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Examining the Spatiotemporal Dynamics and Determinants of Land Urbanization in Prefecture-level Cities,China

Chinese geographical Science 2024年第1期34卷 19-33页

作者： YANG Zhen ZHU Huxiao ZHANG Xinlin OU Xiangjun School of Geography Geomatics and Planning&Urban-rural Integration Development Research InstituteJiangsu Normal UniversityXuzhou221116China

Examining the spatiotemporal dynamics and determinants of land urbanization is critical for promoting healthy urban development and the rational use of land resources.Based on the dataset consisting of land use change data and selected factors in 2010 and2020,this study used visual analysis to reveal the spatiotemporal dynamics of land urbanization across prefecture-level cities in China.Meanwhile,the driving forces underlying land urbanization were examined by using geographical detector technique.Following are the findings:1)we find that there exist notable spatial variances in land urbanization across prefecture-level cities.Currently,the differentiation in land urbanization between the northern and southern cities is more pronounced than that between the coastal and inland cities,or between the eastern and western cities.Prefecture-level cities located in central and western China have experienced the most rapid growth in land urbanization.Conversely,the growth rate in northeastern China is the lowest,while the velocity in eastern China remains relatively stable.By using spatial autocorrelation analysis,this study reveals that the land urbanization level in prefecture-level cities has significant spatial agglomeration.2)We further find that land urbanization in China is influenced by factors related to urban land supply and demand,and urban population growth,economic growth,land financial and political incentive have greater impact on land urbanization than other factors.3)We also find that the impacts of determinants on China’s land urbanization vary over time,the explanatory power of economic development increased,while the explanatory power of state forces declined.We argue that integrating the supply and demand factors of land urbanization can provide a more comprehensive understanding of the driving mechanisms underlying land urbanization in China and other transitional countries,and help decision-makers in these countries formulate more detailed and specific land urbanization policies.

关键词： land urbanization spatial pattern influencing factor geographical detector China

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Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

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Chinese geographical Science 2024年第2期34卷 210-229页

作者： JIANG Hongtao YIN Jian ZHANG Bin WEI Danqi LUO Xinyuan DING Yi XIA Ruici Center for Western China Modernization Guizhou University of Finance and EconomicsGuiyang 550025China College of Big Data Application and Economic Guizhou University of Finance and EconomicsGuiyang 550025China Key Laboratory of Green Fintech Guizhou University of Finance and EconomicsGuiyang 550025China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

关键词： industrial carbon emission intensity carbon emission social network analysis Location Indicators of Spatial Association(LISA) geographical detector multi-scale geographically weighted regression Pearl River Basin(PRB),China

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Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

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Journal of Mountain Science 2024年第1期21卷 218-235页

作者： WANG Yumeng DENG Qingchun YANG Haiqing LIU Hui YANG Feng ZHAO Yakai School of geographical Sciences China West Normal UniversityNanchong 637009China Sichuan Provincial Engineering Laboratory of Monitoring and Control for Soil Erosion in Dry Valleys China West Normal UniversityNanchong 637009China Liangshan Soil Erosion and Ecological Restoration in Dry Valleys Observation and Research Station Xide 616753China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors af

关键词： Rural settlements Location entropy geographical detector Spatiotemporal differentiation Influencing factors

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Assessing environmental factors associated with regional schistosomiasis prevalence in Anhui Province,Peoples’Republic of China using a geographical detector method

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Infectious Diseases of Poverty 2017年第1期6卷 761-768页

作者： Yi Hu Congcong Xia Shizhu Li Michael PWard Can Luo Fenghua Gao Qizhi Wang Shiqing Zhang Zhijie Zhang Department of Epidemiology School of Public HealthFudan UniversityShanghai 200032China Key Laboratory of Public Health Safety Ministry of EducationShanghaiChina Laboratory for Spatial Analysis and Modeling School of Public HealthFudan UniversityShanghaiChina Collaborative Innovation Center of Social Risks Governance in Health School of Public HealthFudan UniversityShanghaiChina National Institute of Parasitic Diseases Chinese Center for Disease Control and PreventionKey Laboratory of Parasite and Vector BiologyMinistry of HealthWHO Collaborating Center for Tropical diseasesShanghaiPeople’s Republic of China Faculty of Veterinary Science The University of Sydney NSWSydneyAustralia Department of Environmental Art and Architecture Changsha Environmental Protection Vocational Technical CollegeChangshaHunanPeople’s Republic of China Anhui Institute of Parasitic Diseases WuhuPeople’s Republic of China No.130 Dong’an Road Xuhui DistrictShanghai 200032China

Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multiple biological characteristics and social factors but also factors can play a role.Few studies have assessed the exact and interactive influence of each factor promoting schistosomiasis transmission.Methods:We used a series of different detectors(i.e.,specific detector,risk detector,ecological detector and interaction detector)to evaluate separate and interactive effects of the environmental factors on schistosomiasis prevalence.Specifically,(i)specific detector quantifies the impact of a risk factor on an observed spatial disease pattern,which were ranked statistically by a value of Power of Determinate(PD)calculation;(ii)risk detector detects high risk areas of a disease on the condition that the study area is stratified by a potential risk factor;(iii)ecological detector explores whether a risk factor is more significant than another in controlling the spatial pattern of a disease;(iv)interaction detector probes whether two risk factors when taken together weaken or enhance one another,or whether they are independent in developing a disease.Infection data of schistosomiasis based on conventional surveys were obtained at the county level from the health authorities in Anhui Province,China and used in combination with information from Chinese weather stations and internationally available environmental data.Results:The specific detector identified various factors of potential importance as follows:Proximity to Yangtze River(0.322)>Land cover(0.285)>sunshine hours(0.256)>population density(0.109)>altitude(0.090)>the normalized different vegetation index(NDVI)(0.077)>land surface temperature at daytime(LST_(day))(0.007).The risk detector indicated that areas of schistosomiasis high risk were located within a buffer distance of 50 km from Yangtze River.The ecological detector disclosed that the factors

关键词： Schistosoma japonicum geographical detector Spatial variation analysis Environmental factors Geographic information systems China

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长三角城市群多情景暴雨人口暴露度时空演变分析

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Journal of geographical Sciences 2024年第4期34卷 654-680页

作者：张亚茹姚蕊朱治州金恒旭张书亮 Key Laboratory of VGE of Ministry of Education Nanjing Normal UniversityNanjing 210023China Jiangsu Center for Collaborative Innovation in geographical Information Resource Development and Application Nanjing210023China School of Geography and Tourism Anhui Normal UniversityWuhu 241002AnhuiChina

Population exposure is a dominant representation of rainstorm hazard risks. However, the refined precipitation data in temporal resolution and the comparison of exposure to different rainstorm events remain relatively unexplored. Hourly precipitation data from 165meteorological stations w used to investigate the spatiotemporal evolution of population exposure to different rainstorm scenarios in the prefecture-level cities for different periods and age groups. The geographical detector was adopted to quantitatively analyze the influencing factors and contribution rates to changes in population exposure during each period. The results revealed that population exposure to persistent rainstorms and abrupt rainstorms was low in the center and high in the surrounding areas, and the high exposure value decreased significantly in the 2010s. Additionally, as the duration of rainstorm events increased, the center of the high-value area of population exposure shifted southward. The distribution of population exposure was closely related to the age structure, demonstrating strong consistency with the distribution of different age groups. Except for abrupt rainstorms, the contribution rates of the average land GDP and urbanization rate to the exposure of all rainstorm scenarios increased significantly. This implies that the main factors influencing population exposure have shifted from meteorological to socioeconomic factors.

关键词： rainstorm events population exposure multiple scenarios spatiotemporal characteristics geographical detector

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中国城市绿色技术创新空间格局演化及驱动因素

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Journal of geographical Sciences 2024年第2期34卷 289-308页

作者：李影方远平孟庆港 School of Economics and Management South China Normal UniversityGuangzhou 510006China School of Geography South China Normal UniversityGuangzhou 510006China School of Statistics and Mathematics Shandong University of Finance and EconomicsJinan 250014China

This study uses green patent data from 264 cities in China between 2006 and 2020 to examine the evolution of spatial patterns in urban green technology innovation(GTI)across the country and identify the underlying driving factors.Moran’s I index,Getis-Ord Gi*index,standard deviation ellipse,and geographical detector were used for the analysis.The findings indicate an increase in the overall level of GTI within Chinese cities.Provincial capitals,cities along the eastern coast,and planned cities emerge as the prominent“highlands”of GTI,whereas the“lowlands”of GTI predominantly lie in the western and northeastern regions,forming the spatial pattern of“hot in the east and center of the country,cold in the northwest and the northeast.”The distribution center of gravity of GTI is toward the southwest of China.The distribution pattern is in the“northeast–southwest”direction,which is characterized by“diffusion,”followed by“agglomeration.”Differences in economic development have the highest determining power on the spatial differentiation of GTI in Chinese cities,whereas differences in environmental regulation and industrial structure have the lowest degree of relative influence.The interaction between any two factors contributes to an amplified explanatory power in understanding the differences in GTI.

关键词： green technology innovation spatial pattern driving factors geographical detector Chinese city

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Specifc urban units identifed in tuberculosis epidemic using a geographical detector in Guangzhou,China

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Infectious Diseases of Poverty 2022年第2期11卷 98-98页

作者： Hongyan Ren Weili Lu Xueqiu Li Hongcheng Shen State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China 不详

Background:A remarkable drop in tuberculosis(TB)incidence has been achieved in China,although in 2019 it was still considered the second most communicable disease.However,TB’s spatial features and risk factors in urban areas remain poorly understood.This study aims to identify the spatial diferentiations and potential infuencing factors of TB in highly urbanized regions on a fne scale.Methods:This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou,China.TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention.Before using Pearson correlation and a geographical detector(GD)to identify potential infuencing factors,we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales.Results:Owing to its strong spatial autocorrelation(Moran’s I=0.33,Z=4.71),the 2 km×2 km grid was selected as the spatial scale.At this level,TB incidence was closely associated with most socioeconomic variables(0.31

关键词： Tuberculosis geographical detector Specifc urban units Pairwise interaction Guangzhou China

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Spatial-temporal Evolution and Influencing Factors of Digital Financial Inclusion: County-level Evidence from China

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Chinese geographical Science 2023年第2期33卷 221-232页

作者： ZHANG Guojun CHEN Yu WANG Gengnan ZHOU Chunshan School of Finance Guangdong University of Finance and EconomicsGuangzhou 510320China School of Geography and Planning Sun Yat-sen UniversityGuangzhou 510275China

The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.

关键词： digital financial inclusion spatiotemporal characteristics influencing factors geographical detector China

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A practical method for identifying key factors in the distribution and formation of heavy metal pollution at a smelting site

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Journal of Environmental Sciences 2023年第5期127卷 552-563页

作者： Jiaqing Zeng Wenshun Ke Min Deng Jingqiang Tan Chuxuan Li Yizhi Cheng Shengguo Xue School of Metallurgy and Environment Central South UniversityChangsha 410083China School of Geosciences and Info-physics Central South UniversityChangsha 410083China New World Environment Protection Group of Hunan Changsha 410083China

Smelting activities are the main pathway for the anthropogenic release of heavy metals(HMs)into the soil-groundwater environment.It is vital to identify the factors affecting HMs pollution to better prevent and manage soil pollution.The present study conducted a comprehensive investigation of HMs in soil from a large abandoned Zn smelting site.An integrated approach was proposed to classify and quantify the factors affecting HMs pollution in the site.Besides,the quantitative relationship between hydrogeological characteristics,pollution transmission pathways,smelting activities and HMs pollutionwas established.Results showed that the soils were highly contaminated by HMs with a pollution index trend of As>Zn>Cd>Pb>Hg.In identifying the pollution hotspots,we conclude that the pollution hotspots of Pb,As,Cd,and Hg present a concentrated distribution pattern.Geo-detector method results showed that the dominant driving factors for HMs distribution and accumulation were the potential pollution source and soil permeability.Additionally,the main drivers are variable for different HMs,and the interaction among factors also enhanced soil HMs contamination.Our analysis illustrates how the confounding influences from complex environmental factors can be distilled to identify key factors in pollution formation to guide future remediation strategies.

关键词： Zinc smelting site Heavy metal pollution Spatial distribution Hotspot identification geographical detector

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Flash Flood Risk Assessment and Driving Factors:A Case Study of the Yantanxi River Basin,Southeastern China

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International Journal of Disaster Risk Science 2022年第2期13卷 291-304页

作者： Liutong Chen Zhengtao Yan Qian Li Yingjun Xu Key Laboratory of Environmental Change and Natural Disaster Ministry of EducationFaculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Academy of Disaster Reduction and Emergency Management Ministry of Emergency Management and Ministry of EducationBeijing Normal UniversityBeijing 100875China School of National Safety and Emergency Management Beijing Normal UniversityBeijing 100875China

In the context of climate change,the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China,posing a serious threat to the socioeconomic development in the region.This study took tropical cyclones–extreme precipitation–flash floods as an example to carry out a risk assessment of flash floods under climate change in the Yantanxi River Basin,southeastern China.To obtain the flash flood inundation characteristics through hydrologic–hydrodynamic modeling,the study combined representative concentration pathway(RCP)and shared socioeconomic pathway(SSP)scenarios to examine the change of flash flood risk and used the geographical detector to explore the driving factors behind the change.The results show that flash flood risk in the Yantanxi River Basin will significantly increase,and that socioeconomic factors and precipitation are the main driving forces.Under the RCP4.5-SSP2 and RCP8.5-SSP5 scenarios,the risk of flash floods is expected to increase by 88.79%and 95.57%,respectively.The main drivers in the case study area are GDP density(q=0.85),process rainfall(q=0.74),asset density(q=0.68),and population density(q=0.67).The study highlights the influence of socioeconomic factors on the change of flash flood disaster risk in small river basins.Our findings also provide a reference for regional planning and construction of flood control facilities in flash flood-prone areas,which may help to reduce the risk of flash floods.

关键词： Asset values China Climate change Extreme precipitation Flash flood risk geographical detector Tropical cyclones

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