In 2007, China surpassed the USA to become the largest carbon emitter in the world. China has promised a 60%-65% reduction in carbon emissions per unit GDP by 2030, compared to the baseline of 2005. Therefore, it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies. This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000-2013 using nighttime lighting data and carbon emission statistics data. By applying the Exploratory Spatial-Temporal Data Analysis (ESTDA) framework, this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001-2013. The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units. The results show that, firstly, high accuracy was achieved by the model in simulating carbon emissions. Secondly, the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82% and 5.72%, respectively. The overall carbon footprints and carbon deficits were larger in the North than that in the South. There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units. Thirdly, the relative lengths of the Local Indicators of Spatial Association (LISA) time paths were longer in the North than that in the South, and they increased from the coastal to the central and western regions. Lastly, the overall decoupling index was mainly a weak decoupling type, but the number of cities with this weak decoupling continued to decrease. The unsustainable development trend of China’s economic growth and carbon emission load will continue for some time.
The Qinling-Daba Mountains are the main body of China’s North-South Transitional Zone. Analysis of the north-south gradual variation of vegetation components is significant for understanding the structural diversity and complexity of this transitional zone. In this study, based on survey data of plant communities, the eastern Qinling-Daba Mountains is divided into four geographic units: the north flank of eastern Qinling Mts., south flank of eastern Qinling Mts., north flank of eastern Daba Mts. and south flank of eastern Daba Mts. We also explore division of regional climate according to areal differentiation of plant-species, community structure and species-richness, respectively. The results show that, (1) at plant-species level, there are mainly northern plants in north flank of eastern Qinling Mts. with evergreen species and fewer northern plants in south flank of eastern Qinling Mts.; there are mainly southern plants in eastern Daba Mts. (2) At community structure level, there are 4 formations (3 northern formations and 1 widespread formation) in north flank of eastern Qinling, 6 formations (3 northern formations, 1 southern formation, and 2 widespread formations) in south flank of eastern Qinling, 4 formations (2 southern formations and 2 widespread formations) in north flank of eastern Daba Mts., and 3 formations (3 southern formations) in south flank of eastern Daba Mts. In terms of the numbers and properties of formations, there is a mixture of northern and southern formations only in the south flank of eastern Qinling Mts. (3) At species-richness level, the diversity of families, genera and species decreased with increasing latitude, but the mixing of northern plants and the southern plants began to occur in south flank of eastern Qinling Mts. This means that the south flank of the eastern Qinling Mts. serves more suitably as the dividing line between China’s warm temperate and subtropical zones.
This paper presents a detailed account of the effect of shipping activity on the increasing trends of air temperatures in the Canadian Arctic region for the period of 1980-2018. Increasing trend of temperature has gained significant attention with respect to shipping activities and sea ice area in the Canadian Arctic. Temperature, sea ice area and shipping traffic datasets were investigated, and simple linear regression analyses were conducted to predict the rate of change (per decade) of the average temperature, considering winter (January) and summer (July) seasons. The results indicate that temperature generally increased over the studied region. Significant warming trend was observed during July, with an increase of up to 1°C, for the Canadian Arctic region. Such increasing trend of temperature was observed during July from the lower to higher latitudes. The increase in temperature during July is speculated to increase the melting of ice. Results also show a decline in sea ice area has a significant positive effect on the shipping traffic, and the numbers of marine vessel continue to increase in the region. The increase in temperature causes the breaking of sea ice due to shipping activities over northern Arctic Canada.
The surface air temperature lapse rate (SATLR) plays a key role in the hydrological, glacial and ecological modeling, the regional downscaling, and the reconstruction of high-resolution surface air temperature. However, how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for researchers. The geographically weighted regression (GWR) model was applied in this paper to estimate the SATLR in China’s mainland, and then the assessment and validation for the GWR model were made. The spatial pattern of regression residuals which was identified by Moran’s Index indicated that the GWR model was broadly reasonable for the estimation of SATLR. The small mean absolute error (MAE) in all months indicated that the GWR model had a strong predictive ability for the surface air temperature. The comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the estimation. Therefore, the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.
The Belt and Road Initiative (BRI) instigated by China is catalyzing the evolution of a new global economic landscape. To cope with the great changes in the economic landscape, China needs to view the South China Sea Region (SCSR) as a strategic focus and study carefully the characteristics of regional development and explore the possibility for construction of a strategic multi-integrated economic zone which includes China and ASEAN countries. Based on key indicators, this paper outlines the overall development characteristics of the SCSR and analyzes the regional structural characteristics of industry and global trade based on the indexes of industrial structure similarity and trade commodity structure coincidence; the paper also depicts the spatial characteristics of the nine core growth areas (CGAs) in the region and discusses the construction prospects for a multi-integrated economic zone in the SCSR. The results show that, first, from 2000 to 2017, the main economic indicators of the SCSR grew quite well, and the development trend was much better than the global average for the same period. Second, driven by the global industrial transfer stages and spatial paths, the level of comprehensive development in the SCSR has evolved into four categories. Third, the index values for industrial structure similarity and trade commodity structure coincidence for the 11 countries in the SCSR have remained at a high level, and reveal an integration trend not only from the horizontal and vertical perspective, but also from an upgrading and downgrading standpoint. Fourth, nine CGAs have been established in the SCSR and the advantaged industries and the export commodity types between different countries exhibited the characteristics of convergence and complementarity due to the polarization and diffusion effects of the CGAs. Finally, from a long-term perspective, the SCSR has already acquired the internal and external conditions such as the 5th global industrial transfer initiative, the reconstruction of the global value chain, regional production-consumption networks and spatial entities for building a multi-integrated economic zone in the SCSR.
Unbalanced economic growth is a ubiquitous phenomenon while investigating the regional development at a large spatial scale. Therefore, it is of great significance to analyze the spatio-temporal pattern of regional economic growth and the drivers to understand and facilitate the economic development of low development areas. Taking a county as a fundamental study unit, we used the county-level per capita GDP data on the Loess Plateau from 2005 to 2017, and geographic variables such as slope, elevation, and population density to analyze the spatio-temporal differences and the driving factors of the county-level economic development in the Loess Plateau by employing both conventional and advanced quantitative methods including Exploratory Spatial Data Analysis (ESDA) and the geographic detector model. Our results suggested that: (1) The selected indicators, including absolute difference, the fluctuation of relative difference and total difference of economic development on the Loess Plateau, all show steady increasing trends, respectively. (2) There are 64.5% of the counties with economic development being below the average level of the whole Loss Plateau region. The relatively high developed counties are distributed in the “A”-shaped regions in Inner Mongolia Autonomous Region, Shaanxi, and Henan provinces, however, the low development counties are mainly located in the “V”-shaped regions in Gansu and Shanxi provinces. (3) GDP, investment in fixed assets and urbanization rate are the major driving factors influencing the regional economic development, and the combined effects are far greater than that of any individual factor.
In this paper, we review the research progress in development geography since the 20th century, focusing on its connotation and theory, fields, methods, and development trends. Specifically, we systematically review the research and applications of development geography, comprising fields such as the convergence of underdeveloped countries and regions, and the convergence of the process of improving the quality of life in developed countries and regions. Then, based on an analysis of research progress in development geography in foreign countries, we examine the development conditions and disciplinary advantages of development geography in China. Further, we highlight that future development geography research in China should focus on the latest international academic research and China’s national macro-strategic needs. Future research in development geography should be guided by the theory of sustainable development, the core of which is to improve sustainable livelihood capacity and regional green development levels in underdeveloped regions. This core includes the construction of industrial policy and development geography theory, as well as an interdisciplinary integrated research system. The focus must be placed on researching the spatial patterns, diffusion characteristics, and the convergence mechanism of regional development. Such a focus will facilitate exploration of the regulatory policies and scientific paths that serve regional economic construction and industrial development.
Digital terrain analysis (DTA) is one of the most important contents in the research of geographical information science (GIS). However, on the basis of the digital elevation model (DEM), many problems exist in the current research of DTA in geomorphological studies. For instance, the current DTA research appears to be focused more on morphology, phenomenon, and modern surface rather than mechanism, process, and underlying terrain. The current DTA research needs to be urgently transformed from the study of landform morphology to one focusing on landform process and mechanism. On this basis, this study summarizes the current research status of geomorphology-oriented DTA and systematically reviews and analyzes the research about the knowledge of geomorphological ontology, terrain modeling, terrain derivative calculation, and terrain analytical methods. With the help of DEM data, DTA research has the advantage of carrying out geomorphological studies from the perspective of surface morphology. However, the study of DTA has inherent defects in terms of data expression and analytic patterns. Thus, breakthroughs in basic theories and key technologies are necessary. Moreover, scholars need to realize that DTA research must be transformed from phenomenon to mechanism, from morphology to process, and from terrain to landform. At present, the research development of earth science has reached the critical stage in which the DTA research should focus more on geomorphological ontology. Consequently, this study proposes several prospects of geomorphology-oriented DTA from the aspects of value-added DEM data model, terrain derivatives and their spatial relations, and macro-terrain analysis. The study of DTA based on DEM is at a critical period along with the issue on whether the current GIS technology can truly support the development of geography. The research idea of geomorphology-oriented DTA is expected to be an important exploration and practice in the field of GIS.
