable development goals in the future. Estuarine cities are a special type of coastal city in urgent need of a clear definition. This paper proposed that estuarine cities are cities developed on the coast where rivers and oceans meet and defined four connotations, including the intersection of rivers and marine water systems, the coordinated development of land and oceans, the location advantages of connecting rivers and seas, and the important fragility of the ecological environment. We used HydroSHEDS, OSM, GPW, and urban socioeconomic statistics and selected 50 estuarine cities with large rivers as representatives to summarize the main geographical basis and socioeconomic characteristics. Cities are primarily found in low-altitude, flat regions with average annual temperatures that mainly vary from 10°C to 25°C, relatively abundant precipitation, and extensive biological resources. There are substantial variations in the socioeconomic features of estuarine cities. We proposed eight development patterns, including open and inclusive city spirit, high-quality livable cities, high-quality development driven by innovation, integration of internal and external communication with ports and cities, construction of an international financial center, ecological environment protection and restoration, active promotion of cultural tourism, and positive international exchanges.
Construction land is the leading carrier of human activities such as production and living. Evaluating the construction land suitability (CLS) on the Qinghai-Tibet Plateau (QTP) holds significant implications for harmonizing the relationship between ecological protection and human activity and promoting population and industry layout optimization. However, no relevant studies provide a complete CLS assessment of the QTP. In this study, we developed a model-based CLS evaluation framework coupling of pattern and process to calculate the global CLS on the QTP based on a previously developed CLS evaluation model. Then, using the land-use data of 1990, 2000, 2010, and 2020, we examined the adaptability of existing construction land (ECL) to the CLS assessment result through the adaptability index and vertical gradient index and further analyzed the limitations of maladaptive construction land. Finally, we calculated the potential area of reserve suitable construction land. This article includes four conclusions: (1) The highly suitable, suitable, moderately suitable, marginally suitable, and unsuitable CLS classes cover areas of 0.33×104 km2, 10.42×104 km2, 18.06× 104 km2, 24.12×104 km2, and 205.29×104 km2, respectively. Only approximately 11% of the study area on the QTP is suitable for large-scale permanent construction land, and approximately 79.50% of the area is unsuitable under current economic and technological conditions. (2) The ECL adaptability index is 85.16%, 85.93%, 85.18%, and 78.01% during 1990-2020, respectively, with an average adaptability index exceeding 80% on the QTP. The ECL distribution generally conforms to construction land suitable space characteristics but with a significant spatial difference. (3) From 1990 to 2020, the maladaptive ECL was dominated by rural settlement land, transport land, and special land, with a rapidly increasing proportion of urban and other construction land. The maladaptive ECL is constrained by both elevation and slope in the southern Qinghai Plateau, the Hengduan Mountains, and the Qilian Mountains. In contrast, elevation is significantly more limiting than slope in the northern Tibet Plateau, the Gangdis Mountains, and the Himalayan Mountains. (4) The potential area of reserve suitable construction land is 12.41×104 km2, accounting for 4.81% of the total land area of the QTP, and the per capita area is 9928 m2. Regions of Qaidam Basin, Gonghe Basin, and Lhasa-Shannan Valley have the richest and most concentrated land resource of reserve suitable construction land. The research results provide spatial decision support for urban and rural settlement planning and ecological migration on the QTP.
Identification of the spatial mismatch between land use functions (LUFs) and land use efficiencies (LUEs) is essential to regional land use policies. However, previous studies about LUF-LUE mismatch and its driving factors have been insufficient. In this study, we explored the spatiotemporal mismatch of LUFs and LUEs and their influencing factors from 2000 to 2018 in the Middle Reaches of the Yangtze River (MRYR). Specifically, we used Spearman correlation analysis to reveal the trade-off relationship between LUFs and LUEs and determine the direction of the influencing factors on the LUF-LUE mismatch, adopted spatial mismatch analysis to measure the imbalance between LUFs and LUEs, and used the geographical detector model to analyze the factors influencing this spatial mismatch. The results showed that production function (PDF), living function (LVF), ecological function (ELF), agricultural production efficiency (APE), urban construction efficiency (UCE), and ecological services efficiency (ESE) all displayed significant spatial heterogeneity. The high trade-off areas were widely distributed and long-lasting in agricultural space and urban space, while gradually decreasing in ecological space. Wuhan and Changsha showed high spatial mismatch coefficients in urban space, but low spatial mismatch coefficients in agricultural space. Hunan generally presented high spatial mismatch coefficients in ecological space. Furthermore, the interaction of the proportion of cultivated area and transportation accessibility exacerbated the mismatch in agricultural space. The interaction effects of capital investment and technology innovation with other factors have the most intense impact on the mismatch in urban space. The internal factor for cultivated area interacts with other external factors to drastically affect ecological spatial mismatch.
Urban shrinkage has attracted the attention of many geographers and urban planners in recent years. However, there are fewer studies on vacant housing in shrinking cities. Therefore, this study combines multi-source remote sensing images and urban building data to assess the spatiotemporal variation patterns of housing vacancy in a typical shrinking city in China. The following points were obtained: (1) We developed an evaluation model to identify vacant residential buildings in shrinking cities by removing the contribution of nighttime lights from roads and non-residential buildings; (2) The residential building vacancy rate in Fushun city significantly increased from 2013 to 2020, resulting in a significant high-value clustering effect. The impact of urban shrinkage on vacant residential buildings was higher than that on vacant non-residential buildings; (3) The WorldPop population data demonstrated consistent spatial distribution and trend of population change in Fushun with the residential building vacancy rate results, suggesting good reliability of the constructed evaluation model in this study. Identifying housing vacancies can help the local government to raise awareness of the housing vacancy problem in shrinking cities and to propose reasonable renewal strategies.
The carbon cycle of terrestrial ecosystems is influenced by global climate change and human activities. Using remote sensing data and land cover products, the spatio-temporal variation characteristics and trends of NEP in the Yangtze River Delta from 2000 to 2020 were analyzed based on the soil respiration model. The driving influences of ecosystem structure evolution, temperature, rainfall, and human activities on NEP were studied. The results show that the NEP shows an overall distribution pattern of high in the southeast and low in the northwest. The area of carbon sinks is larger than that of the carbon sources. NEP spatial heterogeneity is significant. NEP change trend is basically unchanged or significantly better. The future change trend in most areas will be continuous decrease. Compared with temperature, NEP are more sensitive to precipitation. The positive influence of human activities on NEP is mainly observed in north-central Anhui and northern Jiangsu coastal areas, while the negative influence is mainly found in highly urbanized areas. In the process of ecosystem structure, the contribution of unchanged areas to NEP change is greater than that of changed areas.
The taiga vegetation in Western Siberia has been seriously threatened by climate warming in recent decades. However, how vegetation in different growing states and climate conditions responds to climate changes differently is still unclear. Here we explore the vegetation activity trends in Western Siberia taiga forests using the annual rate of change in leaf area index (LAI) during 1982-2018 so as to answer two questions: (1) how did climate warming affect taiga vegetation activity in the recent last decades? (2) Did the growing state of taiga forest affect its response to climate warming? Our results revealed that climate warming promoted taiga vegetation activity in Western Siberia before 2000. However, continuous warming caused excessive evapotranspiration and led to decreased vegetation activity after 2000. Moreover, the intensity of vegetation growth response to warming was positively related to canopy height and LAI, indicating that both the positive and negative effects of warming were more significant in taiga forests in better growing state. Since these forests generally have higher productivity and play more important roles in ecosystem functioning (e.g., carbon sink and biodiversity conservation), our results highlight their vulnerability to future climate change that need more research attention.
Current ecosystem models used to simulate global terrestrial carbon balance generally suggest that terrestrial landscapes are stable and mature, but terrestrial net primary productivity (NPP) data estimated without accounting for disturbances in species composition, environment, structure, and ecological characteristics will reduce the accuracy of the global carbon budget. Therefore, the steady-state assumption and neglect of elevation-related changes in forest NPP is a concern. The Qilian Mountains are located in continental climate zone, and vegetation is highly sensitive to climate change. We quantified aboveground biomass (AGB) and aboveground net primary productivity (ANPP) sequences at three elevations using field-collected tree rings of Picea crassifolia in Qilian Mountains of Northwest China. The results showed that (1) There were significant differences between AGB and ANPP at the three elevations, and the growth rate of AGB was the highest at the low elevation (55.99 t ha-1 10a-1). (2) There are differences in the response relationship between the ANPP and climate factors at the three elevations, and drought stress is the main climate signal affecting the change of ANPP. (3) Under the future climate scenario, drought stress intensifies, and the predicted decline trend of ANPP at the three elevations from mid-century to the end of this century is -0.025 t ha-1 10a-1, respectively; -0.022 t ha-1 10a-1; At -0.246 t ha-1 10a-1, the level of forest productivity was significantly degraded. The results reveal the elevation gradient differences in forest productivity levels and provide key information for studying the carbon sink potential of boreal forests.
Digital elevation model (DEM) plays a fundamental role in the study of the earth system by expressing surface configuration, understanding surface process, and revealing surface mechanism. DEM is widely used in analysis and modeling in the field of geoscience. However, traditional DEM has the defect of single attribute, which is difficult to support the research in earth system science oriented to geoscience process and mechanism mining. Hence, realizing the value-added data model on the basis of traditional DEM is necessary to serve digital elevation modeling and terrain analysis under the background of a new geomorphology research paradigm and earth observation technology. A theoretical framework for value-added DEM that mainly includes concept, connotation, content, and categories, is constructed in this study. The relationship between different types of value-added DEMs as well as the research significance and application category of this theoretical framework are also proposed. The following are different methods of value-added DEMs: (1) value-added methods of DEM space and time dimensions that emphasize the integration of the ground and underground as well as coupling of time and space, (2) attribute-based value-added methods composed of material (including underground, surface, and ground) and morphological properties, and (3) value-added methods of features and physical elements that consider geographical objects and landform features formed by natural processes and artificial effects. The digital terrace, slope, and watershed models are used as examples to illustrate application scenarios of the three kinds of value-added methods. This study aims to improve expression methods of DEMs under the background of new surveying and mapping technologies by adding value to the DEM at three levels of dimensions, attributes, and elements as well as support knowledge-driven digital geomorphological analysis in the era of big data.
In the context of climate change and human activities, flood disasters in arid mountainous areas have become increasingly frequent, and seriously threatened the safety of people’s lives and property. Rapid and accurate flash flood inundation modelling is an essential foundational research area, which can aid in the reduction of casualties and the minimization of disaster losses; however, this modelling is also very difficult, and models need to be urgently developed to address flash flood forecasting and warnings. The objective of this study is to construct a numerical modelling method for flash floods in drylands. Based on a 2D high-resolution flood numerical model (FloodMap-HydroInundation2D), we hindcasted the dynamic process of flash flooding and show the spatio-temporal characteristics of flash flood inundation for the “8·18” flash flood disaster that occurred in Datong county, Qinghai province. The results showed that the model output effectively agreed with the observed inundation after the event in terms of both spatial extent and temporal process. Extensive flooding mainly occurred between 00:00 and 01:00 on August 18, 2022. Qingshan, Hejiazhuang and Longwo villages were affected most heavily. We further conducted model sensitivity analysis and found that the model was highly sensitive to both roughness and hydraulic conductivity in drylands, and the effect of hydraulic conductivity was more pronounced. Our study confirmed the good performance of our model for the simulation of flash flooding in arid areas and provides a potential method for flash flood assessment and management in arid areas.
