Exploring Regional Innovation Growth Through A Network Approach:A Case Study of the Yangtze River Delta Region,China

As the leading urban agglomeration in China,the Yangtze River Delta(YRD)is experiencing a factor-driven to innovationdriven transition.However,the dynamics of regional innovation growth are not yet fully understood.This paper combines the complex network methodology with spatial econometrics to disentangle the contributions of innovation endowments,innovation network flows,and innovation network positions to regional innovation growth,as well as their spatial spillover effects.The primary findings suggest that regional innovation growth results from the networked agglomeration economies,which is shaped by the interactions between agglomeration factors and network factors.Specifically,agglomeration factors play a fundamental role in regional innovation growth.In contrast,network factors,such as the network flows and network positions,may contribute to new path creation by promoting access to external innovation resources.Additionally,the institutional factors show multiplexity in fostering regional innovation patterns.Such findings indicate that the YRD region should shift the innovation growth pattern from competitive involution to mutually beneficial cooperation to reduce regional disparities.In this regard,the institutional capacity of organizing network flows and fostering reciprocal inter-city partnerships has become increasingly critical for promoting sustainable innovation and regional development.     

Industrial green spatial pattern evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.     

The Evolution of Regional Economic Resilience in the Old Industrial Bases in China: A Case Study of Liaoning Province,China

The economic transformation of the old industrial bases is a key research topic among geographers in China. In this paper, we propose that the concept of regional economic resilience(RER) has unique theoretical value in analyzing the economic transformation of the old industrial bases. We constructed an analytical framework and an index system and applied the conceptual tools to study the evolution of RER in the old industrial base of Liaoning Province in China, which is currently subjected to not only sudden shocks but ‘slow burn’—longer term processes of change that may nevertheless affect the regional economy. There are four main findings: first, the evolution of RER in Liaoning can be divided into four stages from 2000 to 2015. Liaoning is currently in its conservation-release period, and the next stage will be a release-reorganization period. Second, the RER of the majority of the studied cities is lower than the average value for Liaoning, and this is mainly attributed to the relatively weak vulnerability-resistance and adaptability-transformation capacity of these cities. Third, the RER levels of the 14 cities in Liaoning differ significantly. At the first level is Shenyang and Dalian, at the second level is Dandong and Yingkou, and the third level comprises the remaining cities. Fourth, regional economic resilience is mainly determined by vulnerability-resistance, which indirectly reflects Liaoning's lack of adaptability-transformation capacity, and the ability of the region to renew or create a new development path is weak.     

基于多源数据的长江经济带内河港口区位优势度评估

内河港口是内河航运纽带的重要节点,评估内河港口的区位优势度对长江经济带港口基础设施建设等具有重要意义。以2021年长江沿岸内河港口为研究对象,采用多源数据,结合长江内河港口辐射范围内的3个指标并对原模型进行改进,结合AHP-EWM模型计算长江经济带长江沿岸28个港口的区位优势度,研究结果显示：① 除重庆和武汉以外,江苏省以外的其他省份港口辐射范围内交通网络密度都比较低;从交通干线影响度来看,分布比较均衡且数值较为相近;而城市经济影响力的空间分布较为无序;② 根据区位优势度的高低以及空间分布得出长江经济带货运港口空间格局为“三中心,一组团”的空间格局;③ 将内河港口按长江岸线所属省份进行划分后发现：江西省3个港口区位优势度差异最小,但其优势度也整体偏低;安徽省与江西省类似;江苏省整体优势度较高且差异小,湖北省的优势度差异最大,表明存在基础设施建设不均衡等问题且亟需改善。研究成果可对长江经济带内各个港口范围内基础设施建设、道路交通规划、港口选址等方面提供指导性意见帮助打通铁路、高等级公路进港“最后一公里”。     

长江三角洲地区高温热浪人群健康风险评价

在全球极端气象、气候事件频发的背景下,获取高分辨的灾害风险信息对于区域防灾减灾决策具有重要的参考价值。而在当前的灾害风险评估中,基于行政单元的人口和社会经济等承灾体信息与栅格水平上的致灾因子普遍存在空间不匹配的现象。本文通过融合多源遥感数据和人口、社会经济统计数据,在利用人居指数对高温人口暴露进行空间化的基础上,获取了250 m分辨率的长江三角洲地区高温热浪人群健康风险空间格局。结果表明,风险等级较高的地区集中在上海、常州、杭州、宁波、无锡、嘉兴、泰州等城市的中心城区,主要是较高的人口暴露度和城市高温共同作用的结果;而大城市近郊以及各规模较小的城区的风险等级次之;相对欠发达地区虽然人口暴露程度较低,但较高的高温危险性和社会经济脆弱性指数使得这些地区的高温人群健康风险也不容忽视。识别高风险地区的风险主导因子对于提高人群高温适应能力以及减轻高温健康风险具有重要意义。     

Tourism and Land Transformation:A Case Study of the Li River Basin,Guilin,China

Land-use change is intertwined with tourism because land is used as a resource for human activities.Land-use change also provides an opportunity to evaluate the status of the ecoenvironment.Understanding the relationship between tourism and land use change would help to predict the effect of tourism on land use and encourage sustainable tourism development.Using the Li River Basin as a case study,a hybrid approach using multilevel modeling and logistic regressions was employed to analyze the distribution of land-usechange between 1989 and 2010 to examine potential driving factors.Results reveal that rapid tourism development and construction expansion expose this area to risk of deforestation and forest degradation.Construction increased by 141% between 1989 and 2000 and by 195% between 2000 and 2010.The primary driving force for construction expansion shifted from population growth between 1989 and 2000 to investment growth after 2000.New construction primarily occurred on crop and woodlands areas,with shares of 81.25% and 6.38%,respectively,between 1989 and 2000,and with shares of 57.79% and 15.29%,respectively,between 2000 and 2010.Moreover,these drastic increases in construction also led to frequent transitions between croplands,woodlands,and grasslands.Traits including distances to urban areas and roads and scenic locations exerted significant effects on land-use change.Woodland regrowth in the areas thatsurround scenic locations consisted of fluctuating woodlands,whereas stable woodland regrowth was often absent in these areas.Likewise,permanent woodland clearing tended to be closed to near scenic locations.That is,construction at scenic locations negatively affected forest conservation in the Li River Basin.     

长江三角洲地区制造业集群辨识及空间组织特征

本文基于投入产出表的主成分分析和企业空间分布数据的聚类分析,从产业功能联系和空间联系角度辨识长江三角洲地区主要的制造业集群,并从企业、产业、区域3个维度刻画和比较不同类型制造业集群的空间组织特征。研究表明,长江三角洲地区存在冶金及装备、电子信息、纺织及服装等12个垂直联系紧密的制造业群组,并高度集聚于沿沪宁线、沪杭线、杭甬线的“Z”字形区域。冶金及装备、电子信息和纺织及服装3个制造集群分别呈现轮辐式、卫星式和马歇尔式产业集群组织方式。上海和江苏的制造业集群在集群规模、大型企业占比、外资企业占比等方面,要明显高于浙江的制造业集群。     

Spatial Pattern and Benefit Allocation in Regional Collaborative Innovation of the Yangtze River Delta,China

As an important step enhancing regional innovation, researches on collaborative innovation have attracted much more attention recently. One significant reason is that cities can get excessive benefits while they take collaborative innovation activities. Based on the theories of innovation geography, this paper takes the collaborative innovation of the Yangtze River Delta(YRD) Urban Agglomeration as a case study and measures the collaborative innovation capacity from innovation actors and innovat...     

Urban Chemical Industrial Cluster Area Restructuring and Determin-ants:A Case Study of a Typical Old Chemical Industry Area Along the Yangtze River,China

China is in a transitional period between urban renewal and industrial change.In this period,the focus has been on the sub-urbanization of enterprises and land ...     

Cloud Data and Computing Services Allow Regional Environmental Assessment:A Case Study of Macquarie-Castlereagh Basin,Australia

Large amounts of data at various temporal and spatial scales require terabyte(TB) level storage and computation, both of which are not easy for researchers to access. Cloud data and computing services provide another solution to store, process, share and explore environmental data with low costs, stronger computation capacity and easy access. The purpose of this paper is to examine the benefits and challenges of using freely available satellite data products from Australian Geoscience DataCube and Google Earth Engine(GEE) online data with time series for integrative environmental analysis of the Macquarie-Castlereagh Basin in the last 15 years as a case study. Results revealed that the cloud platform simplifies the procedure of traditional catalog data processing and analysis. The integrated analysis based on the cloud computing and traditional methods represents a great potential as a low-cost, efficient and user-friendly method for global and regional environmental study. The user can save considerable time and cost on data integration. The research shows that there is an excellent promise in performing regional environmental analysis by using a cloud platform. The incoming challenge of the cloud platform is that not all kinds of data are available on the cloud platform. How data are integrated into a single platform while protecting or recognizing the data property, or how one portal can be used to explore data archived on different platforms represent considerable challenges.     

Three Types of Spatial Function Zoning in Key Ecological Function Areas Based on Ecological and Economic Coordinated Development: A Case Study of Tacheng Basin,China

Three types of spatial function zoning is an effective measure for regional environmental protection and orderly development.For ecological and economic coordinated development, spatial function zones should be divided scientifically to clear its direction of development and protection. Therefore, based on ecological constraints, a beneficial discussion would be about the key ecological function areas adopting the concept of ecological protection restriction and supporting socioeconomic development for spatial function zoning. In this paper, the researchers, taking Tacheng Basin, Xinjiang of China as an example, choose township as basic research unit and set up an evaluation index system from three aspects, namely, ecological protection suitability, agricultural production suitability, and urban development suitability, which are analyzed by using spatial analysis functions and exclusive matrix method. The results showed that: 1) This paper formed a set of multilevel evaluation index systems for three types of spatial function zoning of the key ecological function areas based on a novel perspective by scientifically dividing Tacheng Basin into ecological space, agricultural space, and urban space,which realized the integration and scientific orientation for spatial function at the township scale. 2) Under the guidance of three types of spatial pattern, the functional orientation and suggestions of development and protection was clearly defined for ecological protection zones,ecological economic zones, agricultural production zones, and urban development zones. 3) A new idea of space governance is provided to promote the coordinated and sustainable development between ecology and economy, which can break the traditional mode of thinking about regional economic development, and offers a scientific basis and reference for macro decision-making.     

长江经济带城乡一体化对能源效率的空间效应分析

城乡一体化作为新的经济增长动能,是建设高效的能源经济体系、平衡经济社会发展与生态环境保护的关键性途径。因此城乡一体化对能源效率的效应分析成为促进经济社会可持续发展的重要课题。本文以长江经济带各省市为研究对象,采用DEA测度了考虑非期望产出的能源效率值,并分析其时空上的分异特征,通过构建经济、社会和基础设施3个维度的综合指标体系评价城乡一体化水平,以此为基础运用Moran's I指数确定了能源效率、城乡一体化水平及其他影响因素的空间相关性,最后运用混合地理加权回归估计城乡一体化及3个控制变量的回归参数值并作空间效应分析。得出结论:① 从空间相关性分析来看,长江经济带的城乡一体化发展水平对能源效率具有正向作用,同时经济发展水平和产业结构也对能源效率有正向影响,而技术进步则在一定条件下与能源效率呈负相关关系;② 从回归系数的估计值来看,城乡一体化对能源效率的影响程度要小于技术进步和产业结构,而经济发展水平对能源效率的影响程度最小;③ 城乡一体化水平对能源效率的正向影响程度随着能源效率的上升呈现出先上升后下降的趋势,并且其影响在空间分布上自东向西呈现出递增的特征;④ 长江经济带的能源效率呈现显著的空间相关性和空间异质性。基于此,对长江经济带推进城乡一体化进程中的能源效率提升具有重要意义。     

地理国情信息支持下的长江经济带空间开发评价

通过构建空间开发评价指标体系,利用现势性强、精细化程度高的地理国情普查成果,以及社会经济统计资料,研究分析了长江经济带区域开发的适宜程度,对其自然条件和空间开发程度进行了评价,空间化、定量化地呈现了长江经济带空间开发的现状,为长江经济带绿色发展提供信息支撑。     

Spatial-temporal Analysis and Prediction of Precipitation Extremes:A Case Study in the Weihe River Basin,China

Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-tem-poral characteristics of extreme pre...     

基于移去-恢复法的区域大气负荷影响精化——以滇西地区为例

传统的大气负荷改正根据全球大气压模型计算获取,但全球大气压模型中、长波信号占优,缺乏突显区域特征信息的短波信号,而在研究高精度的区域大气负荷影响时,空间信息中的短波信号不可忽视。为此,根据地球重力场理论,引入移去-恢复思想,结合ECMWF提供的全球大气压变化数据和区域高分辨率大气压变化数据（CLDAS-V2.0）,基于负荷球谐系数和区域负荷格林函数方法得到大气压变化对滇西地区的负荷影响。结果表明,得到的大气负荷形变场在空间和时间分变率上均有一定提高。利用移去-恢复法计算区域大气压负荷影响,可为固体地球形变和CORS站时序分析提供参考。     

地理科学系统理论及其在现代经济建设中的意义——以长江三角洲为例

论述了地理科学系统理论与过去地理学的人地关系理论之间的差异,其不同点:(1)地理科学系统强调人与地之间的相互影响;(2)地理科学系统指出研究范围包括过去、现在和将来;(3)地理科学系统理论既适用于某一国家、地区,也适用于研究全球变化。同时论及了其在现代经济建设中的意义。     

Ecological Network Analysis Quantifying the Sustainability of Regional Economies: A Case Study of Guangdong Province in China

To meet the challenge of sustainable development, sustainability must be made. Ecological network analysis(ENA) was introduced in this paper as an approach to quantitatively measure the growth, development, and sustainability of an economic system. The Guangdong economic networks from 1987 to 2010 were analyzed by applying the ENA approach. Firstly, a currency flow network among economic sectors was constructed to represent the Guangdong economic system by adapting the input-output(I-O) table data. Then, the network indicators from the ENA framework involving the total system throughput(TST), average mutual information(AMI), ascendency(A), redundancy(R) and development capacity(C) were calculated. Lastly, the network indicators were analyzed to acquire the overall features of Guangdong's economic operations during 1987–2010. The results are as follows: the trends of the network indicators show that the size of the Guangdong economic network grows exponentially at a high rate during 1987–2010, whereas its efficiency does not present a clear trend over its whole period. The growth is the main characteristic of the Guangdong economy during 1987–2010, with no clear evidence regarding its development. The quantitative results of the network also confirmed that the growth contributed to a great majority of the Guangdong economy during 1987–2010, whereas the development's contribution was tiny during the same period. The average value of the sustainability indicator(α) of the Guangdong economic network was 0.222 during 1987–2010, which is less than the theoretically optimal value of 0.37 for a sustainable human-influenced system. The results suggest that the Guangdong economic system needs a further autocatalysis to improve its efficiency to support the system maintaining a sustainable evolvement.     

Mapping Soil Salinity Using a Similarity-based Prediction Approach:A Case Study in Huanghe River Delta,China

Spatial distribution of soil salinity can be estimated based on its environmental factors because soil salinity is strongly affected and indicated by environmental factors. Different with other properties such as soil texture, soil salinity varies with short-term time. Thus, how to choose powerful environmental predictors is especially important for soil salinity. This paper presents a similarity-based prediction approach to map soil salinity and detects powerful environmental predictors for the Huanghe(Yellow) River Delta area in China. The similarity-based approach predicts the soil salinities of unsampled locations based on the environmental similarity between unsampled and sampled locations. A dataset of 92 points with salt data at depth of 30–40 cm was divided into two subsets for prediction and validation. Topographical parameters, soil textures, distances to irrigation channels and to the coastline, land surface temperature from Moderate Resolution Imaging Spectroradiometer(MODIS), Normalized Difference Vegetation Indices(NDVIs) and land surface reflectance data from Landsat Thematic Mapper(TM) imagery were generated. The similarity-based prediction approach was applied on several combinations of different environmental factors. Based on three evaluation indices including the correlation coefficient(CC) between observed and predicted values, the mean absolute error and the root mean squared error we found that elevation, distance to irrigation channels, soil texture, night land surface temperature, NDVI, and land surface reflectance Band 5 are the optimal combination for mapping soil salinity at the 30–40 cm depth in the study area(with a CC value of 0.69 and a root mean squared error value of 0.38). Our results indicated that the similarity-based prediction approach could be a vital alternative to other methods for mapping soil salinity, especially for area with limited observation data and could be used to monitor soil salinity distributions in the future.     

Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City,China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index(LMDI) model. The main conclusions are as follows: 1) Total anthropogenic carbon emission of Nanjing increased from 1.22928 x 107 t in 2000 to 3.06939 x 107 t in 2009, in which the carbon emission of Inhabitation, mining & manufacturing land accounted for 93% of the total. 2) The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining & manufacturing land was the highest(200.52 t/ha), which was much higher than that of other land use types. 3) The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity(2.83 t/ha) in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4) Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5) Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.