Reconstruction of the spatial pattern of regional habitat quality can revivify the ecological environment background at certain historical periods and provide scientific support for revealing the evolution of regional ecological environmental quality. In this study, we selected 10 driving factors of land use changes, including elevation, slope, aspect, GDP, population, temperature, precipitation, river distance, urban distance, and coastline distance, to construct the CA-Markov model parameters and acquired the land use spatial data for 1975, 1980, 1985, 1990, and 1995 by simulation based on the land use status map for 2010. On this basis, we used the InVEST model to reconstruct the spatial pattern of habitat quality in the study area and conducted classification division and statistical analysis on the computed habitat degradation degree index and the habitat quality index. (1) The results showed that from 1975 to 2010, the habitat degradation degree gradually increased, and the habitat degradation grade spatially presented a layered progressive distribution. Habitat quality presented a constantly decreasing trend. The high-value zones were mainly distributed in the mountainous areas, while the low-value zones were mostly located in built-up areas. During the period of 1975-2010, low-value zones gradually expanded to their surrounding high-value zones, and the high-value zones of habitat quality tended to be fragmented. (2) The spatial-temporal variation characteristics of habitat quality from 1975 to 2010 showed that the regions with low habitat quality were difficult to be restored and mostly maintained their original state; the regions with poor habitat quality, which accounted for 6.40% of the total study area, continued to deteriorate, mainly around built-up areas; the regions with good and superior habitat quality, which accounted for 5.68% of the total study area, were easily converted to regions with bad or poor habitat quality, thus leading to the fragmentation of the regional habitat. (3) From 1975 to 2010, land use changes in the study area were significant and had a huge influence on habitat quality; the habitat quality in the study area decreased consistently, and the area of the regions with bad and poor habitat quality accounted for more than 60% of the total study area. Construction land was the largest factor threatening habitat quality.
The Chinese government ratified the Paris Climate Agreement in 2016. Accordingly, China aims to reduce carbon dioxide emissions per unit of gross domestic product (carbon intensity) to 60%-65% of 2005 levels by 2030. However, since numerous factors influence carbon intensity in China, it is critical to assess their relative importance to determine the most important factors. As traditional methods are inadequate for identifying key factors from a range of factors acting in concert, machine learning was applied in this study. Specifically, random forest algorithm, which is based on decision tree theory, was employed because it is insensitive to multicollinearity, is robust to missing and unbalanced data, and provides reasonable predictive results. We identified the key factors affecting carbon intensity in China using random forest algorithm and analyzed the evolution in the key factors from 1980 to 2017. The dominant factors affecting carbon intensity in China from 1980 to 1991 included the scale and proportion of energy-intensive industry, the proportion of fossil fuel-based energy, and technological progress. The Chinese economy developed rapidly between 1992 and 2007; during this time, the effects of the proportion of service industry, price of fossil fuel, and traditional residential consumption on carbon intensity increased. Subsequently, the Chinese economy entered a period of structural adjustment after the 2008 global financial crisis; during this period, reductions in emissions and the availability of new energy types began to have effects on carbon intensity, and the importance of residential consumption increased. The results suggest that optimizing the energy and industrial structures, promoting technological advancement, increasing green consumption, and reducing emissions are keys to decreasing carbon intensity within China in the future. These approaches will help achieve the goal of reducing carbon intensity to 60%-65% of the 2005 level by 2030.
Cyberspace is a new spatial realm of activities involving both humans and data, and it has become a cornerstone of the national security of every country. A scientific understanding of cyberspace is essential for analyzing cyberspace incidents, governing cyberspace and ensuring cybersecurity. Accordingly, cyberspace has become a new field of geographic research in the Information Age. Against the backdrop of fierce international competition over cyberspace, there has been an urgent need to strengthen research between the fields of geography and cybersecurity, leading to theoretical and methodological innovations that have created the sub-discipline of cyberspace geography. Cyberspace geography (CG) extends geographical research from real spaces to virtual spaces, and its theoretical basis is the evolution of the traditional geographic human-land relationship theory into a human-land-network relationship theory. CG research includes constructing mapping relationships between cyberspace and real space, redefining the traditional geographic concepts of distance and regions for cyberspace, creating a language, models and methodologies for visually representing cyberspace, drawing maps of cyberspace, and researching the principles governing the evolution of cyberspace structures and behaviors. The technical methods of CG include collecting and integrating data on elements of cyberspace, visually representing cyberspace and conducting cyberspace situational and behavioral intelligence awareness. Intelligence awareness covers cyberspace situational status assessments, network hotspot event dissemination and traceability analysis, and network event situational simulations and risk predictions. CG offers new perspectives on the scientific understanding of cyberspace, the development of disciplines such as geography and cybersecurity, and the creation of national cybersecurity prevention and control mechanisms as well as a community of common future in cyberspace.
The urban-rural transformation from dichotomy to integration is a gradual process. Like rural areas in many countries, Chinese rural society is experiencing a decline in all spheres due to depopulation, aging, lack of economic opportunity, and so on. Aiming at solving the serious rural issues, China proposed the implementation of a rural revitalization strategy and the promotion of an integrated urban-rural development for the first time in 2017. This proposal marks the transformation of the urban-rural relationship, and the integrated urban-rural development reflects a significant conceptual change. Researches on issues of rural decline are urgently needed to determine the most effective method for rural revitalization and development from the perspective of the urban-rural dynamics. In this context, this paper focuses on studying the theory, technology and management of rural revitalization and development. We construct a theoretical framework for urban-rural integration based on population-land-industry-right between the urban and rural systems, regarding land engineering for land capacity building as the technical support and the rural land system reform and reconstruction as the policy support for management. This research will provide theoretical support for the implementation of China’s rural revitalization strategy.
The vertical distribution and exchange mechanisms of soil organic and inorganic carbon (SOC, SIC) play an important role in assessing carbon (C) cycling and budgets. However, the impact of land use through time for deep soil C (below 100 cm) is not well known. To investigate deep C storage under different land uses and evaluate how it changes with time, we collected soil samples to a depth of 500 cm in a soil profile in the Gutun watershed on the Chinese Loess Plateau (CLP); and determined SOC, SIC, and bulk density. The magnitude of SOC stocks in the 0-500 cm depth range fell into the following ranking: shrubland (17.2 kg m-2) > grassland (16.3 kg m-2) > forestland (15.2 kg m-2) > cropland (14.1 kg m-2) > gully land (6.4 kg m-2). The ranking for SIC stocks were: grassland (104.1 kg m-2) > forestland (96.2 kg m-2) > shrubland (90.6 kg m-2) > cropland (82.4 kg m-2) > gully land (50.3 kg m-2). Respective SOC and SIC stocks were at least 1.6- and 2.1-fold higher within the 100-500 cm depth range, as compared to the 0-100 cm depth range. Overall SOC and SIC stocks decreased significantly from the 5th to the 15th year of cultivation in croplands, and generally increased up to the 70th year. Both SOC and SIC stocks showed a turning point at 15 years cultivation, which should be considered when evaluating soil C sequestration. Estimates of C stocks greatly depends on soil sampling depth, and understanding the influences of land use and time will improve soil productivity and conservation in regions with deep soils.
Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems. As a process-oriented modelling approach, agent based model (ABM) plays an important role in revealing the driving forces of land change and understanding the process of land change. This paper starts from three aspects: The theory, application and modeling framework of ABM. First, we summarize the theoretical basis of ABM and introduce some related concepts. Then we expound the application and development of ABM in both urban land systems and agricultural land systems, and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region, China. On the basis of combing the ABM modeling protocol, we propose the land system ABM modeling framework and process from the perspective of agents. In terms of urban land use, ABM research initially focused on the study of urban expansion based on landscape, then expanded to issues like urban residential separation, planning and zoning, ecological functions, etc. In terms of agricultural land use, ABM application presents more diverse and individualized features. Research topics include farmers’ behavior, farmers’ decision-making, planting systems, agricultural policy, etc. Compared to traditional models, ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data. However, due to its unique bottom-up model structure, ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.
The climate change and Land Use/Land Cover (LULC) change both have an important impact on the rainfall-runoff processes. How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources. In this research, the SWAT (Soil and Water Assessment Tool) model was established for the Jinsha River Basin, and the method of scenarios simulation was used to study the runoff response to climate change and LULC change. Furthermore, the climate variables exported from 7 typical General Circulation Models (GCMs) under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017-2050. Results showed that: (1) During the past 57 years, the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious. (2) Compared with the significant increase of temperature in the Jinsha River Basin, the LULC change was very small. (3) During the historical period, the LULC change had little effect on the hydrological processes in the basin, and climate change was one of the main factors affecting runoff. (4) In the context of global climate change, the precipitation, temperature and runoff in the Jinsha River Basin will rise in 2017-2050 compared with the historical period. This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.
Despite the increasing depletion of the groundwater at the Zhangjiakou aquifer system in the northwest of Beijing-Tianjin-Hebei region, little information is available on the hydrological process of groundwater in this region. In this study, we utilized water isotopes composition (δ18O, δD and3H) of groundwater, river and precipitation to identify the characteristics of hydrochemistry, groundwater age and recharge rates in different watersheds of the Zhangjiakou area. Results showed that the river water and groundwater could be characterized as HCO3-Mg·Na, HCO3·Cl-Na and HCO3-Mg·Na, HCO3·Cl-Na, HCO3·Cl-Na·Mg types, respectively. The δD and δ18O values in precipitation were linearly correlated, which is similar to the Global Meteorological Water Line (GMWL). Furthermore, the decreasing values of the δD and δ18O from precipitation to surface water and groundwater indicate that groundwater is mainly recharged by atmospheric precipitation. In addition, the variation of3H concentration with depth suggests that groundwater shallower than around 100 m is generally modern water. In contrast, groundwater deeper around 100 m is a mixture of modern and old waters, which has longer residence times. Groundwater showed a relatively low tritium concentration in the confined aquifers, indicating the groundwater recharged might be relatively old groundwater of over 60 years. The flow velocity of the groundwater in the study area varied from 1.10 to 2.26 m/a, and the recharge rates ranged from 0.034 to 0.203 m/a. The obtained findings provide important insights into understanding the groundwater recharge sources and hydrochemistry in the Zhangjiakou area, in turn developing a sustainable groundwater management plan.
In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors, the urban surface temperature patterns of Changsha in 2000, 2009 and 2016 are retrieved based on multi-source spatial data (Landsat 5 and Landsat 8 satellite image data, POI spatial big data, digital elevation model, etc.), and 12 natural and human factors closely related to urban thermal environment are quickly obtained. The standard deviation ellipse and spatial principal component analysis (PCA) methods are used to analyze the effect of urban human residential thermal environment and its influencing factors. The results showed that the heat island area increased by 547 km2 and the maximum surface temperature difference reached 10.1℃ during the period 2000-2016. The spatial distribution of urban heat island was mainly concentrated in urban built-up areas, such as industrial and commercial agglomerations and densely populated urban centers. The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs. There were multiple high-temperature centers, such as Wuyi square business circle, Xingsha economic and technological development zone in Changsha County, Wangcheng industrial zone, Yuelu industrial agglomeration, and Tianxin industrial zone. From 2000 to 2016, the main axis of spatial development of heat island remained in the northeast-southwest direction. The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9° in 2000-2009. The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9° in 2009-2016. On the whole, the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity. Through the PCA method, it was concluded that landscape pattern, urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha. The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors. The temperature would rise by 0.293℃ under the synthetic effect of human and natural factors. Due to the complexity of factors influencing the urban thermal environment of human settlements, the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment, deepen the understanding of the causes of urban heat island effect, and clarify the correlation between human and natural factors, so as to provide scientific supports for the improvement of the quality of urban human settlements.
New Urban Districts (NUDs) are the important spatial carriers to promote urban expansion or transformation. Since the 1990s, they have been playing a more and more crucial role in China’s urbanization. For NUDs in the strict sense we found that: 96% to the east of Hu Line; 56% within the municipal districts; 64% within 36 km from their every city center and below the area of 423 km 2. The regional distribution follows significant spatial difference as “Eastern Region (50%) - Central Region (42%) - Western Region (8%)”, and the provinces with the largest number of NUDs are Guangdong, Henan, Zhejiang, Liaoning, and Jiangsu. Furthermore, their interesting constructed process highlights the typical characteristics of spatial production and spatial dialectic. This paper uses the theory of the production of space, and discovers that the growth of NUDs is a rapid ternary dialectical process of spatial production: “representations of space” is guided by the top-down governmental power; “spatial practice” is reflected in the hierarchical and regional difference of spatial elements, such as the type, pattern, distance and area of NUD; “spaces of representation” embodies the tension between governmental power and urban development rights, as well as the countermeasure mechanism. The extensibility of spatiotemporal sequences ensures the unity and continuity of spatial (re)production of NUDs. However, this is also facing a series of challenges like the management coordination of administrative division and the increasing unbalanced or inadequate development. Thus, critically rethinking the evolution of NUD is the key basis for achieving sustainable urban renewal and regional orderly development in the new era.
The countries throughout the Belt and Road region account for more than 60% of the world’s population and half of the global economy. Future changes in this area will have significant influences on the global economic growth, industrial structure and resource allocation. In this study, the proportion of the urban population to the total population and the gross domestic product were used to represent the levels of urbanization and economic development, respectively. The population, urbanization and economic levels of the Belt and Road countries for 2020-2050 were projected under the framework of the IPCC's shared socioeconomic pathways (SSPs), and the following conclusions are drawn. (1) The population, urbanization and economic levels in the Belt and Road region will likely increase under all five pathways. The population will increase by 2%-8%/10a during 2020-2050 and reach 5.0-6.0 billion in 2050. Meanwhile, the urbanization rate will increase by 1.4%-7.5%/10a and reach 49%-75%. The GDP will increase by 17%-34%/10a and reach 134-243 trillion USD. (2) Large differences will appear under different scenarios. The SSP1 and SSP5 pathways demonstrate relatively high urbanization and economic levels, but the population size is comparatively smaller; SSP3 shows the opposite trend. Meanwhile, the economy develops slowly under SSP4, but it has a relatively high urbanization level, while SSP2 exhibits an intermediate trend. (3) In 2050, the population will increase relative to 2016 in most countries, and population size in the fastest growing country in Central Asia and the Middle East countries will be more than double. Urbanization will develop rapidly in South Asia, West Asia and Central Asia, and will increase by more than 150% in the fastest growing countries. The economy will grow fastest in South Asia, Southeast Asia and West Asia, and increase by more than 10 times in some counties with rapid economic development.
Understanding the interactions between humans and nature in the Anthropocene is central to the quest for both human wellbeing and global sustainability. However, the time-space compression, long range interactions, and reconstruction of socio-economic structures at the global scale all pose great challenges to the traditional analytical frameworks of human-nature systems. In this paper, we extend the connotation of coupled human and natural systems (CHANS) and their four dimensions—space, time, appearance, and organization, and propose a novel framework: “Coupled Human and Natural Cube” (CHNC) to explain the coupling mechanism between humans and the natural environment. Our proposition is inspired by theories based on the human-earth areal system, telecoupling framework, planetary urbanization, and perspectives from complexity science. We systematically introduce the concept, connotation, evolution rules, and analytical dimensions of the CHNC. Notably there exist various “coupling lines” in the CHNC, connecting different systems and elements at multiple scales and forming a large, nested, interconnected, organic system. The rotation of the CHNC represents spatiotemporal nonlinear fluctuations in CHANS in different regions. As a system continually exchanges energy with the environment, a critical phase transition occurs when fluctuations reach a certain threshold, leading to emergent behavior of the system. The CHNC has four dimensions—pericoupling and telecoupling, syncoupling and lagcoupling, apparent coupling and hidden coupling, and intra-organization coupling and inter-organizational coupling. We mainly focus on the theoretical connotation, research methods, and typical cases of telecoupling, lagcoupling, hidden coupling, and inter-organizational coupling, and put forward a human-nature coupling matrix to integrate multiple dimensions. In summary, the CHNC provides a more comprehensive and systematic research paradigm for understanding the evolution and coupling mechanism of the human-nature system, which expands the analytical dimension of CHANS. The CHNC also provides a theoretical support for formulating regional, sustainable development policies for human wellbeing.
The concept of ‘Beautiful China’ is a new goal of ecological construction in the new era of socialism and aims to meet the needs of people as they strive for a better life. National land spatial planning is one major component of the Chinese state’s overall planning for various spatial types. The concept of ‘Beautiful China’ is thus a leading goal of Chinese development in the second centenary. The background of this concept aims for ‘ecological beauty’ as well as the combined beauty of ‘economy-politics-culture-society-ecology.’ The construction of ‘Beautiful China’ therefore necessitates a differentiated evaluation index system that is built on the basis of local conditions. This concept is intimately related to land spatial planning and the idea of Beautiful China guides an important direction for this planning which itself provides an important mechanism and spatial guarantee for construction. The establishment of land spatial planning nevertheless needs to strengthen further discussion of the regional system of human-land relationship, point axis system, main functional division, sustainable development, resources and environmental carrying capacity as well as new urbanization, and the rural multi-system. The aim of this paper is to summarize current thinking in land spatial planning, scientifically analyze the natural geographical conditions, the socioeconomic development, the interrelationship of the land space, plan the goal, vision and path of land space, encourage the public to participate in and carry out dynamic evaluation, build an intelligent system platform for land and spatial planning to realize the goal of ‘Beautiful China’ from a geographical perspective. And they can also present key ideas relating to the compilation and implementation of land spatial planning.
Frequent chilling injury has serious impacts on national food security and in northeastern China heavily affects grain yields. Timely and accurate measures are desirable for assessing associated large-scale impacts and are prerequisites to disaster reduction. Therefore, we propose a novel means to efficiently assess the impacts of chilling injury on soybean. Specific chilling injury events were diagnosed in 1989, 1995, 2003, 2009, and 2018 in Oroqen community. In total, 512 combinations scenarios were established using the localized CROPGRO-Soybean model. Furthermore, we determined the maximum wide dynamic vegetation index (WDRVI) and corresponding date of critical windows of the early and late growing seasons using the GEE (Google Earth Engine) platform, then constructed 1600 cold vulnerability models on CDD (Cold Degree Days), the simulated LAI (Leaf Area Index) and yields from the CROPGRO-Soybean model. Finally, we calculated pixel yields losses according to the corresponding vulnerability models. The findings show that simulated historical yield losses in 1989, 1995, 2003 and 2009 were measured at 9.6%, 29.8%, 50.5%, and 15.7%, respectively, closely (all errors are within one standard deviation) reflecting actual losses (6.4%, 39.2%, 47.7%, and 13.2%, respectively). The above proposed method was applied to evaluate the yield loss for 2018 at the pixel scale. Specifically, a sentinel-2A image was used for 10-m high precision yield mapping, and the estimated losses were found to characterize the actual yield losses from 2018 cold events. The results highlight that the proposed method can efficiently and accurately assess the effects of chilling injury on soybean crops.
This paper investigated spatial structures of 3418 national protected areas (NPAs) grouped into 13 types using GIS and quantitative analysis, including point patterns, Ripley’s K function, hotspot clustering, quadrat analysis, and Gini coefficient. Spatial accessibility was calculated for all NPAs from matrix raster data using cost weighted distance on the ArcGIS platform. The results are as follows: (1) The NNI of NPAs is 0.515, Gini is 0.073, all of which indicates distribution was shown to be a spatially dependent agglomeration, and more balanced in the provinces. The national key parks and the national water conservancy scenic spots had present the strongest aggregation, with NNI of 0.563 and 0.561 respectively, and K index indicates reducing aggregation when distance exceeds 600 km. (2) The national forest parks account for the largest proportion of 22.87% of all NPAs, and the world biosphere reserves the least of 0.77%. The number of NPAs in Shandong with 240 had been the largest one in all the provinces, while Tianjin had the least number including 9 NPAs. (3) There is only one hot spot in the first-class zone, 5 in the second-class zones, and 51 in the third-class zones, which indicates NPAs are also aggregated at microscopic scales. (4) The hotspot NPA regions were mainly concentrated in the middle and lower reaches of the Yellow and Yangtze rivers, east of 100°E. High density of NPAs were generally in flat, water-rich, broad-leaved forest dominated plains and low mountain areas, with fertile soil, pleasant weather, long cultural history, and high transportation accessibility. (5) Average NPA accessible time is 60.05 min, with 70.76% regions being within 60 min, and the furthest was 777 min. The distribution of accessibility was positively related to the traffic lines. Interdepartmental protectionism has meant the various departments developed different management systems, standards, and technical specifications.
Systematically revealing the impact of cultivated land fragmentation (CLF) on the geographical agglomeration pattern of agricultural specialization (AS) has positive significance for national agricultural production management. Based on the data of the second national land survey and agricultural production, this study has explored the impact of CLF on spatial heterogeneity of agricultural agglomeration in China by comprehensively using the Theil index, ordinary least square model and geographically weighted regression. Results showed that: (1) the regional differentiation of the CLF in China is obvious, and the cultivated land fragmentation index is generally characterized by increasing pattern from northwest to southeast. (2) Spatially, the development level of AS in China has formed three high-value clusters in the Northeast China Plain, the Qinghai-Tibet Plateau, and the middle of the Middle-lower Yangtze Plain; and the low-value contiguous areas centered on the Yunnan-Guizhou Plateau and the Sichuan Basin and surrounding regions, with significant spatial differences. The contribution of grain crops, economic crops, and vegetables and melon to the level of AS was 74.63%, 9.09%, and 16.28%, respectively, and the pattern of agricultural geographical aggregation dominated by grain crops has primarily taken in shape. (3) CLF is significantly negatively correlated with AS, and every 1% increase in the degree of CLF will result in a decrease of about 0.2% in AS. However, the impact of CLF on the geographic agglomeration of different crop categories or groups varies significantly. Among them, CLF has a prominent impact on the specialization level of grain crops and vegetables and melon. Each 1% increase in the CLF will reduce the specialization level of grain crops by 0.38%, and increase the level of vegetables and melon by about 0.22%. (4) According to the landscape characteristics of cultivated land, the degree of spatial division and agglomeration of cultivated land patches have a significant impact on the formation of geographical agglomeration pattern of AS, and the intensity and direction of influence show significant regional differentiation, while the patch size has no significant impact.
To resolve conflicts between development and the preservation of the natural environment, enable economic transformation, and achieve the global sustainable development goals (SDGs), green development (GD) is gradually becoming a major strategy in the construction of an ecological civilization and the ideal of building a “beautiful China”, alongside the transformation and reconstruction of the global economy. Based on a combination of the concept and implications of GD, we first used the Slacks Based Model with undesirable outputs (SBM-Undesirable), the Theil index, and the spatial Markov chain to measure the spatial patterns, regional differences, and spatio-temporal evolution of urban green development efficiency (UGDE) in China from 2005 to 2015. Second, by coupling natural and human factors, the mechanism influencing UGDE was quantitatively investigated under the framework of the human-environment interaction. The results showed that: (1) from 2005 to 2015, the UGDE increased from 0.475 to 0.523, i.e., an overall increase of 10%. In terms of temporal variation, there was a staged increase, with its evolution having the characteristics of a “W-shaped” pattern. (2) The regional differences in UGDE followed a pattern of eastern > central > western. For different types of urban agglomeration, the UGDE had inverted pyramid cluster growth characteristics that followed a pattern of “national level > regional level > local level”, forming a stable hierarchical scale structure of “super cities > mega cities > big cities > medium cities > small cities”. (3) UGDE in China has developed with significant spatial agglomeration characteristics. High-efficiency type cities have positive spillover effects, while low-efficiency cities have negative effects. Different types of urban evolution processes have a path dependence, and a spatial club convergence phenomenon exists, in which areas with high UGDE are concentrated and drive low UGDE elsewhere. (4) Under the framework of regional human-environment interaction, the degree of human and social influence on UGDE is greater than that of the natural background. The economic strength, industrial structure, openness, and climate conditions of China have positively promoted UGDE.
Sensitivity assessment is useful for monitoring land desertification. Research into how to prevent and control desertification is also important. In the arid region of northwest China, desertification is becoming worse and is a serious problem that affects local sustainable development. Based on remote-sensing and geographic information system technology, this study establishes a “soil-terrain-hydrology-climate-vegetation” desertification sensitivity comprehensive evaluation system to reflect the spatiotemporal changes of land desertification, and proposes a spatial distance model to calculate a desertification sensitivity index. The spatiotemporal change characteristics of land desertification sensitivity in northwest China are quantitatively assessed from 2000 to 2017. Moreover, the main driving factors are analyzed using the geographical detector method. The results show the following. (1) Terrain, soil, climate, vegetation and hydrology affect and restrict each other, and constitute the background conditions of the distributions and changes of sensitivity to desertification in northwest China. (2) Desertification sensitivity generally displays a low distribution characteristic on the periphery of the area and a high one in the interior. The low-sensitivity regions are mainly in the five major mountain ranges (Altai Mountains, Tianshan Mountains, Kunlun Mountains, Altun Mountains and Qilian Mountains), while the high-sensitivity regions are mainly in regions such as the Junggar Basin, the Tarim Basin and the Inner Mongolia Plateau, as well as the Taklimakan Desert, Badain Jaran Desert and Tengger Desert. The spatial distribution of desertification sensitivity is obviously regional, and the high- and low-sensitivity regions have clear boundaries and a concentrated distribution. (3) With regard to spatiotemporal evolution, changes in desertification sensitivity since 2000 have been predominantly stable, and the overall sensitivity has displayed a slowly decreasing trend, indicating that potential desertification regions are decreasing annually and that some achievements have been made in the control of regional desertification. (4) Soil and climate play a direct role in the driving factors of desertification in northwest China, and these have been found to be the most important influential factors. Vegetation is the most active and basic factor in changing the sensitivity. In addition, topography and hydrology play a role in restricting desertification changes. Socio-economic factors are the most rapid factors affecting regional desertification sensitivity, and their impacts tend to be gradually increasing. In general, desertification has been effectively controlled in northwest China, and positive results have been achieved in such control. However, against the backdrop of intensified global climate change, increasingly prominent human activities and new normals of socio-economic development, the monitoring, assessment and control of desertification in China still have a long way to go.
With the introduction of the concept of land use transition into China, related researches have been carried out extensively in the past two decades, which enrich the knowledge of land system science. This paper describes the development of research on land use transitions in China from the perspectives of conceptual connotations, theoretical model, research methods, and research progress and prospects. With the in-depth investigation of land use transitions, the concept and connotations of land use morphology are developed and encapsulated as two kinds, i.e., dominant morphology and recessive morphology. The dominant morphology refers to the land use structure of a certain region over a certain period of time, with features such as the quantity and spatial pattern of land use types. While the recessive morphology includes the land use features in the aspects of quality, property rights, management mode, input, output and function. Accordingly, the concept of land use transition is further developed, and the theoretical model of regional land use transitions is established. Thereafter, three innovative integrated approaches to study land use transitions are put forward, i.e., multidisciplinary research framework for recessive land use transition, transect and horizontal comparison. To date, there have been 62 Ph.D. and 166 M.S. dissertations on the topic of “land use transition” in China. During 2002-2019, the National Natural Science Foundation of China has funded 48 research programs on the theme of “land use transition”. As such, the Chinese scholars have adapted the concept derived from western literature to the situations and experiences in China.
The pattern for utilization of rural space is closely related to rural transformation development (RTD). The problem of rural space utilization is an important manifestation of the uncoordinated relationship between land use patterns and rural development status during a transformation period. Considering the rural space utilization issue, this article seeks to analyze the interaction mechanisms between land use transition (LUT) and rural spatial governance and then build a rural spatial governance analysis framework based on LUT. Also, the paper explores the internal relationship between rural spatial governance and rural vitalization and discusses the research prospective of the interaction. The study found that: (1) Rural space utilization has systemic problems such as limited development space, ill-defined ownership and poor organization, which have become important obstacles for rural development. (2) The uncoordinated relationship between LUT and RTD is an important reason for the dilemma surrounding rural space utilization. (3) The LUT provides a basis for determining the timing of rural spatial governance, specifying spatial governance objectives, and clarifying rural spatial governance methods. (4) The construction of a comprehensive analysis framework of “matter-ownership-organization” of rural space based on the LUT has created conditions for the orderly promotion of rural spatial governance. (5) Rural spatial governance which facilitates the integration of urban-rural development is an important foundation for rural vitalization. (6) Interaction analysis of LUT, RTD and rural spatial governance is conducive to facilitating research on the operational mechanism of rural regional systems and to expanding the research field of rural geography.
The Yangtze River floodplain is critical for migratory waterbirds along the East Asian-Australasian Flyway (EAAF). Greater awareness of its global importance is urgently needed to ensure waterbird populations remain in favourable conservation status, as well as the enhancement of wider wetland biodiversity within this region. The designation of protected wetland areas and building a green ecological corridor in the Yangtze floodplain is now becoming a critical issue of interest to the Chinese government. Priority sites in this area were identified based on the criteria used to identify sites that qualify as Wetlands of International Importance (Ramsar Sites) and Important Bird and Biodiversity Areas (IBAs) by using multi-source data. The results show that 140 of the sites surveyed are priority sites. The Importance Index (I) for the whole floodplain decreased slightly from 2001-2005 and an unbalanced distribution pattern is evident with Jiangxi and Hunan provinces significantly higher than the other provinces in the floodplain. Although more than 60% of the priority sites are currently located outside protected areas, the average Conservation Effectiveness Index (C) of the whole floodplain is 75.6%, which suggests the coverage of protected areas for most wintering waterbird population is reasonable. Conservation of the Yangtze River floodplain needs to be further strengthened due to declining waterbird abundances and the mismatch between the distribution of protected areas and their importance for wintering waterbirds. A comprehensive system for priority site identification and protection and scientific review is needed. Multi-sourced data from regular, systematic and coordinated monitoring of waterbird distribution and abundance across the EAAF, as well as national scale citizen science programmes are also critically important.
The Qinling Mountains is not only the geographical boundary between North and South China, but also the boundary between subtropical and warm temperate zones. It plays an important role in the geo-ecological pattern of China. However, there is controversy about the specific location of this geographical boundary in academic community due to the complexity, transition and heterogeneity of the transitional zone, as well as the differences in the delimitation indicators and research purposes. To further reveal the characteristics of the North-South transitional zone and clarify the specific location of the geo-ecological boundary between North and South China, combined with SRTM topographic data, temperature and precipitation data, Pinus massoniana forest and Pinus tabulaeformis forest, which represent subtropical coniferous forest in South China and temperate coniferous forest in North China respectively, were chosen to analyze their spatial distributions in the Qinling-Daba Mountains and the climatic conditions at their boundary with the climatic indexes of annual precipitation, the coldest month (January) average temperature, the warmest month (July) average temperature and the annual average temperature. The results show that: (1) Pinus massoniana and Pinus tabulaeformis forests and the climate indicators of their boundary can be used as one of the vegetation-climate indexes for the delimitation of subtropical and warm temperate zones. The boundary between the subtropical coniferous forest (Pinus massoniana forest) and temperate coniferous forest (Pinus tabulaeformis forest) is located along the south slope of Funiu Mountain to the north edge of Hanzhong Basin (the south slope of Qinling Mountains) at an altitude of 1000-1200 m, where the climatic indictors are stable: the annual precipitation is about 750-1000 mm, the annual average temperature is about 12-14℃, the coldest monthly average temperature is 0-4℃, and the warmest monthly average temperature is about 22-26℃. (2) It can be more scientifically to delimitate the boundary of subtropical and warm temperate zones in China by comprehensively considering the vegetation-climate indicators. Additionally, the boundary between subtropical and warm temperate zones in Qinling-Daba Mountains should be a transitional zone consisting of the boundaries of coniferous forests, broad-leaved forests and shrubs between subtropical and warm temperate zones. The results provide a scientific basis for the selection of delimitation index of subtropical and warm temperate zones.
Exploring the spatio-temporal dynamics of poverty is important for research on sustainable poverty reduction in China. Based on the perspective of development geography, this paper proposes a panel vector autoregressive (PVAR) model that combines the human development approach with the global indicator framework for Sustainable Development Goals (SDGs) to identify the poverty-causing and the poverty-reducing factors in China. The aim is to measure the multidimensional poverty index (MPI) of China’s provinces from 2007 to 2017, and use the exploratory spatio-temporal data analysis (ESTDA) method to reveal the characteristics of the spatio-temporal dynamics of multidimensional poverty. The results show the following: (1) The poverty-causing factors in China include the high social gross dependency ratio and crop-to-disaster ratio, and the poverty-reducing factors include the high per capita GDP, per capita social security expenditure, per capita public health expenditure, number of hospitals per 10,000 people, rate of participation in the new rural cooperative medical scheme, vegetation coverage, per capita education expenditure, number of universities, per capita research and development (R&D) expenditure, and funding per capita for cultural undertakings. (2) From 2007 to 2017, provincial income poverty (IP), health poverty (HP), cultural poverty (CP), and multidimensional poverty have been significantly reduced in China, and the overall national poverty has dropped by 5.67% annually. there is a differentiation in poverty along different dimensions in certain provinces. (3) During the study period, the local spatial pattern of multidimensional poverty between provinces showed strong spatial dynamics, and a trend of increase from the eastern to the central and western regions was noted. The MPI among provinces exhibited a strong spatial dependence over time to form a pattern of decrease from northwestern and northeastern China to the surrounding areas. (4) The spatio-temporal networks of multidimensional poverty in adjacent provinces were mainly negatively correlated, with only Shaanxi and Henan, Shaanxi and Ningxia, Qinghai and Gansu, Hubei and Anhui, Sichuan and Guizhou, and Hainan and Guangdong forming spatially strong cooperative poverty reduction relationships. These results have important reference value for the implementation of China’s poverty alleviation strategy.
Physical geography is a basic research subject of natural sciences. Its research object is the natural environment which is closely related to human living and development, and China’s natural environment is complex and diverse. According to national needs and regional development, physical geographers have achieved remarkable achievements in applied basis and applied research, which also has substantially contributed to the planning of national economic growth and social development, the protection of macro ecosystems and resources, and sustainable regional development. This study summarized the practice and application of physical geography in China over the past 70 years in the following fields: regional differences in natural environments and physical regionalization; land use and land cover changes; natural hazards and risk reduction; process and prevention of desertification; upgrading of medium- and low-yield fields in the Huang-Huai-Hai region; engineering construction in permafrost areas; geochemical element anomalies and the prevention and control of endemic diseases; positioning and observation of physical geographical elements; and identification of geospatial differentiation and geographical detectors. Furthermore, we have proposed the future direction of applied research in the field of physical geography.
Climate change is an important factor affecting the sustainable development of tourist destinations. Based on the monthly observation data of the main meteorological stations on the ground in Tibet from 1960 to 2015, this paper constructs a tourism climate index model. This index is used to quantitatively evaluate the tourism climate changes in Tibet, and investigate the impact of climate change on tourism. The results show that from 1960 to 2015, the temperature in Tibet increased by 1.35°C, and the tourism climate index changed significantly, especially in the regions of Changtang, Ngari and Kunlun Mountain. The fluctuation of temperature-humidity index, wind-chill index and index of clothing of these areas was larger than that of other regions. The changes of each index in different months are different, where spring observes larger changes while summer observes smaller changes. The tourism climate index in northwestern Tibet has increased, and the climate comfort period is expanding. In southeastern Tibet, the comfort level has declined and the comfort level in the central part has been slowly increasing. The comfort index in the southeastern part of Tibet has gradually declined, and the comfort index in central Tibet has slowly increased. According to the comprehensive assessment method including temperature and humidity index, wind-chill index, index of clothing and altitude adaptability index, the types of tourism climate index in Tibet can be divided into reduced, low-speed growth, medium-speed growth and rapid growth. Different regions should adopt alternative tourism products, strengthen energy conservation and emission reduction technology applications and green infrastructure construction, and appropriately control the scale of tourism activities so as to adapt to and mitigate the impact of climate change on tourist destinations.
The reform of global production mode and social system accelerate the process of urbanization, and the urban-rural factors accelerate rural space diversification. Based on the space production theory and game theory, this paper analyzed the space diversification process and its influence on Beicun village. The results show that: (1) In the past 30 years, the development of Beicun has experienced three stages: agricultural development, industrial development, and service industrial development. The industrial structure has changed from single to diverse. The transformation of agricultural decentralization to rural community has been realized. (2) Accompanying the rural economic development transformation, the land use type and structure of Beicun has diversified. The spatial relationship of various types of land use was complicated and gave rise to new characteristics of mixed land for commercial and residential use, and industrial and commercial use, gradually forming a circular spatial layout structure model of public service facilities, traditional residential areas and modern residential areas, commercial areas, agricultural and industrial areas. (3) Rural space diversification was mainly due to the intervention of new industries and the transformation of leading industries. The endogenous land transferring mechanism and exogenous urban capital jointly promoted the industrialization process, and the market power promoted the transformation of industry into the service industry. (4) The industrialization process promoted the functional replacement of historical buildings by village organizations. It changed the social relations of the village with the blood clan and geography oriented, and produced the occupational relation between migrant workers and urban low-income groups. (5) The multi-differentiation of suburban rural space followed the game logic of capital and land interests. The rural community played a key mediation in the competition for space and the game of interests among local villagers, farmers, economic cooperation, industrial operators, and service owners.
Giant clam shell mining (GCSM), a unique phenomenon occurring at remote coral reefs in the southern South China Sea (SCS), forms striking scars on the reef flats and damages the reef flat substrate. Through image analyses at three times (2004.02.02, 2014.02.26, and 2019.04.10) and in situ surveys at Ximen Reef, a representative site that has experienced GCSM, we quantified the GCSM-generated substrate damage and the corresponding recovery. GCSM was estimated to have occurred sometime between 2012 and 2014, causing reduction in live coral subarea and formation of micro-relief as trenches and mounds. GCSM-generated damage was restricted to the reef flat. After GCSM, coral and algae subarea increased, and the trenches and mounds tended to be filled and eroded, representing a natural recovery of the substrate. The legal prohibition on human disturbances at the coral reefs contributed to substrate recovery at Ximen Reef. This case also implied that recovery of the other coral reefs that suffered from GCSM is possible.
A largely unexplored application of “Big Data” in urban contexts is using human mobility data to study temporal heterogeneity in intercity travel networks. Hence, this paper explores China’s intercity travel patterns and their dynamics, with a comparison between weekdays and holidays, to contribute to our understanding of these phenomena. Using passenger travel data inferred from Tencent Location Big Data during weekdays (April 11-15, 2016) and National Golden Week (October 1-7, 2016), we compare the spatial patterns of Chinese intercity travel on weekdays and during Golden Week. The results show that the average daily intercity travel during Golden Week is significantly higher than that during weekdays, but the travel distance and degree of network clustering are significantly lower. This indicates temporal heterogeneity in mapping the intercity travel network. On weekdays, the three major cities of Beijing, Shanghai, and Guangzhou take prominent core positions, while cities that are tourism destinations or transportation hubs are more attractive during Golden Week. The reasons behind these findings can be explained by geographical proximity, administrative division (proximity of cultural and policy systems), travel distance, and travel purposes.
With rapid globalization, industrial parks are playing an increasingly important role in the national and regional development. Since the Belt and Road Initiative (BRI) was put forward, national-level overseas industrial parks of China have emerged with new development features and trends. It is of great importance to carry out a comparative study on domestic and overseas industrial parks of China. Based on the perspective of spatiotemporal evolution, this paper compares and analyzes national-level overseas industrial parks along the Belt and Road (B&R) and domestic industrial parks of China. In time, China’s industrial parks have experienced four stages with distinctive state-led characteristic. There are different development paths and modes for overseas industrial parks along the B&R and domestic industrial parks. In space, the national-level overseas industrial parks are invested and constructed by Chinese enterprises (mostly from the coastal developed cities), and mainly distributed in the countries along the B&R. Through typical cases comparison of Thai-Chinese Rayong Industrial Zone and Tianjin Economic-Technological Development Area, the paper finds that national-level overseas industrial parks are basically market-driven and concentrated in traditional advantageous industries, while domestic industrial parks are mainly government-led high-tech industries. Localization of overseas industrial parks and remote coupling with domestic industrial parks become very important.
In this paper, meteorological industry standard, daily mean temperature, and an improved multiple regression model are used to calculate China’s climatic seasons, not only to help understand their spatio-temporal distribution, but also to provide a reference for China’s climatic regionalization and crop production. It is found that the improved multiple regression model can accurately show the spatial distribution of climatic seasons. The main results are as follows. There are four climatic seasonal regions in China, namely, the perennial-winter, no-winter, no-summer and discernible regions, and their ranges basically remained stable from 1951 to 2017. The cumulative anomaly curve of the four climatic seasonal regions clarifies that the trend of China’s climatic seasonal regions turned in 1994, after which the area of the perennial-winter and no-summer regions narrowed and the no-winter and discernible regions expanded. The number of sites with significantly reduced winter duration is the largest, followed by the number of sites with increased summer duration, and the number of sites with large changes in spring and autumn is the least. Spring advances and autumn is postponed due to the shortened winter and lengthened summer durations. Sites with significant change in seasonal duration are mainly distributed in Northwest China, the Sichuan Basin, the Huanghe-Huaihe-Haihe (Huang-Huai-Hai) Plain, the Northeast China Plain, and the Southeast Coast.