珠三角流动人口的代际就业结构分异及影响因素——基于六城市的调查分析

基于珠三角六城市流动人口的问卷调查数据,划分流动人口就业类型,从职业布局和多样化指数的角度比较了新生代、中生代和老一代三代流动人口职业结构差异,利用无序多分类Logistic模型对影响因素进行探究。研究发现：1）珠三角流动人口整体就业水平不高,就业结构在代际间分异明显。新生代在技术型就业和公司文员型就业上表现出优势,中生代在各行业就业相对均衡,老一代多被束缚在以体力劳动为主的基础型部门;就业多样化水平随代际的升高而下降。2）代际就业结构的影响因素及影响方式存在共性和差异,共性因子为受教育程度、月薪水平和性别;外出务工时间正向影响新生代服务型和管理型就业,工作环境稳定的职业对已婚新生代更具吸引力,中生代对户籍和工作保障因子更为敏感。政府可从代际就业特征出发,为流动人口制定有针对性的就业政策;针对就业市场中女性和农村户籍人口的弱势地位,为其提供就业引导,创造健康的就业环境,提高流动人口整体就业水平。     

基于开放大数据的广州市中心城区职住平衡特征研究

以广州市中心城区为例,借助百度热力图、百度实时路况和百度地图POI数据,从中观层面多角度综合分析广州市中心城区就业与居住的空间分布关系。结果显示：1）工作时间段人口聚集的高值区整体呈带状分布,斑块较为细碎,但绝大部分集中在核心地带;人口主要高度集中于各区的商业繁华地段与交通线路周围。而休息时间段的高值区则相对集中分布,用地效率较高,表现出多中心的圈层结构;人口主要高度集中分布在传统的老城居住区和新开发的商业住宅区,与核心商圈相对错开。2）不管是在上班时段还是休息时段,人口聚集程度越高的地区,POI设施密度表现越显著;这意味着人口的聚集具有一定的选择性,主要集中在城市基础设施发展较完备的区域。3）广州市中心城区各街道的职住比介于0.73~1.54,职住相对平衡,区域之间差异较小。其中,分值较高的街道多分布于核心地带（主要集中在越秀区、荔湾区北部和天河区南部）,分值较低的街道多分布于核心地带的外围或边缘地区（主要在海珠区、荔湾区和白云区零散分布）。4）从城市交通响应上看,广州市中心城区工作日内早高峰的拥堵度大于晚高峰,但总体路况变化跨度不大,区内并没有出现特别严重的“潮汐通勤”现象。     

长江经济带城市群要素集聚能力差异的比较研究

城市群作为当前区域发展的主要空间载体,在区域发展竞争中扮演着越来越重要的角色。论文结合互联网大数据抓取等手段,以长江经济带5个城市群为研究对象,对城市群间要素集聚能力差异进行比较研究,发现：① 长江经济带城市群间要素集聚能力差异与长江经济带社会经济发展的区域差异相吻合,城市群要素集聚格局呈现出由东向西梯度衰减的分布特征;② 城际层面要素集聚能力差异的两极分化现象显著,以城市群首位城市为中心的要素集聚“核心—边缘”空间结构特征较为鲜明;③ 长江经济带城市群内科技创新、对外开放、金融等要素的集聚格局具有明显的差异分化和集聚分布指向特征;④ 长江经济带城市(群)要素集聚能力等级规模结构分布总体符合位序-规模法则,可分为“均衡型”和“离散型”2种类型,首位城市要素集聚首位度随城市群要素集聚能力高低呈现出“两端高、中间低”的特征。     

湖南省武陵山片区人口城镇化与流通产业发展协同演化及其减贫效应研究

运用协同度模型、空间ESDA、趋势面分析和面板计量回归模型,分析湖南省武陵山片区2001—2017年人口城镇化与流通产业发展协同的时空演化特征及其减贫效应。研究发现：湖南省武陵山片区人口城镇化与流通产业协同发展整体呈上升趋势但水平偏低,不同板块间协同水平差异显著且有扩大倾向;具有“集聚–分散–集聚”空间循环过程,局部空间极化效应明显,形成邵阳板块的显著热点区和湘西自治州板块的显著冷点区;协同发展“东高西低”空间分布格局更趋明显,“北高南低”分布态势减弱;两者协同发展对农民收入提升、贫困减缓具有显著正向促进作用,进一步空间效应分解发现协同减贫的空间正外溢性显著;实施人口城镇化与流通产业发展“双轮”协同驱动战略是实现乡村振兴的现实需要,也是落实高质量脱贫方略的重要支撑。     

浙江省人口健康脆弱性评估及影响因素分析

运用集对分析法从敏感性和应对性2个方面对浙江省11个地市的人口健康脆弱性进行评估。研究表明：① 从敏感性和应对性2个维度对城市人口健康脆弱性进行评估的方法具有一定可靠性,但在突发大型流行性病毒感染疫情的情境下仍需进一步完善;② 各地市脆弱性指数排名与敏感性指数保持较高一致性,而与应对性指数则表现出异质性和随机性,认为降低敏感性是降低城市人口健康脆弱性指数的关键;③ 城市人口健康脆弱性评价还应该增加城市对大型突发公共卫生事件的敏感性和应对能力的考量,相应的评估方法和模型仍有待进一步研究。     

城市内涝灾害受灾人口评估方法与实证研究：以哈尔滨市道里区为例

城市内涝灾害频发,对居民生命安全造成严重威胁,为提高城市内涝灾害受灾人口评估精度,提出一种更为精确的受灾人口评估方法。以哈尔滨市道里区为研究区,以城市内涝灾害受灾人口为研究对象,运用一、二维非恒定流为主控方程,构建城市内涝数值模拟模型,并结合受灾人口分布特点,综合构建基于土地利用的人口随时间变化的计算模型。实现在模拟内涝灾害影响范围基础上,利用受灾人口计算模型提取白天与夜晚受灾人口分布情况。结果表明：研究区在百年一遇降雨情景下,有25条街道会发生不同程度积水,积水深度范围值为0.10~1.42 m;此级别内涝灾害在白天11条街道受灾人口数量最大值达到3 500人,夜晚10条街道受灾人口数量最大值为720人。     

长江三角洲人口分布演变、偏移增长及影响因素

在长江三角洲区域一体化上升为国家战略背景下,论文运用核密度、重心、集中指数和偏移—分享等方法,研究2000—2018年长江三角洲人口时空演变规律,并采用定量方法探讨人口偏移增长影响因素。结果表明：① 部分城市主导下的人口集散趋势转变,并未显著改变区域人口不均衡格局,且集中度呈现稳步增长态势。② 基于偏移—分享法的研究发现,人口增长格局转变主要表现为部分欠发达地区人口增速加快,如三省一市上安徽省转变为正偏移增长、城市尺度上核心发达城市为主的正偏移增长向部分欠发达城市为主的正偏移增长转变、县域尺度上正偏移市辖区由核心区向边缘区的转移,但人口向少数大城市、市辖区集聚的态势显著,而多样化的人口偏移增长态势表征了未来城市发展策略的差异化需求。③ 经济因素、社会发展和财政水平等是长江三角洲人口偏移增长的重要驱动力,而影响因素的时空演变表明,未来人口均衡化政策的制定不仅要因地制宜,更要与时俱进。     

Population,urbanization and economic scenarios over the Belt and Road region under the Shared Socioeconomic Pathways

The countries throughout the Belt and Road region account for more than 60% of the world's population and half of the global economy. Future changes in this area will have significant influences on the global economic growth, industrial structure and resource allocation. In this study, the proportion of the urban population to the total population and the gross domestic product were used to represent the levels of urbanization and economic development, respectively. The population, urbanization and economic levels of the Belt and Road countries for 2020–2050 were projected under the framework of the IPCC's shared socioeconomic pathways(SSPs), and the following conclusions are drawn.(1) The population, urbanization and economic levels in the Belt and Road region will likely increase under all five pathways. The population will increase by 2%–8%/10 a during 2020–2050 and reach 5.0–6.0 billion in 2050. Meanwhile, the urbanization rate will increase by 1.4%–7.5%/10 a and reach 49%–75%. The GDP will increase by 17%–34%/10 a and reach 134–243 trillion USD.(2) Large differences will appear under different scenarios. The SSP1 and SSP5 pathways demonstrate relatively high urbanization and economic levels, but the population size is comparatively smaller; SSP3 shows the opposite trend. Meanwhile, the economy develops slowly under SSP4, but it has a relatively high urbanization level, while SSP2 exhibits an intermediate trend.(3) In 2050, the population will increase relative to 2016 in most countries, and population size in the fastest growing country in Central Asia and the Middle East countries will be more than double. Urbanization will develop rapidly in South Asia, West Asia and Central Asia, and will increase by more than 150% in the fastest growing countries. The economy will grow fastest in South Asia, Southeast Asia and West Asia, and increase by more than 10 times in some counties with rapid economic development.     

Analysis of city centrality based on entropy weight TOPSIS and population mobility: A case study of cities in the Yangtze River Economic Belt

Based on statistical data and population flow data for 2016,and using entropy weight TOPSIS and the obstacle degree model,the centrality of cities in the Yangtze River Economic Belt(YREB)together with the factors influencing centrality were measured.In addition,data for the population flow were used to analyze the relationships between cities and to verify centrality.The results showed that:(1)The pattern of centrality conforms closely to the pole-axis theory and the central geography theory.Two axes,corresponding to the Yangtze River and the Shanghai-Kunming railway line,interconnect cities of different classes.On the whole,the downstream cities have higher centrality,well-defined gradients and better development of city infrastructure compared with cities in the middle and upper reaches.(2)The economic scale and size of the population play a fundamental role in the centrality of cities,and other factors reflect differences due to different city classes.For most of the coastal cities or the capital cities in the central and western regions,factors that require long-term development such as industrial facilities,consumption,research and education provide the main competitive advantages.For cities that are lagging behind in development,transportation facilities,construction of infrastructure and fixed asset investment have become the main methods to achieve development and enhance competitiveness.(3)The mobility of city populations has a significant correlation with the centrality score,the correlation coefficients for the relationships between population mobility and centrality are all greater than 0.86(P<0.01).The population flow is mainly between high-class cities,or high-class and low-class cities,reflecting the high centrality and huge radiating effects of high-class cities.Furthermore,the cities in the YREB are closely linked to Guangdong and Beijing,reflecting the dominant economic status of Guangdong with its geographical proximity to the YREB and Beijing's enormous influence as the national political and cultural center,respectively.     

Spatiotemporal analysis of COVID-19 risk in Guangdong Province based on population migration

Journal of Geographical Sciences - Population migration, especially population inflow from epidemic areas, is a key source of the risk related to the coronavirus disease 2019 (COVID-19) epidemic....