Traditional spatial clustering methods have the disadvantage of “hardware division”, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures’ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated characteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.

Despite the well-documented effects of global climate change on terrestrial species’ ranges, eco-geographical regions as the regional scale of ecosystems have been poorly studied especially in China with diverse climate and ecosystems. Here we analyse the shift of temperature zones in eco-geographical study over China using projected future climate scenario. Projected climate data with high resolution during 1961–2080 were simulated using regional climate model of PRECIS. The number of days with mean daily temperature above 10℃ and the mean temperature of January are usually regarded as the principal criteria to indicate temperature zones, which are sensitive to climate change. Shifts due to future climate change were calculated by comparing the latitude of grid cells for the future borderline of one temperature zone with that for baseline period (1961–1990). Results indicated that the ranges of Tropical, Subtropical, Warm Temperate and Plateau Temperate Zones would be enlarged and the ranges of Cold Temperate, Temperate and Plateau Sub-cold Zones would be reduced. Cold Temperate Zone would probably disappear at late this century. North borderlines of temperature zones would shift northward under projected future climate change, especially in East China. Farthest shifts of the north boundaries of Plateau Temperate, Subtropical and Warm Temperate Zones would be 3.1°, 5.3° and 6.6° latitude respectively. Moreover, northward shift would be more notably in northern China as future temperature increased.

In this paper, the monthly precipitation and temperature data collected at 7 stations in the Ili River Basin from 1961 to 2007 were analyzed by means of simple regression analysis, running mean, db6 wavelet function and Mann-Kendall test. This study revealed the characteristics of climate change and abrupt change points of precipitation and temperature during different time scales in the Ili River Basin within the past 50 years. The results showed that the precipitation increased from the mid-1980s until 2000 and has continued to increase at a smaller magnitude since 2000. Over the studied period, the precipitation increased significantly during the summer and winter months. The temperature increased greatly in the late 1980s, and has continued to show an increasing trend from the year 2000 to present. The temperature increases were most significant during the summer, autumn and winter months. In terms of different geographies, the temperature increase was significant during the winter in the plains and hilly regions; the increase was also significant during autumn in the intermontane basins. The climate change trends in the Ili River Basin were consistent with the changing trends of the North Atlantic Oscillation and the plateau monsoon.

Glaciers are one of the most important land covers in alpine regions and especially sensitive to global climate change. Remote sensing has proved to be the best method of investigating the extent of glacial variations in remote mountainous areas. Using Landsat thematic mapping (TM) and multi-spectral-scanner (MSS) images from Mt. Qomolangma (Everest) National Nature Preserve (QNNP), central high Himalayas for 1976, 1988 and 2006, we derived glacial extent for these three periods. A combination of object-oriented image interpretation methods, expert knowledge rules and field surveys were employed. Results showed that (1) the glacial area in 2006 was 2710.17 ± 0.011 km2 (about 7.41% of the whole study area), and located mainly to the south and between 4700 m to 6800 m above sea level; (2) from 1976 to 2006, glaciers reduced by 501.91 ± 0.035 km2 and glacial lakes expanded by 36.88 ± 0.035 km2; the rate of glacier retreat was higher in sub-basins on the southern slopes (16.79%) of the Himalayas than on the northern slopes (14.40%); most glaciers retreated, and mainly occurred at an elevation of 4700–6400 m, and the estimated upper limit of the retreat zone is between 6600 m and 6700 m; (3) increase in temperature and decrease in precipitation over the study period are the key factors driving retreat.

Based on the temporal-spatial distribution features of ancient settlement sites from the middle and late Neolithic Age to the Han dynasty in the Chaohu Lake Basin of Anhui Province, East China, using the methods of GIS combined with the reconstructed paleoenvironment by the records of lake sediment since Holocene, the transmutation of ancient settlements with response to environmental changes in this area has been discussed. Studies show that the main feature of transmutation of ancient settlements from the middle and late Neolithic Age to the Han Dynasty was that the distribution of settlements in this area changed from high altitudes to low ones and kept approaching the Chaohu Lake with the passage of time. These could be the response to the climate change from warm-moist to a relatively warm-dry condition during the middle Holocene, leading to the lake level fluctuations. The large area of exposed land provided enough space for human activities. These indicate that the above changes in geomorphologic evolution and hydrology influenced by climate conditions affected the transmutation of ancient settlements greatly. The distribution pattern of settlement sites was that the number of sites in the west was more than in the east. This pattern may be related to the geomorphologic conditions such as frequent channel shifting of the Yangtze River as well as flood disasters during the Holocene optimum. Therefore, climate change was the inducement of the transmutation of ancient settlements in the Chaohu Lake Basin, which exerted great influence on the distribution, expansion and development of the ancient settlements.

Water regulation has been carried out by the Heihe River Bureau since 2000, which aims to address the existing eco-environmental problems in the lower Heihe River. In the past nine years, great changes in spatial-temporal distribution of water resources took place in the lower Heihe River. In order to objectively evaluate the influence of water regulation on the eco-environment, the changes of groundwater table, typical vegetation, landscape types as well as East Juyan Lake have been analyzed in the lower Heihe River, by means of field surveys and remote sensing. These results indicate that there are obvious effects of water regulation on the eco-environment, which has been improved toward sustainability in the lower Heihe River.

A 332-cm long lacustrine core was drilled in the Nam Co in the central-southern part of the Tibetan Plateau. From the core, 15 species of ostracods (Crustacea: Ostracoda), which belong to 6 genera have been identified. According to the variations of the ostracod assemblages and the ostracods ecological features, which are sensitive to the changing environment, three main stages can be distinguished as follows: Stage I was from 8400 to 6800 a BP, during which the climate was cold-humid, and the lake depth changed from shallow to deep. Stage II was from 6400 to 2500 a BP, during which the climate changed from warm-humid to cold-humid, and then to cold-dry. The lake depth gradually became deep. The shifting of climate, from wet-cold to dry-cold during this period, had constructed the basis of present environment in the Nam Co. Stage III was from 2500 a BP to the present, which showed a trait of lake depth increasing. At the earlier period of this stage, the climate kept as cold-dry as that in the former stage, but the salinity of the lake increased. At the later period of this stage, the degree of cold-dry was enhanced, and the activities of land surface runoff tended to be weakened. Our research also found that the peak values of ostracods with black shell was coherent with the maximum production of the ostracods, and agreed with the increasing sedimentary water dynamics. This indicated that the ostracods with black shell was simultaneous with the high prolificacy of ostracod, and transported from other places. The abundance of Candona juvenile shells reflected the high mortality of that kind of ostracods under an unfavorable condition. This was probably a result of the rapid change of water dynamics of sedimentary environment.

GIMMS NDVI database and geo-statistics were used to depict the spatial distribution and temporal stability of NDVI on the Mongolian Plateau.The results demonstrated that:(1) Regions of interest with high NDVI indices were distributed primarily in forested mountainous regions of the east and the north,areas with low NDVI indices were primarily distributed in the Gobi desert regions of the west and the southwest,and areas with moderate NDVI values were mainly distributed in a middle steppe strap from northwest to southeast.(2) The maximum NDVI values maintained for the past 22 years showed little variation.The average NDVI variance coefficient for the 22-year period was 15.2%.(3) NDVI distribution and vegetation cover showed spatial autocorrelations on a global scale.NDVI patterns from the vegetation cover also demonstrated anisotropy;a higher positive spatial correlation was indicated in a NW-SE direction,which suggested that vegetation cover in a NW-SE direction maintained increased integrity,and vegetation assemblage was mainly distributed in the same specific direction.(4) The NDVI spatial distribution was mainly controlled by structural factors,88.7% of the total spatial variation was influenced by structural and 11.3% by random factors.And the global autocorrelation distance was 1178 km,and the average vegetation patch length(NW-SE) to width(NE-SW) ratio was approximately 2.4:1.0.

Rainstorms are one of the extreme rainfall events that cause serious disasters, such as urban flooding and mountain torrents. Traditional studies have used rain gauge observations to analyze rainstorm events, but relevant information is usually missing in gauge-sparse areas. Satellite-derived precipitation datasets serve as excellent supplements or substitutes for the gauge observations. By developing a grid-based rainstorm-identification tool, we used the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) time series product to reveal the spatial and temporal variabilities of rainstorms over China during 1998-2017. Significant patterns of both increasing and decreasing rainstorm occurrences were detected, with no spatially uniform trend being observed across the whole country. There was an increase in the area being affected by rainstorms during the 20-year period, with rainstorm centers shifting along the southwest-northeast direction. Rainstorm occurrence was found to be correlated with local total precipitation. By comparing rainstorm occurrence with climate variables such as the El Ni?o-Southern Oscillation and Pacific Decadal Oscillation, we also found that climate change was likely to be the primary reason for rainstorm occurrence in China. This study complements previous studies that used gauge observations by providing a better understanding of the spatiotemporal dynamics of China’s rainstorms.

Explicitly identifying the spatial distribution of ecological transition zones (ETZs) and simulating their response to climate scenarios is of significance in understanding the response and feedback of ecosystems to global climate change. In this study, a quantitative spatial identification method was developed to assess ETZ distribution in terms of the improved Holdridge life zone (iHLZ) model. Based on climate observations collected from 782 weather stations in China in the T0 (1981-2010) period, and the Intergovernmental Panel on Climate Change Coupled Model Intercomparison Project (IPCC CMIP5) RCP2.6, RCP4.5, and RCP8.5 climate scenario data in the T1 (2011-2040), T2 (2041-2070), and T3 (2071-2100) periods, the spatial distribution of ETZs and their response to climate scenarios in China were simulated in the four periods of T0, T1, T2, and T3. Additionally, a spatial shift of mean center model was developed to quantitatively calculate the shift direction and distance of each ETZ type during the periods from T0 to T3. The simulated results revealed 41 ETZ types in China, accounting for 18% of the whole land area. Cold temperate grassland/humid forest and warm temperate arid forest (564,238.5 km ²), cold temperate humid forest and warm temperate arid/humid forest (566,549.75 km ²), and north humid/humid forest and cold temperate humid forest (525,750.25 km ²) were the main ETZ types, accounting for 35% of the total ETZ area in China. Between 2010 and 2100, the area of cold temperate desert shrub and warm temperate desert shrub/thorn steppe ETZs were projected to increase at a rate of 4% per decade, which represented an increase of 3604.2, 10063.1, and 17,242 km ² per decade under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. The cold ETZ was projected to transform to the warm humid ETZ in the future. The average shift distance of the mean center in the north wet forest and cold temperate desert shrub/thorn grassland ETZs was generally larger than that of other ETZs, with the mean center moving to the northeast and the shift distance being more than 150 km during the periods from T0 to T3. In addition, with a gradual increase of temperature and precipitation, the ETZs in northern China displayed a shifting northward trend, while the area of ETZs in southern China decreased gradually, and their mean center moved to high-altitude areas. The effects of climate change on ETZs presented an increasing trend in China, especially in the Qinghai-Tibet Plateau.

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.

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.

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.

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.

In the context of accelerated globalization, intercity factor flows are becoming increasingly dependent on a reasonable and orderly spatial structure. Therefore, an in-depth study of the optimization and adjustment of spatial structure is essential for coordinated development. This study quantitatively evaluated urban development levels and introduced network analysis methods to analyse the spatial structure and robustness of development. The results indicated the following: (1) The urban development level in the Beijing-Tianjin- Hebei (BTH) region increased in all dimensions, and the transmission efficiency significantly improved. (2) The spatial structure of the BTH region has been relatively stable, as illustrated by the main pattern of the spatial distribution of central cities, with a trend towards contiguous development. (3) The ranking of network robustness is environment>society>economy, and the core network and key nodes are primarily located within the radiation of the three central cities of Beijing, Tianjin, and Shijiazhuang. (4) The coordinated development of the BTH region is effective but still needs to be optimized and adjusted, and the strategic significance of edge cities has not been completely exploited. This study aims to provide an emerging analytical perspective for optimizing regional spatial structure and promoting regional coordinated development.

Social upgrading does not inherently follow economic upgrading; rather, they present a complex interplay. This paper, focusing on China, utilizes the coupling coordination degree and a panel regression model to shed light on the intricate interaction between social upgrading and economic upgrading. It is found that the coupling coordination degree of social and economic upgrading in China has improved from 0.33 to 0.49 since the mid-1990s, undergoing a shift from a stage of slight imbalance to low-level coordination. However, significant regional disparities are present in terms of economic upgrading, social upgrading, and their coupling coordination degree. Developed areas exhibit a higher degree of coupling coordination compared to less developed regions, indicating a connection between the coupling coordination degree and the level of economic growth. Economic globalization, public governance, and the legal environment positively impact the coupling coordination between social and economic upgrading, while economic privatization and corporate violations of law exert negative effects. The paper concludes with policy discussions for enhancing the coupling coordination between social and economic upgrading.

Construction land expansion is a key driver of urbanization and industrialization, yet it poses the risk of losing farmland and cascading impacts on food supply. The spatial characteristics of farmland occupied by construction land and its association with grain yield in China were unclear. We analyzed the characteristics of farmland converted into construction land, and its relationship with grain yield in China for 2000-2020. Construction land increased in area in central and western regions of China, and farmland decreased in area in southeastern China. The expansion of construction land in the North China Plain, Northeast China Plain, and the Loess Plateau, occurred at the expense of farmland. Except the southeast coast of China, grain yield increase was only weakly dependent on farmland area. Patterns in which farmland was converted into construction land and grain-yield change were highly coupled in southeastern coastal China, Sichuan Basin, Shandong Peninsula, and the Hu Huanyong Line. It should be noted that expansion in construction land area does have some influence on grain production; ultimately it is greatly affected by yield per unit area.

Urbanization interacts with land use through resource consumption and space encroachment. Clarifying the spatial correlations of the interactive relationship between urbanization and land use, along with their spatiotemporal dynamics, is of vital importance for addressing the complex interplay between urban development and land resources and identifying regional differences. However, previous studies have not sufficiently explored these issues. Herein, we introduce a coupling coordination degree (CCD) model and present the results of exploratory spatiotemporal analyses involving in-depth investigation of the CCD between urbanization quality and land-use intensity in 290 Chinese cities. The results demonstrate that the CCD for most cities was at the transition-period or basic-coordination stage. The dynamics of the spatial correlation of the CCD was found to increase from the east to the central and western regions, but this was found to decline overall. The movement direction and spatial dependence of the local spatial structure of the CCD exerted a dominant synergistic effect. The transition of the spatial correlation was mainly Type I (stable local and neighboring morphology), showing strong transfer inertia, path dependence, and locking features. Dynamic transitions occurred more in central and eastern cities. The results suggest that more cross-city cooperation could contribute to moderate land-resource exploitation for high-quality urbanization.

Landscape in the middle and lower reaches of the Yellow River in China has undergone significant changes for thousands of years due to agricultural expansion. Lack of reliable long-term and high-resolution historical cropland data has limited our ability in understanding and quantifying human impacts on regional climate change, carbon and water cycles. In this study, we used a data-driven modeling framework that combined multiple sources of data (historical provincial cropland area, historical coastlines, and satellite data-based maximum cropland extent) with a new gridding allocation model for croplands distribution to reconstruct a historical cropland dataset for the middle and lower reaches of the Yellow River at a 10-km resolution for 58 time points ranging from the period 1000 to 1999. The cropland area in the study area increased by 2.3 times from 21.87 million ha in 1000 to 50.64 million ha in 1999. Before 1393, the area of cropland increased slowly and was primarily concentrated in the Weihe and Fenhe plains. From 1393‒1820, the area of cropland increased rapidly, particularly on the North China Plain. Since 1820, cropland cover has tended to become saturated. Our newly reconstructed results agreed well with remotely sensed data as well as historical document-based facts regarding cropland distribution.

Gully erosion, an integrated result of various social and environmental factors, is a severe problem for sustainable development and ecology security in southern China. Currently, the dominant driving forces on gully distribution are shown to vary at different spatial scales. However, few systematic studies have been performed on spatial scaling effects in identifying driving forces for gully erosion. In this study, we quantitatively identified the determinants of gully distribution and their relative importance at four different spatial scales (southern China, Jiangxi province, Ganxian county, and Tiancun township, respectively) based on the Boruta algorithm. The optimal performance of gully susceptibility mapping was investigated by comparing the performance of the multinomial logistic regression (MLR), logistic model tree (LMT), and random forest (RF). Across the four spatial scales, the total contributions of gully determinants were classified as lithology and soil (32.65%) > topography (22.40%) > human activities (22.31%) > climate (11.32%) > vegetation (11.31%). Among these factors, precipitation (7.82%), land use and land cover (6.16%), rainfall erosivity (10.15%), and elevation (11.59%) were shown to be the predominant factors for gully erosion at the individual scale of southern China, province, county, and township, respectively. In addition, contrary to climatic factors, the relative importance of soil properties and vegetation increased with the decrease of spatial scale. Moreover, the RF model outperformed MLR and LMT at all the investigated spatial scales. This study provided a reference for factor selection in gully susceptibility modeling and facilitated the development of gully erosion management strategies suitable for different spatial scales.

The imbalance in global streamflow gauge distribution and regional data scarcity, especially in large transboundary basins, challenge regional water resource management. Effectively utilizing these limited data to construct reliable models is of crucial practical importance. This study employs a transfer learning (TL) framework to simulate daily streamflow in the Dulong-Irrawaddy River Basin (DIRB), a less-studied transboundary basin shared by Myanmar, China, and India. Our results show that TL significantly improves streamflow predictions: the optimal TL model achieves an average Nash-Sutcliffe efficiency of 0.872, showing a marked improvement in the Hkamti sub-basin. Despite data scarcity, TL achieves a mean NSE of 0.817, surpassing the 0.655 of the process-based model MIKE SHE. Additionally, our study reveals the importance of source model selection in TL, as different parts of the flow are affected by the diversity and similarity of data in the source model. Deep learning models, particularly TL, exhibit complex sensitivities to meteorological inputs, more accurately capturing non-linear relationships among multiple variables than the process-based model. Integrated gradients (IG) analysis further illustrates TL’s ability to capture spatial heterogeneity in upstream and downstream sub-basins and its adeptness in characterizing different flow regimes. This study underscores the potential of TL in enhancing the understanding of hydrological processes in large-scale catchments and highlights its value for water resource management in transboundary basins under data scarcity.

China’s outward foreign direct investment (FDI) is different from traditional FDI in various ways, for example being rooted in “Guanxi” in Chinese culture, influenced by government, and located in developed economies where they have limited ownership advantages compared with local firms. Chinese investment in the United States (the U.S.) is an example of how the location is influenced by economic factors, social linkages, as well as geopolitical events, such as the U.S.-China trade conflict, which deserves more academic attention. It is such a complex phenomenon that cannot be fully explained by traditional FDI theories, which mainly focus on economic factors. In this paper, we illustrate the historical development, distribution and firm heterogeneity of Chinese investment in the U.S. from 2000 to 2020, and use a conditional logit model to investigate the location factors. Our study reveals that the number of Chinese investment projects in the U.S. peaked in 2017 and has declined year-over-year since then. These projects are mainly located along the East and West coasts of the U.S. and around the Great Lakes, with the largest numbers in California and New York. Previous Chinese investment agglomeration and ethnic networks both influence the location choice of China’s outward FDI, even when controlling for regional attributes and economic embeddedness. In terms of firm heterogeneity, Chinese firms that enter the American market with greenfield investment modes, state-owned enterprises and firms in high-tech sectors are more likely to follow previous Chinese investment, but place less emphasis on Chinese ethnic linkages, implying that previous Chinese investment agglomeration can replace the role of Chinese ethnic networks for these firms. Finally, the U.S.-China trade conflict has significantly lessened the active role of Chinese ethnic networks and has reduced Chinese investment in states with higher industrial output.

Due to complex terrain of the Loess Plateau, the classification accuracy is unsatisfactory when a single supervised classification is used in the remote sensing investigation of the sloping field. Taking the loess hill and gully area of northern Shaanxi Province as a test area, a research was conducted to extract sloping field and other land use categories by applying an integrated classification. Based on an integration of supervised classification and unsupervised classification, sampling method is remarkably improved. The results show that the classification accuracy is satisfactory by the method and is of critical significance in obtaining up-to-date information of the sloping field, which should be helpful in the state key project of converting farmland to forest and grassland on slope land in this area. This research sought to improve the application accuracy of image classification in complex terrain areas.

The ecological footprint of China's provinces is calculated in this paper. In general, China's development is not sustainable because its ecological footprint is beyond its bio-capacity. The sustainability status of each province in China is presented. Ulanowicz's development capacity formula was introduced to discuss the relationship of development and ecological footprint's diversity. The diversity of ecological impacts is related to the efficiency with which an economy uses the source and sink services of the environment and, in this view, should be a factor in economic output. Development capacity, calculated from the ecological footprint and its diversity, is used to examine the relationship of economic output with the structure of the ecological footprint. China and its provinces are presented as a case study to investigate this relationship. The analysis shows that footprint capacity is significant in predicting economic output. Increasing the ecological footprint's diversity is presented as another way to increase development capacity.