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  • Norbert J. NGOWI
    Journal of Resources and Ecology.
    Accepted: 2023-06-15
    Low efficiency of earth kilns used in the carbonising process of wood to make charcoal has been reported as one of the sources of increasing charcoal wastes in the global south. However, the potential link and approaches of converting charcoal wastes-to-valuable energy and for the environmental health is not well known in Africa. Promoting local community capacity engagement in the production and reutilisation of recycled charcoal wastes at the households’ level is one of important measures to maintain environmental services for sustainability since households make decisions on the type of energy used. This paper, presents an approach of converting charcoal wastes to fuel energy for rural households and environmental health in Kilosa District, Tanzania. To achieve the objective of this research, the primary data were collected through interviews held with 298 randomly selected households, Focus Group Discussions and observations. IBM SPSS statistics version 20 Cross tab tools were used in the data analysis. Results revealed that the conversion of charcoal wastes-to-fuel energy approach used in this research demonstrates the ability of recyclable briquettes made from the locally available charcoal pollutants collected at different stages from earth kilns, to selling centers, improves tree harvest behaviour, adds another fuel energy source through reutilisation, and ultimate reduces pollution at the local level. Thus, the study provides a basis for policymakers to adopt charcoal wastes recycling strategies to address matters related to energy and ultimately enhances environmental health for sustainable development in Tanzania and beyond.
  • JOSHI Nabin Raj, JOSHI Rajeev, MISHRA Jay Raj
    Journal of Resources and Ecology.
    Accepted: 2023-06-15
    Urban trees are valuable resources for urban areas as they have the capacity to reduce ambient temperatures, mitigate urban heat island effects and reduce runoff of rainwater playing an important role in mitigating the impacts of climate change by reducing atmospheric carbon dioxide (CO2). It also helps to reduce aerial suspended particulate matter, add visual appeal to the urban landscape sequestrating a significant amount of carbon from ambient atmospheric CO2. Carbon storage by urban trees in the ring road area of the Kathmandu Valley was quantified to assess the magnitude and role of urban forests in relation to mitigate the impact of global climate change. A total of 40 sample plots were placed randomly for the detailed carbon assessment. Aboveground and belowground carbon pools were considered in the detailed assessment. Furthermore, quality assurance (QA) and quality control (QC) were maintained through regular monitoring and capacity building of the field crews while collecting the bio-physical data. The assessment recorded a total of 33 different species of plants in the avenue’s plantation sites in ring road. The mean seedling, sapling, and tree density was found to be 2149585 and 185 per hectare. The mean carbon stock per hectare in the avenue plantation of the ring road area was 24.03 tC ha1 and the existing total carbon stock was 7785.72 tC in 2021. Likewise, the total baseline carbon dioxide equivalent (tCO2e) in the avenue plantation was found to be 28573.60 tCO2e. The carbon dioxide emission from the transport sector in the ring road area in a full movement scenario was 312888.00 tCO2e per annum, while the net emissions was 42547 tCO2e. There was a deficit of carbon dioxide in terms of stock by avenue plantations of 14000.8 tCO2e.This study indicates that the existing urban forest plantation is unable to sequestrate or offset the carbon dioxide that is emitted through the transportation sector. Consequently, open spaces like riverbanks and any other public lands, in which urban forests could be developed has to be planned for the green infrastructure and plantation of the multipurpose trees. The distinct values of forests in and around urban areas have to be recognized in the specific policies and plans for the sustainable management of urban and peri-urban forests to meet the adverse impact of global climate change. In addition, this study provides insights for decision-makers to better understand the role of urban forests and make sustainable management plans for urban forests in the cities like in Kathmandu Valley.
  • OU Dinghua, WU Nengjun, LI Yuanxi, MA Qing, ZHENG Siyuan, LI Shiqi, YU Dongrui, TANG Haolun, GAO Xuesong
    Journal of Resources and Ecology.
    Accepted: 2022-03-30
    Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions (ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai city and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai city’s ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai city show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai city represented strong non-stationary characteristics during 2003-2019, which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019-2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.
  • WU Bin, ZHANG Wenzhu, TIAN Yichao, LIANG Mingzhong, XU Jun, GU Guanhai
    Journal of Resources and Ecology.
    Accepted: 2022-02-28
    Abstract: By studying the structural characteristics and carbon storage of the mangrove island ecosystem in the 
    Beibu Gulf, this study provides a scientific basis for mangrove ecological compensation in the coastal areas of 
    Guangxi, South China Sea. On the basis of the unmanned aerial vehicle remote sensing images and a sample plot 
    survey, the object-oriented multi-scale segmentation algorithm is used to extract the mangrove community type information, and one-way analysis of variance is conducted to analyse the structural characteristics of the mangrove 
    community. The carbon storage and carbon density of different mangrove ecosystems were obtained based on the 
    allometric growth equation of mangrove plants. The analysis yielded four main results. (1) The island group covers 
    about 27.10 ha, 41.32% (11.20 ha) of which represents mangrove areas. The mangrove forest is widely distributed 
    in the tidal flats around the islands. (2) The main mangrove types were Aegiceras corniculatum, Kandelia obovata + 
    Aegiceras corniculatum, Avicennia marina + Aegiceras corniculatum and Avicennia marina communities. (3) 
    Amongst the mangrove plants, Avicennia marina had the highest biomass (18.52 kg plant–1), followed by Kandelia 
    obovata (7.84 kg plant–1) and Aegiceras corniculatum (3.85 kg plant–1). (4) The mangrove carbon density difference 
    was significant. Kandelia obovata had the highest carbon density (148.03 t ha–1), followed by Avicennia marina
    (104.79 t ha–1) and Aegiceras corniculatum (99.24 t ha–1). The carbon storage of the mangrove island ecosystem 
    was 1194.70 t, which was higher than in other areas with the same latitude. The carbon sequestration capacity of 
    the mangrove was relatively strong.
  • Journal of Geo-information Science. 2024, 26(4): 765-766.
  • LV Guonian, YUAN Linwang, CHEN Min, ZHANG Xueying, ZHOU Liangchen, YU Zhaoyuan, LUO Wen, YUE Songshan, WU Mingguang
    Journal of Geo-information Science. 2024, 26(4): 767-778. https://doi.org/10.12082/dqxxkx.2024.240149

    Geographic Information Science (GIS) is not only the demand for the development of the discipline itself, but also the technical method to support the exploration of the frontiers of geography, earth system science and future geography, and the supporting technology to serve the national strategy and social development. In view of the intrinsic law of the development of geographic information science, the extrinsic drive of the development of related disciplines, and the pull of new technologies such as Artificial Intelligence (AI), this paper firstly analyses the development process of GIS and explores its development law from six dimensions, such as description content, expression dimension, expression mode, analysis method and service mode, etc.; then, on the basis of interpreting the original intention and goal of the development of geography, a geography discipline system oriented to the "physical-humanistic-informational" triadic world is proposed, the research object of information geography is discussed, and a conceptual model integrating the seven elements of information and seven dimensions of geographic descriptions is put forward; then, the development trend of geographic information science is analysed from three aspects, including geography from the perspective of information science, information geography from the perspective of geography, and geo-linguistics from the perspective of linguistics, information geography from the perspective of geography, and geolinguistics from the perspective of linguistics, the development trend of geographic information discipline is analysed. Finally, the paper summarises the possible directions and points of development of GIS, geography in the information age, geo-scenario, and geo-big model. We hope that our work can contribute to enriching the understanding of geographic information disciplines, promoting the development of geographic information related sciences, and enhancing the ability of the discipline to support national development needs and serve society.

  • ZHANG Xinchang, HUA Shuzhen, QI Ji, RUAN Yongjian
    Journal of Geo-information Science. 2024, 26(4): 779-789. https://doi.org/10.12082/dqxxkx.2024.240065

    The new smart city is an inevitable requirement for the development of urban digitalization to intelligence and further to wisdom, and is an important part of achieving high-quality development. This paper first introduces the background and basic concept of smart city, and analyzes the relationship and difference between the three stages of digital city, smart city and new smart city. Digital cities use computer networks, spatial information and virtual reality to digitize urban information, and focus on building information infrastructure. Smart cities, on the other hand, use spatio-temporal big data, cloud computing, and the Internet of Things to integrate systems across urban life, emphasizing intelligent management through a unified digital platform. New smart cities combine technologies such as digital twins, blockchain, and the meta-universe for citywide integration, and employ AI-based intelligent lifeforms for decision-making, blending real and virtual elements for advanced city management. This paper then explores the construction of new smart cities, focusing on high-quality urban development driven by technology and societal needs. It highlights the transition from digital to smart cities, emphasizing the role of information infrastructure and intelligent technology in this evolution. The paper discusses key technologies such as 3D urban modeling, digital twins, and the metaverse, and details their impact on urban planning and governance. It also examines how smart cities contribute to economic growth, meet national needs, and ensure public health and safety. The integration of technologies such as AI, IoT, and blockchain is shown to be critical to creating connected, efficient, and sustainable urban environments. The paper concludes by assessing the role of smart cities in measuring economic development, demonstrating their potential as a benchmark for national progress. Finally, based on the latest advances in AI technology, this paper analyzes and systematically looks forward to the key role AI can play in building new smart cities. AI's ability to analyze massive amounts of data, improve decision-making, and integrate various urban systems all provide important support for realizing the vision of a truly smart city ecosystem. With the synergy of "AI + IoT", "AI + Big Data", "AI + Big Models", and "AI + High Computing Power", the new smart cities are expected to achieve an unparalleled level of urban intelligence and ultimately a high quality of sustainable, efficient, and people-centered urban development.

  • WU Tianjun, LUO Jiancheng, LI Manjia, ZHANG Jing, ZHAO Xin, HU Xiaodong, ZUO Jin, MIN Fan, WANG Lingyu, HUANG Qiting
    Journal of Geo-information Science. 2024, 26(4): 799-830. https://doi.org/10.12082/dqxxkx.2024.230747

    With high quality development becoming the primary task of comprehensively building a socialist modernized country, the importance of geographic spatiotemporal information in supporting national and local socio-economic development has been raised to new heights. Based on the urgent need for high-quality development to empower geographic spatiotemporal information, this paper first comprehensively reviews the theoretical and methodological research status of geographic spatiotemporal expression and computation from the perspectives of complex land surface system expression, spatiotemporal uncertainty analysis, and geographic spatial intelligent computing. It is pointed out that there is an urgent need to update concepts, integrate across borders, and innovate technologies to improve the production level of spatiotemporal information products and assist in the high-quality transformation and development of social and economic activities in the three living spaces. Furthermore, driven by the problems of deconstructing complex land surface and analyzing precise parameters, we propose relevant theoretical thinking and research ideas of geographic spatiotemporal digital base (GST-DB) with an overview of basic concepts and technical points. The GST-DB is based on the uniqueness and distribution of time and space, and is proposed by three basic elements around brackets, containers, and engines. The paper focuses on analyzing three key scientific issues, including multiple representations and knowledge association for complex land surface systems, uncertainty analysis of spectral feature reconstruction under spatial form constraints, signal transmission and optimized control with the collaboration of satellite, ground, and human. The three key objectives, namely deconstruction of global space, analyticity of local space, and transferability between spaces, cut into the process of connecting the two-step process of spatial expression and parameter calculation, and further explain the difficulties and feasible solution paths of reliable expression, reliable analysis, and controllable computing. Through the analysis of the solution approach, the feasibility and necessity of the organic synergy of geoscientific analysis ideas, remote sensing mechanism knowledge, and machine intelligence algorithms are demonstrated. On this basis, this paper focuses on the monitoring and supervision of agricultural production as a demand-oriented problem for introducing agricultural application cases of GST-DB. Four types of application models for people, land, money, and things are preliminarily described. By demonstrating the construction process and implementation effectiveness of integrated intelligent computing, the advantages and basic supporting role of the base in carrying and utilizing spatiotemporal data elements are highlighted. This case study demonstrates the potential to provide high-quality spatiotemporal information services for the development of modern agriculture in complex mountain areas.

  • LIU Kang
    Journal of Geo-information Science. 2024, 26(4): 831-847. https://doi.org/10.12082/dqxxkx.2024.230488

    Human mobility data play a crucial role in many real-world applications such as infectious diseases, transportation, and public safety. The development of modern Information and Communication Technologies (ICT) has made it easier to collect large-scale individual-level human mobility data, however, the availability and usability of the raw data are still significantly limited due to privacy concerns, as well as issues of data redundancy, missing, and noise. Generating synthetic human mobility data through modeling approaches to statistically approximate the real data is a promising solution. From the data perspective, the generated human mobility data can serve as a substitute for real data, mitigating concerns about personal privacy and data security, and enhance the low-quality real data. From the modeling perspective, the constructed models for human mobility data generation can be used for scenario simulations and mechanism exploration. The human mobility data generation tasks include individual trajectory data generation and collective mobility data generation, and the research methods primarily consist of mechanistic models and machine learning models. This article firstly provides a systematic review of the research progress in human mobility data generation and then summarizes its development trends and challenges. It can be observed that mechanistic-model-based methods are predominantly studied in the field of statistical physics, while machine-learning-based methods are primarily studied in the field of computer science. Although the two types of models have complementary advantages, they are still developing independently. The article suggests that future research in human mobility data generation should focus on: 1) exploring and revealing the underlying mechanisms of human mobility behavior from a multidisciplinary perspective; 2) designing hybrid approaches by coupling machine learning and mechanistic models; 3) leveraging cutting-edge generative Artificial Intelligence (AI) and Large Language Model (LLM) technologies; 4) improving the models' spatial generalization and transfer-learning capabilities; 5) controlling the costs of model training and implementation; and 6) designing reasonable evaluation metrics and balancing data utility with privacy-preserving effectiveness. The article asserts that human mobility processes are typical phenomenon of human-environment interactions. On the one hand, research in Geographic Information Science (GIS) field should integrate with theories and technologies from other disciplines such as computer science, statistical physics, complexity science, transportation, and others. While on the other hand, research in GIS field should harness the unique characteristics of GIS by explicitly incorporating geographic spatial effects, including spatial dependency, distance decay, spatial heterogeneity, scale, and more into the modeling process to enhance the rationality and performance of the human mobility data generation models.

  • JIANG Bingchuan, SI Dongyu, LIU Jingxu, REN Yan, YOU Xiong, CAO Zhe, LI Jiawei
    Journal of Geo-information Science. 2024, 26(4): 848-865. https://doi.org/10.12082/dqxxkx.2024.240151

    Cyberspace surveying and mapping has become a hot research topic of widespread concern across various fields. Its core task involves surveying the components of cyberspace, analyzing the laws of cyberspace phenomena, and mapping the structure of cyberspace. Research on cyberspace surveying and mapping faces issues such as diverse conceptual terminologies which is lack of unified research frameworks, unclear understanding of elements and laws, non-standardized methods of cyberspace map expression, and the absence of unified standards. Based on systematically reviewing the current status of cyberspace surveying and mapping research across fields, a common understanding of the essence of cyberspace has been analyzed. Starting from the spatial, geographical, and cultural characteristics of cyberspace, the features and advantages of studying and utilizing cyberspace from the perspective of mapping geography are dissected. A research framework for cyberspace surveying and mapping is proposed, focusing on the core content and key technologies of "surveying " and "mapping" in cyberspace, and explaining its relationship with 3D Real Scene, Digital Twins and Metaverse. Cyberspace surveying has been divided into narrow and broad senses, pointing out the lack of holistic measurement of cyberspace features and the lack of research on measuring the phenomena and patterns of human activity in cyberspace. From the perspective of cyberspace cognitive needs, a conceptual model and classification system for cyberspace maps have been proposed. Focusing on the cyberspace coordinate system, "geo-cyber" correlation mapping, and methods of expressing cyberspace maps, the key technologies for creating cyberspace maps are described in detail, and the methods of representing cyberspace maps and their applicability are systematically analyzed. Finally, key scientific questions and critical technologies that need focused research, such as the top-level concepts of cyberspace, cyberspace modeling methods, theories and methods of cyberspace maps, and the design of application scenarios for cyberspace maps, are discussed.

  • LI Lu, GONG Huili, GUO Lin, ZHU Lin, CHEN Beibei
    Journal of Geo-information Science. 2024, 26(4): 927-945. https://doi.org/10.12082/dqxxkx.2024.230336

    The development of hydrologic time series analysis is crucial for the effective management and utilization of water resources. Based on the WoS Core Collection database and the CNKI database, this paper employs bibliometrics and CiteSpace software to reveal the development trends, research hotspots, and future directions in the field of hydrologic time series analysis both domestically and internationally. Firstly, starting with the randomness, nonlinearity, and uncertainty of hydrologic time series, as well as emerging methods such as machine learning and neural networks, this paper divides the recent advances in the field of hydrologic time series analysis into six aspects. Then, a detailed introduction for each advance is provided, and a comparison with traditional methods is also made to summarize the shortcomings of traditional methods. Finally, the directions for improving the accuracy of hydrologic time series analysis are pointed out, including:1) modeling at spatiotemporal scales and integrating multi-source data for analysis; 2) incorporating physical mechanisms into machine learning models to enhance interpretability and generalization capabilities; 3) considering the coupling of climate change (extreme weather events) and hydrologic processes in research advances; 4) conducting comprehensive research on multiple complex characteristics and improving the research level of each complex characteristic. By revealing the development trends, research hotspots, and future directions of hydrologic time series analysis both domestically and internationally, we can better understand and respond to the impacts of climate change, extreme weather events, and human activities on water resources, enhance our understanding of hydrologic processes, and provide scientific basis for water resources planning, flood risk management, and sustainable development.

  • YANG Cankun, LI Xiaojuan, LI Wei, ZHONG Ruofei, LI Qingyang, DU Xin
    Journal of Geo-information Science. 2024, 26(4): 1040-1056. https://doi.org/10.12082/dqxxkx.2024.230759

    Moving target detection plays a pivotal role in extracting temporal information from time-series images, particularly from satellite data. This method enables the rapid acquisition, analysis, and utilization of dynamic change information, meeting the demand for "real-time target discovery and delivery." In the processing of optical image-based moving target detection, existing methods often fall short of meeting the requirements for large-scale target discovery, accommodating diverse speeds, and ensuring hardware acceleration compatibility. This study aims to achieve swift perception of large-scale moving targets using optical remote sensing satellites, with a primary focus on both camera innovation and algorithm research in terms of target discovery and target information processing. This paper proposes a novel imaging mode, leveraging a dual-linear array push-broom optical remote sensing camera to capture dual-strip images containing temporal changes associated with moving targets. The camera principle prototype was successfully deployed on the "Taijing-4 Satellite" on February 27, 2022, thereby validating the technical approach for large-scale detections. Furthermore, this paper introduces a pioneering approach for detecting moving targets based on saliency region proposal for dual-band images, which significantly enhances the temporal information captured in dual-linear array push-broom imaging. Subsequently, we employ a sophisticated saliency region proposal method to extract the prominent regions of moving targets by utilizing the temporal and spatial change information within the image. These salient regions encompass dynamic targets across the entire image, effectively reducing the amount of intermediate data processed by the algorithm. Finally, a lightweight and efficient deep learning object detection model is leveraged to classify moving targets and eliminate false positives from the initial detection outcomes. The results indicate that the proposed method can efficiently detect moving targets in dual-strip images, substantially improving the accuracy of dynamic target shape extraction and optimizing the results of target matching. Notably, by enhancing the recall rate of the moving target detection algorithm, the algorithm's execution efficiency is also increased by 61.4%. This paper demonstrates two remarkable strengths in its viewpoints and discussion. Firstly, it puts forth a groundbreaking imaging mode and method to enhance the temporal information of images, effectively addressing the challenge of observing large-scale moving targets without relying on satellite attitude maneuvering. Secondly, it proposes a highly efficient moving target detection model based on saliency region proposal, resolving the problem of detecting moving targets in complex backgrounds. The acquisition of key information about moving targets can significantly reduce the bandwidth requirements for ground transmission of remote sensing data, providing a new way of data acquisition and on-orbit processing for mega Earth observation systems.

  • WANG Fang, LIU Yong, HE Jin-sheng, HU Xie, QIN Yue, WANG Le-ye
    JOURNAL OF NATURAL RESOURCES. 2024, 39(5): 997-1007. https://doi.org/10.31497/zrzyxb.20240501

    In the complex human and water adaptation process, river basins have become the containers and links that nurture human civilization and witness the evolution of urban and rural areas. River basin habitats refer to the adaptive systems formed by the interaction and coevolution of river basin and human settlement, characterized by integrity, dynamism, and synergy. From the multi-disciplinary common problems, the river basin habitats (riv-habitats) science encompasses three key issues: element coupling, scale correlation, and system evolution. It refines the theoretical model of the "node-setting-connection" structural theory and the "locality-adaptation" evolutionary theory and also improves a new paradigm of interdisciplinary approach and artificial intelligence for river basin habitats. As an interdisciplinary field that adapts to the needs of the times and that aims at the sustainable development goal of harmonious coexistence between humans and nature, riv-habitats science comprehensively applies the knowledge and methods of multiple disciplines to carry out interdisciplinary systematic research on river basin habitats, which will contribute to the ecological civilization and high-quality development and construction of river basins in the New Era.

  • WANG Tian-yu, YUE Wen-ze
    JOURNAL OF NATURAL RESOURCES. 2024, 39(5): 1008-1021. https://doi.org/10.31497/zrzyxb.20240502

    The patterns of territorial spatial development determine the dynamic carbon balance in regional terrestrial ecosystems. In the context of global "carbon neutrality" and China's new urbanization transformation, it is urgent to establish development patterns that enhance terrestrial ecosystems' carbon sink capacity. To this end, the study establishes a systematic cognitive framework for the carbon balance effects of land use under urbanization. It proposes a "direct-indirect-potential" typology for the impact of urbanization-induced land use changes on terrestrial ecosystems' carbon cycling. To achieve the goal of carbon sequestration and increase in terrestrial ecosystems, the study explores the inherent logic of low-carbon optimization in territorial spatial layout. It also deconstructs the governance dimensions of low-carbon optimization in territorial spatial layout concerning "quantity, spatial layout, and spatial utilization". Finally, the study proposes policy instruments and improvement suggestions for supporting low-carbon adjustments in territorial spatial layout. In conclusion, the study's first contribution is the enhancement of low-carbon thinking in territorial spatial development and utilization. Secondly, it broadens the research path for low-carbon optimization in territorial space. The study highlights the positive role of territorial spatial layout optimization and governance in achieving regional "carbon neutrality" goals.

  • Jiao'e Wang, Enyu Che, Fan Xiao
    Tropical Geography. 2024, 44(5): 771-782. https://doi.org/10.13284/j.cnki.rddl.003870

    Air cargo is an important component of transportation and plays a vital role in the efficient allocation of high-quality resources on global and regional scales. Air cargo contributes significantly to regional economic development by strengthening inter-regional cooperation and resource integration. However, air cargo geography has received relatively less attention from the research community. Existing studies have analyzed the spatial pattern of air cargo using a limited cross-sectional data from selected years, lacking an analysis of its influencing factors. Based on spatial statistics and panel data of air cargo, this study explores the evolution process and characteristics of China's air cargo pattern on a 20-years time scale and quantitatively reveals its key influencing factors. The research findings are as follows: 1) Air cargo in China has transitioned from the rapid development stage to the stable development stage in the past 20 years; 2) Air cargo volume in China is mainly concentrated in the eastern region, and in the past 20 years, China's air cargo center of gravity has been generally located at the junction of Anhui, Henan, and Hubei provinces, showing a spatial displacement trend from Henan to Anhui to Hubei; 3) The pattern of air cargo network in China remains relatively stable, forming a rhombic structure with Beijing, Shanghai, Guangzhou, and Shenzhen as the core; 4) Air cargo development in China is influenced by factors such as urban scale, industrial structure, and ground transportation development. Among them, urban economy, transportation, warehousing, postal and telecommunications industry, and technological investment have a significant positive impact on air cargo volume, whereas the wholesale and retail trade industries have a significant negative impact. For air logistics hubs, the influencing factors are consistent with those of the entire sample airport. However, for non-aviation logistics hubs, population size and research and technology services have a significant positive impact, whereas ground transportation accessibility has a significant negative impact. This study enriches the long-term time-series analysis and quantitative research content in the field of air cargo and has significance for the development of air transportation geography and the construction of a strong civil aviation industry in China.

  • Qitao Wu
    Tropical Geography. 2024, 44(5): 783-793. https://doi.org/10.13284/j.cnki.rddl.003875

    Owing to historical reasons, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) features a unique "one country, two systems" institutional framework. Facilitating the integration and connectivity of transportation among Hong Kong, Macao, and the Mainland is crucial for the high-quality development of the GBA. Previous studies about borders have primarily focused on national (supranational) or administrative boundaries within a country's territory. However, studies on the unique institutional differences in the GBA are insufficient. Additionally, most studies do not perform dynamic border effects measurements using big traffic flow data. This study utilizes toll-collection data from highways in the GBA for 2021 and 2023, as well as cross-border traffic data, to construct a traffic-flow network for the GBA. Complex network analysis and border-effect measurement methods are employed to investigate the spatial structure of the GBA traffic-flow network and its dynamic changes in border effects. The results indicate that, in terms of the overall spatial structure of traffic flow in the GBA, the network exhibits a unique "dual-core edge" structure, with the Guangzhou-Foshan, and Shenzhen-Dongguan-Huizhou regions serving as dual cores. In contrast, the overall coverage and connectivity strength of the passenger-flow network are higher than those of the freight-flow network. Regarding the dynamic changes in the spatial structure of traffic flow from Hong Kong and Macao, the coverage and density of the traffic-flow network in 2023 are significantly higher than those in 2021. Traffic flows from Hong Kong and Macao have begun to extend beyond the border toward the northern regions, thus accelerating the integration of transportation within the GBA and forming a spatial pattern of "cross-strait connectivity and all-area interconnection." However, because of their peripheral positions in the traffic network and the presence of border effects, the importance of Hong Kong and Macao in the GBA traffic-flow network remains relatively weak. Based on the dynamic measurement results of border effects, the obstruction coefficients between Hong Kong and the Mainland, as well as between Macao and the Mainland, are significantly higher than those between various counties within the Mainland. The obstruction coefficients for passenger vehicles are generally lower than those for freight vehicles. Following the outbreak of the pandemic, the obstruction coefficients of the GBA traffic-flow network have increased dynamically, thus indicating a reduction in obstructive border effects. This study expands the quantitative research framework of border effects in traffic-flow networks, thus promoting integrated transportation development in the GBA and facilitating its integration development goals.

  • Pengjun Zhao, Tong Zhao, Mengzhu Zhang, Ting Xiao
    Tropical Geography. 2024, 44(5): 820-837. https://doi.org/10.13284/j.cnki.rddl.003867

    The impact of international geopolitics on transportation network patterns is an important topic in economics and transportation geography. Previous studies have often overlooked the diversity of domestic crude oil transportation among countries due to limitations in statistical data, focusing mainly on national-level node selection. Additionally, the evolution of network characteristics is predominantly analyzed through long-term descriptive approaches, lacking specific contextual analyses of network evolution. This study investigates changes in the maritime crude oil transportation network along the Belt and Road Initiative (BRI) routes against the backdrop of the Russia-Ukraine conflict, offering new evidence for research in this field. Using AIS(Automatic Identification System) ship trajectory big data and complex network analysis methods, this study analyzes the overall characteristics, node importance, core-periphery structure, and clustering of the maritime crude oil transportation network along the BRI routes from 2019 to 2022. Furthermore, it examines the impact of maritime network changes on the stability of crude oil imports to China. Our findings reveal several key points. 1) The closeness, strength, and accessibility of network connections between ports show an initial increase followed by a decreasing trend. The direction of the overall network characteristic changes in the periods 2019-2020 and 2020-2022 are opposite, with a greater magnitude in the latter period. In recent years, particularly following the Russia-Ukraine conflict, the scale-free nature of the network has continuously increased, accompanied by an increase in the concentration of crude oil shipping connections. This concentration, notably evident towards export destinations, reflects a shifting pattern in the crude oil supply demand landscape, spatially manifested as China replacing some of its crude oil shipping connections with the Middle East, thus reducing its reliance on Russian crude oil shipments. 2) The comprehensive importance of export ports has become more prominent, with a slight decrease followed by a significant increase in recent years. The importance of ports in Russia's Far East region has notably increased, reflecting a shift in Russia's crude oil export center eastward after the Russia-Ukraine conflict. The network structure transitioned from single-core to multi-core to single-core with export ports occupying more central layers. 3) Initially, there was a continuation of the core-periphery and clustering structures, but later, there was significant structural reorganization. In 2020, the core-periphery structure and clustering in terms of core ports, geographical distribution, and cluster size were largely the same as corresponding clusters in 2019; however, by 2022, a noticeable structural reorganization emerged. 4) Changes in maritime networks significantly and heterogeneously affect China's crude oil import stability. At the network level, import stability initially increases and then decreases, with the decline in the later period far exceeding that in the earlier period. At the port level, compared to ports around Bohai Bay and the Yangtze River Delta, ports along the southeastern coast, Pearl River Delta, and southwestern coast were more affected by the Russia-Ukraine conflict in terms of crude oil import stability. China responded to the risk of instability in its crude oil import network against the backdrop of the Russia-Ukraine conflict by adjusting its sources and proportions of imports from different ports. This study provides scientific evidence for a deeper understanding of the impact of geopolitical events on China's oil imports and the formulation of national energy security strategies.

  • Tao Li, Leibo Cui, Jiao'e Wang, Huiling Chen
    Tropical Geography. 2024, 44(5): 838-849. https://doi.org/10.13284/j.cnki.rddl.003868

    With the rapid development of urban regionalization and networking of high-speed transport, intercity travel has increasingly played a key role in China's economic and social development and socioeconomic functional connections. However, amidst global change and uncertainty, the event disturbance-oriented theory and empirical research on intercity travel is still insufficient to improve the ability of transportation systems to cope with disturbances. Since uncertainty is prevalent in transport operations, improving Intercity Travel Behavior Resilience (ITBR) and grasping the spatiotemporal pattern of demand-side intercity travel fluctuation to restrain risk is essential for resilient transport construction. Based on related theories and analysis methods of spatial interaction and intercity travel, this study refines the definition of ITBR. A measurement model of ITBR was constructed based on long-term intercity travel data and the general properties of disturbance events. Furthermore, COVID-19 disturbance was used as a case study to reveal the adaptive pattern of intercity travel and the spatiotemporal pattern of ITBR over three years. The results show that the evaluation of ITBR based on seasonal and holiday trends reveal spatiotemporal patterns of intercity travel fluctuations influenced by disturbance events. The impact of the COVID-19 pandemic on intercity travel is as follows: peak of the national pandemic > peak of the Omicron variant > peak of the multipoint fluctuation. The intensity of intercity travel decreased linearly with an increase in distance, and intercity travel during the three stages is lost by 0.86, 1.03, 1.15 percentage points, respectively, with an increase of 50 km. The average intercity travel distances of residents in these three stages were shortened by 52.55, 65.31, and 105.16 km, respectively. The value of ITBR decreased from the multipoint fluctuation period to the national pandemic period because of the Omicron outbreak. Overall, ITBR showed a gradual increasing trend during the study period. Meanwhile, ITBR in these three stages was characterized by obvious spatial differentiation and regional agglomeration. Compared to existing research, this study further expands existing research focusing on intra-city travel behavior resilience by exploring ITBR on the regional scale.

  • Changsheng Xiong, Yuyao Hu, Bo Zhou, Xue Liu, Qiaolin Luan
    Tropical Geography. 2024, 44(5): 938-950. https://doi.org/10.13284/j.cnki.rddl.003862

    High-Speed Rail (HSR) stations can influence the expansion of the surrounding construction land. However, relevant studies face three main limitations: influence scope estimation lacking a theoretical foundation, less focus on whether the impacts of HSR stations on construction land expansion vary, and misjudgment of the drivers of HSR stations on construction land expansion. To address these research questions, this study first conducts a literature review to theoretically analyze the influence of HSR stations on the surrounding construction land expansion and then identifies the ideal curve for the influence distance of HSR on construction land expansion based on location theory and distance decay theory. Using the 24 stations of the Hainan Roundabout Railway (HRR) as an example, we revealed differences in the influence of various HRR stations on construction land expansion through GIS technology, buffer analysis, and nonlinear fitting to quantitatively analyze the expansion of construction land around HRR stations, identifying the impact range and direction of different HRR stations on the expansion of construction land. Building on the identification of heterogeneous impact results, the study further employed Geodetector to analyze the factors and reasons for the differentiated results of construction land expansion around different HRR stations from four dimensions: attributes of the socioeconomic environment, location conditions, HRR station attributes, and natural conditions. The results show that: (1) after the construction and operation of each HRR station, the surrounding construction land has expanded; the Hainan Eastern Ring HSR (the East Ring) has increased 1.70 km2 around each station per year and the Hainan Western Ring HSR (the West Ring) has increased 1.25 km2 around each station per year. (2) The changing trend of construction land expansion around 20 of 24 HRR stations conforms to the ideal curve, with the impact range of construction land expansion concentrated within 0.5-3.5 km, and the influence intensity of impact ranging from 0.06 to 6.64 km2. (3) The impact directions of construction land expansion around 20 HRR stations are mainly in three types of directions: "HSR-main urban area," "HSR-town center," and "HSR-scenic spot." This is because the expansion of construction land around HRR stations is not only influenced by the spillover effects of the stations, but also by the traction effect of the main urban areas, town centers, or tourist areas where the HRR stations are located. The stations along the East Ring of Hainan mainly expanded towards the main urban areas, whereas the stations along the West Ring of Hainan mainly expanded towards town centers. (4) Differences in the scope of the influence of each HRR station on the surrounding construction land expansion were mainly related to several variables, ordered as follows: socioeconomic environment, location conditions, attributes of the HRR station, and natural conditions. The GDP density of the towns where the HRR stations were located had the highest impact intensity at 0.51, followed by population density at 0.49, whereas the average elevation had the lowest impact intensity at 0.12. This study analyzed the mechanism and ideal curve of construction land expansion around HSR stations, establishing a logical basis for studying the spillover effects of HSR stations. In addition, this study analyzes the various impacts of HSR stations on the expansion of surrounding construction land and the reasons for these differences, providing a scientific basis for the current operation and future location of HSR stations. This study also offers methodological insights into the impacts of other infrastructures on the expansion of construction land in surrounding areas.

  • Ye Yuyao, Chen Yijia, Liu Xiangjie, Xu Jili
    SCIENTIA GEOGRAPHICA SINICA. 2024, 44(4): 553-561. https://doi.org/10.13249/j.cnki.sgs.20230567

    New infrastructure is not only the cornerstone of the fourth industrial revolution, the engine for the high-quality development of regional economy and the rise of a great nation, but also the frontier and important research field of economic geography. From the perspective beyond technology, this paper systematically combs the relevant theories about new infrastructure in current economic geography, including the theory of technological relatedness, the theory of key enabling technology, the theory of technology-system co-evolution and the theory of regional integration. On this basis, 3 scientific issues and research ideas that need to be focused on are proposed, namely, the research on the path and mechanism of the new infrastructure technology-system collaborative evolution, the research on the innovation and development mechanism of the new infrastructure enabling industry, and the research on the overall layout of the new infrastructure and the operation mechanism of regional integration. This paper aims to establish a theoretical framework for new infrastructure to promote regional economic development, in order to provide theoretical support for China to better play the strategic potential of new infrastructure and promote regional high-quality development.

  • Zhang Pei, Wang Jiaoe, Ma Li
    SCIENTIA GEOGRAPHICA SINICA. 2024, 44(4): 562-572. https://doi.org/10.13249/j.cnki.sgs.20220407

    Based on the panel data of 31 provinces (cities and districts) in China from 2013 to 2020, this paper measures the level of new infrastructure development and the degree of coordinated regional economic development in each province and then uses the coupling coordination model to measure the coupling coordination degree of the two and analyzes their spatial and temporal evolution patterns and influencing factors. The results show that: 1) The level of development in China’s new infrastructure and regional economic coordination degree has been improving each year, with increasing coupling and coordination between the two. Despite starting from a lower level, the growth rate of new infrastructure has been significant since 2018, reaching 29.96% in 2020. Similarly, there has been a noticeable upward trend in the degree of regional economic coordination and the coupling between new infrastructure and regional economic coordination degree. 2) The coupling and coordination between new infrastructure and regional economic coordination degree exhibit spatial heterogeneity, with the eastern region surpassing the central and northeastern regions, while the western region lags behind. This discrepancy can be attributed to the relatively higher levels of new infrastructure development and regional economic coordination degree in the eastern provinces, as well as the smaller internal differences within the central and northeastern provinces. On the other hand, the western provinces exhibit greater disparities. 3) The level of new infrastructure development demonstrates negative spatial spillover effects among provincial regions, whereas the degree of regional economic coordination and the coupling between new infrastructure and regional economic coordination degree exhibit positive spatial spillover effects among provincial regions. 4) The factors that primarily influence the coupling and coordination between new infrastructure and regional economic coordination degree are related to industrial structure and urbanization processes. Conversely, factors such as government management and population density have less discernible effects on this coupling and coordination. The article investigates the evolutionary characteristics and influencing factors of the level of new infrastructure development, the degree of coordinated regional economic development, and the degree of coupling and coordination of the two in China, and expects to provide a reference for decision-making on the benign interaction between new infrastructure and coordinated regional economic development in China.

  • Li Yaqin, Yu Jia, Zhou Yang, Wu Hangxing, Zhang Min, Wen Jiahong
    SCIENTIA GEOGRAPHICA SINICA. 2024, 44(4): 573-585. https://doi.org/10.13249/j.cnki.sgs.20230850

    The supply and demand allocation and logistics optimization of emergency materials are important support for emergency materials management and decision-makings. This study proposes a supply-demand analysis based material supply point allocation method, which on the basis of the optimal supply and demand allocation model. This method takes into account the constraint condition that the market reserve point must simultaneously supply both the affected and original demand points with supportive materials. Compared to traditional methods, this approach further improves the rationality and accuracy of material supply and demand analysis. Based on the allocation of material supply points, a method for optimizing the emergency material distribution path under flood scenarios is further developed. This method is based on real road networks, using “Degree” “Squares Clustering Coefficient” and “Road Design Daily Traffic Volume” to evaluate the reliability of road sections, and fully considers the impact of the flood disaster on the road travel time. It aims to achieve the shortest path travel time and the highest path reliability, using heuristic algorithms to solve the optimal path. A case study was conducted in Fengxian District, Shanghai, China. Through comparative analysis of multiple scheme scenarios of collaborative supply between the market and government, it was found that the G scheme (100% government supply) required a longer distribution time and resulted in a higher overall time cost, which could lead to the timeout situation for emergency response missions. The S plan (100% market supply) had a lower delivery efficiency and was prone to waste of human and transportation resources. However, the S1500 scheme (the market supplies the shelters within the 1 500 m coverage range and the government supplies the remaining shelters) was a collaborative supply scheme that was suitable for all 3 types of materials (water, rice, milk (infant formula)) in the case study. The research results can provide decision supporting for emergency rescue and relief efforts of relevant departments in the study area. The methods proposed in this paper can provide methodological references for related studies in other regions.

  • Xu Jili, Ye Yuyao, Guo Jie, Xu Xianfeng, Yuan Zhenjie
    SCIENTIA GEOGRAPHICA SINICA. 2024, 44(4): 586-597. https://doi.org/10.13249/j.cnki.sgs.20230565

    The new waves of information technology revolution give rise to digital infrastructure exemplified by 5G base stations, big data centers, and industrial internet, constituting strategic components of the modern infrastructure system. Proliferated studies on digital infrastructure range from diverse disciplines and perspectives. Given the unclear principal line of research progress in geographical studies on digital infrastructure, along with ambiguous disciplinary contribution and future research avenues, this paper therefore seeks to review and compare research progress on digital infrastructure from a geographical perspective in China and abroad, and to draw upon key research agendas for academic attention. In general, overseas studies have an early start, with rapid research progress and diversified themes, and have been consistently intensified and widened. By contrast, domestic studies exhibit a late start but have increased explosively since 2019 mainly by scholars in the field of economics and management. Based on a critical perspective and demand side, overseas studies pay much attention to the digital gap, socio-spatial inequality, and digital transformation of disadvantaged regions. Domestic studies, which place more emphasis on a functional perspective and supply side, focus on how digital infrastructure empowers regional digital economic development and connectivity within and among regions. In short, the new waves of digital technology revolution, justice and equity requirements in the information society, and national strategic demands facilitate the rise and development of digital infrastructure studies in geography. Although overseas and domestic studies share similar themes, but they exhibit different priorities. Knowledge production and theoretical construction of digital infrastructure in China by geographers are still in its infancy. Looking forward, this paper suggests that: 1) geographical studies on digital infrastructure in China should balance the supply and demand sides, in order to strengthen the interaction and systematization of research achievements; 2) digital infrastructure needs to be better incorporated into related theoretical frameworks in geography, deepening disciplinary knowledge production and theoretical contribution; 3) comprehensiveness of geography should be sufficiently employed as an advantaged way to lead multi-disciplinary studies on digital infrastructure.

  • Articles
    GUAN Weihua, WU Xiaoni, WANG Hao, ZHANG Hui, WU Lianxia
    PROGRESS IN GEOGRAPHY. 2024, 43(4): 629-643. https://doi.org/10.18306/dlkxjz.2024.04.001

    Changes in production factors have an important impact on the evolution of the spatial pattern of regional economic development. Based on the panel data of 290 prefecture-level cities in 1990-2020, the Mann-Kendall method was applied to classify China's municipal economic growth into two stages—1990-2012 and 2013-2020, and the Malmquist productivity index and spatial Durbin model were further used to analyze the effects of changes in production factors on China's regional economic growth at different stages. The results show that: 1) China's regional economy has always maintained its growth trend, and the regional economic growth areas have gradually shifted from the eastern coastal areas to the inland areas, and the growth pattern has changed from an obvious east-west difference to a coexistence of east-west and north-south differences. 2) There are clear differences in the spatial distribution pattern of changes in production factors. The regions with a large proportion of capital stock have gradually shifted from a contiguous distribution in the northeast and the Bohai Rim to the southeast coastal region, while sporadically distributed in core cities in the central and western regions; the pattern of incremental employment is consistently high in the southeast and low in the northwest, with high-value areas mainly distributed in the Beijing-Tianjin-Hebei region, Yangtze River Delta, Pearl River Delta, and Chengdu-Chongqing urban agglomerations; the level of capital deepening and factor input-output efficiency generally show a year-on-year upward trend, and the core urban agglomerations are still the ones with higher levels of capital deepening and efficiency. 3) The degree of influence of factor changes on regional economic growth varied over time and at different scales, with factor input-output efficiency and the number of people employed being the main contributors to regional economic growth in the two periods, respectively. The research findings can serve as a decision-making reference for China's economic development under the new circumstance.

  • Yin Lingling, Luo Lijuan
    Historical Geography Research. 2024, 44(1): 1-16. https://doi.org/10.20166/j.issn.2096-6822.L20230083

    In the Luoyang Basin during the Han, Wei, Sui, and Tang dynasties, the flow patterns of the Yi, Luo, Chan, and Jian rivers were closely related to their geological setting. The orientations of these rivers are predominantly determined by the underlying geological fault lines of the basin. The orientations of the Yi and Luo rivers are mainly determined by east-west and northeast-oriented fault lines, with the flow path of the Luo River primarily influenced by the Matun-Yanshi fault and the Yi River influenced by the Yiyang-Yanshi fault. Jian and Chan Rivers share simultaneous spatial similarities and transient transformation similarities, both following city site migrations, turning from being sectioned eastward during Han and Wei dynasties to falling back to the natural southward flow during Sui and Tang dynasties. Luo River exhibited a trend of continual northward transformation during Han, Wei, Sui, and Tang dynasties, while Yi River constantly extends eastward and southward. Over historical periods, the Yi and Luo rivers gradually separated north and south, with their confluence point shifting eastward. Unequal north-south subsidence and a northward tilt of the sedimentary center caused Luo River to migrate northward, while a central bulge and ‘two cut first base’complex fault depression caused Yi River to extend eastward and southward.

  • Zhu Guobing, Huang Yijun
    Historical Geography Research. 2024, 44(1): 38-49. https://doi.org/10.20166/j.issn.2096-6822.L20220330

    The reasons for establishment and the setting process of the four Anfu Si Lu (安抚司路) located to ‘Hebei’ (the north of the Yellow River) during the Song Dynasty are still subject to debate. Through the perspective of historical political geography, this study traces the entire process of the formation of Hebei Four Anfusi Lu. It also draws from two clues of administrative division and organization to offer new interpretations and to enrich several historical details. The military administration of Hebei underwent a transition from generals guarding the borders in division during the reign of Emperor Taizu, to the deployment of Dubushu (field headquarter, 都部署) in Emperor Taizong’s era, to the deployment of three Dubushu in Emperor Zhenzong’s era. In the eighth year of Qingli under the reign of Emperor Renzong, the formal Hebei Four Anfushi (安抚使) established. Yet, the court did not adopt the proposal of establishing a Hebei Jinglue Anfushi (河北经略安抚使) in spite of the border crisis in the Qingli era. The frequent rebellion problems caused by arrogant soldiers and weak generals during the Qingli period were the fundamental reasons for the establishment of the clearly delineated Hebei Four Anfusi Lu.

  • Wu Yiqun, Wang Xuehua
    Historical Geography Research. 2024, 44(1): 50-61. https://doi.org/10.20166/j.issn.2096-6822.L20230149

    After the control of Xinjiang was restored, Qing Dynasty established the Kashgar Dao (喀什噶尔道) and Aksu Dao (阿克苏道) in the southern Xinjiang area in 1882, which was an important preparatory step for the Xinjiang Province and a concrete manifestation of continuous deepening of the national political system in the border regions. Subsequent territorial expansions and adjustments based on the basic concepts of ‘Liang Di Zhi Yi’(量地置邑) and ‘Zhi Guang Yi Xia’(治广以狭), were specific responses to the border defense crisis, territorial crisis and governance crisis in the administrative setting under the drastic changes of the current situation. This move highlighted the role of the political district setups in consolidating the border and perfecting grassroots governance, while laying the foundational framework of current administrative divisions in southern Xinjiang. Alongside the setting of ‘Zheng Qu Fen Deng’ (政区分等), there was a relatively mature system for the selection and appointment of officials, in order to maximize the achievement of local social governance on the ‘Ren Di Xiang Yi’ (人地相宜). Despite the clear lack of hierarchical grades in the newly established political district, they did not do so according to the rules, and the ‘Zheng Qu Fen Deng’ basically deviate from the selection of officials, which became the precursor of the national state and county ‘Ting Bu Xuan’(停部选) in 1908.

  • Zhang Qingyi
    Historical Geography Research. 2024, 44(1): 72-82. https://doi.org/10.20166/j.issn.2096-6822.L20220071

    The Tang Dynasty Chinese cliff carvings discovered in the Dil mountain of Ulziit in the central Gobi Province of Mongolia indicate that this area was an important node on the grassland transportation line at that time. The route through the desert to capital of the Uyghur Empire, as recorded in the New Book of Tang passed through this area as the ‘Eastern Uyghur Road’, also known as the ‘the road of having an audience with Tengri Khan’. The inscriptions were carved during the rule of restraint period of the Tang Dynasty in the second year of Linde, which confirmed the historical event that Emperor Gaozong of the Tang Dynasty offered sacrifices to heaven and earth in Mount Tai and invited the leaders of Tiele tribes in the Boreal desert to come, which reflected the communications between the Tang Dynasty and the northern nomads and the control of the Tang government over the vassal prefectures in the Boreal desert.

  • Urban and Rural Development and Population Mobility
    FU Runde, YANG Zhenshan
    Acta Geographica Sinica. 2024, 79(4): 819-836. https://doi.org/10.11821/dlxb202404001

    The quality of development is crucial for China to comprehensively build a socialist modern country. Drawing on related concepts of development in quality, the paper conceptualizes a city in high-quality development and proposes a stylish framework with five dimensions to evaluate it, in line with the New Development Philosophy, which is composed of innovation, coordination, greenness, openness and sharing. Using the methods of spatial analysis, club convergence test and spatial Durbin model, the paper identified the spatial evolution of the quality of city development in China and associated determinants during 2005-2020. On average, the level of city development quality increased by 48.4% during the study period. The number of cities at low-level of quality in development decreased dramatically, accompanied by a profound transformation in the spatial pattern of city development quality, which presents significant spatial aggregation. The spatial imbalance remains for cities with different development qualities, and the challenge is still huge to narrow the gap. With significant role differentiation among cities, a "pioneering-catching up" pattern emerges, and the 11 pioneering cities such as Beijing, Shanghai and Shenzhen have become the pioneers of high-quality development in China. Key determinants for cities achieving high quality in development includes urbanization level, public investment, digital economy, environmental regulation and economic growth, while there is inverted U-shaped relationship between city size and development quality. To achieve the goal of high-quality city development in the new era, it is necessary to focus on the development of cities in the central and western regions, making full use of the demonstration role of pioneers, promoting quantitative growth, strengthening environmental regulations, cultivating the new forms of digital economy, and optimizing the city size hierarchy.

  • National Spatial Optimization and Regional High-quality Development
    QIAO Yibo, HE Canfei
    Acta Geographica Sinica. 2024, 79(4): 909-930. https://doi.org/10.11821/dlxb202404006

    County has long been the basic unit of national governance in China. Yet, only limited policy attention has been paid to counties. Recently, the central government proposed to carry out county-level urbanization to further deepen the people-centered new urbanization strategy. In this situation, counties need to provide enough jobs and decent income for rural emigrants. However, this is only the case for a small fraction of counties with prosperous local economies, and most of the rest counties need to enhance their industrial development to absorb the rural emigrants. Since China's industrialization process is largely influenced by the government, boundary adjustment, such as turning counties into urban districts, may also influence the local industrial development in various ways. Relying on the National Annual Survey of Industrial Firms Database (1998-2015), this paper constructs a county manufacturing industry dataset with 1110 counties and 376 four-digit level industries. With an Evolutionary Economic Geography approach, this paper explores the causal impacts of turning counties into districts on counties' manufacturing upgrading by employing difference in differences in differences method (DID). The empirical results show that, first, after turning counties into districts, counties have higher probabilities to enter more complex industries and exit less complex industries. And in both cases, the impacts of turning counties into districts has a time lag. Second, at the macro county level, turning counties into districts could benefit manufacturing upgrading through population agglomeration, economic development, infrastructure construction, and public service improvement; at the micro firm level, turning counties into districts could upgrade manufacturing industries by promoting output, intermediate inputs, profit, innovation, and tax reduction. Turning counties into districts has the largest impact on manufacturing upgrading in the eastern region and has negative impact in the central region. These findings could not only provide empirical support for the future implementation of turning counties into districts, but also enrich the institutional perspective of Evolutionary Economic Geography on regional industrial evolution.