Spatial Morphology Evolution Characteristics Analysis of the Resident Population Distribution in Henan, China

The population spatial distribution pattern and its evolving pattern play an important role in regional allocation of social resources and production factors, formulation of regional development plans, construction of a better life society, and promotion of regional economic development. Based on the resident population statistics data of Henan province from 2006 to 2021, with county as the basic study unit, the paper studies the spatial morphology characteristics and its evolution patterns of resident population distribution, by using spatial analysis methods such as population distribution center, standard deviation ellipse, and spatial auto correlation analysis. The results show that: the resident population spatial distribution shows unbalanced state, the population agglomeration areas mainly distribute in the northeast part and north part, where the resident population growth rate is significantly higher than other regions, over time, this trend is gradually becoming significant. The resident population distribution has a trend of centripetal concentration, with the degree and trend of centripetal gradually strengthening. The resident population distribution has obvious directional characteristics, but the significance is not high, the weighted resident population average center is approximately located at (4.13740˚N, 113.8935˚E), and the azimuth of the distribution axis is approximately 11.19˚. The population distribution has obvious agglomeration characteristics, with the built-up areas of Zhengzhou and Luoyang as their centers, where have a significant siphon effect on the surrounding population. The southern and southwestern regions in the province form a relatively stable belt area of Low-Low agglomeration areas.

Population and housing grid spatialization in Yunnan Province based on grid sampling and application of rapid earthquake loss assessment:the Jinggu Ms6. 6 earthquake

Population and housing grid data spatialization hased on 340 grid samples （ 1 kmx 1 kin） is used in- stead of regional statistical data to simulate the population and housing distribution data of Yunnan Province （ 1 km×1 kin） for rapid loss assessment ibr the Jinggu Ms6.6 earthquake. The resuhs indicate that the method reflects the actual population and housing distribution and that the assessment results are eredihle. The method can be used to quickly provide spatial orientation disaster information after an earthquake.

Spatial Agglomeration and Diffusion of Population Based on a Regional Density Function Approach:A Case Study of Shandong Province in China

Population density functions have long been used to describe the spatial structure of regional population distributions.Several studies have been conducted to examine the population distribution in Shandong Province,China,but few have applied regional density functions to the analysis.Therefore,based on the 2000,2010,and 2020 population censuses,this study used monocentric and polycentric regional density functions to study the characteristics of population agglomeration and diffusion in Shandong.This is followed by an in-depth discussion based on population growth rate data and hot-and cold-spot analyses.The results showed that the Shandong Province population was spatially unevenly distributed.Population growth rates were higher in urban centers and counties,with more significant changes in population size in the eastern coastal areas than in the inland areas.As verified in this study,the logarithmic form of the single-center regional density function R2 was greater than 0.8,which was in line with the population spatial structure of Shandong Province.During the study period,the estimated population density of the regional center and the absolute value of the regional population density gradient both increased,indicating a clear and increasing trend of centripetal agglomeration of regional centers over the study period.Overall,the R2 value of the multicenter region density function was higher than that of the single-center region density function.The polycentric regional density function showed that the population density gradient of some centers had a downward trend,which reflected the spatial development trend of outward diffusion in these centers.Meanwhile,the variation in the estimated population density and the population density gradient exhibited differences in the central population distribution patterns at different levels.

Population Spatial Distribution Based on Luojia 1-01 Nighttime Light Image:A Case Study of Beijing

With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.

Spatiotemporal dynamics of population density in China using nighttime light and geographic weighted regression method

The distribution and dynamic changes of regional or national population data with long time series are very important for regional planning,resource allocation,government decision-making,disaster assessment,ecological protection,and other sustainability research.However,the existing population datasets such as LandScan and WorldPop all provide data from 2000 with limited time series,while GHS-POP only utilizes land use data with limited accuracy.In view of the limited remote sensing images of long time series,it is necessary to combine existing multi-source remote sensing data for population spatialization research.In this research,we developed a nighttime light desaturation index(NTLDI).Through the cross-sensor calibration model based on an autoencoder convolutional neural network,the NTLDl was calibrated with the same period Visible Infrared Imaging Radiometer Suite Day/Night Band(VIRS-DNB)data.Then,the geographically weighted regression method is used to determine the population density of China from 1990 to 2020 based on the long time series NTL.Furthermore,the change characteristics and the driving factors of China's population spatial distribution are analyzed.The large-scale,long-term population spatialization results obtained in this study are of great significance in government planning and decision-making,disaster assessment,resource allocation,and other aspects.

The spatial properties of atomic Raman-Nath diffraction

This paper obtains the exact analytical solution of atomic Raman-Nath diffraction in the coordinate representation and discusses the influence of different initial conditions and detunings on the atomic spatial population distribution. The phase difference between the dipole matrix element and initial atomic population may influence the atomic spatial population distribution after diffraction, which has never been discussed before as far as we know. It offers a method to measure the phase by the spatial population distribution, which is interesting in the study of quantum optics.

A Spatial Supply-Demand Imbalance Between Rural Primary and Secondary Schools in Shaanxi Province Based on Road Network Analysis

It is of great significance to optimize the spatial matching of basic education facilities in rural areas and promote the equalization of urban and rural basic public services and the overall revitalization of rural areas.Based on the theory of spatial accessibility and spatial balance of supply and demand,this paper constructs the evaluation system of rural basic education facilities and layout rationality.In this study,we took 42 primary and secondary schools and 2089 rural areas with concentrated population in six township areas of Hancheng City as the research subjects.We used ArcGIS network analysis,population coupling model,and other methods,from the administrative scale and rural population concentration area scale for evaluation.The accessibility of basic education facilities and its coupling relationship with the spatial distribution of student population describe the spatial and geographical pattern of basic education facilities in rural areas.The results show that the accessibility of rural administrative scale and the spatial balance of supply and demand of population concentration area scale are associated with great problems,the differences between towns are obvious,and the overall level of the best performing towns is still low.On the scale of population concentration area,the overall coupling degree is too low,the"dislocation"distribution of educational facilities and student population is obvious,and the matching degree of the student population and school in different towns is significantly different,showing a more obvious"core-periphery"spatial structure characteristics centered on the eastern and southeast regions.The terrain characteristics of rural areas in Shaanxi province are prominent,and the accessibility of the road network is particularly significant.Therefore,optimizing the construction of rural roads and optimizing school layout according to local conditions will become an important solution to promote the balanced allocation of basic education resources in Shaanxi province.

Exploring the differential impacts of urban transit system on the spatial distribution of local and floating population in Beijing

The floating population has become the main driver of urban population excessive growth in China＇s mega cities. Urban transit system （UTS） is a significant factor in population spatial distributions within urban areas, especially rapid and high-capacity transit systems. This paper analyzes the causal effects of the extension of expressways and subways between 2000 and 2010 in the Beijing Metropolitan Area （BMA）, focusing on the group differences between the local residents and the floating population. Due to the endogeneity of transportation improvements and population growth, Instrumental Variable （IV） regression model is applied to avoid this problem. The results show the local residents increased in the inner suburbs but decreased in the city center, while the floating population increased in the majority areas. IV regression results show that the extension of urban transit systems had statistically significant impacts on population growth across the BMA, The results also show that the extension of urban subway system had more effects on the floating population than the local residents across the BMA. It is mainly caused by the rather low fare of urban subway system. This implies that the excessive subsidy on urban subway system could result in ex- cessive floating population growth and residential differentiation, even residential segregation Hence, it is necessary to plan and design reasonable and scientific urban transit systems in order to advance reasonable population size and promote residential integration. Moreover, the regional analysis shows that the effects of urban transportation improvements on the local residents are not statistically significant in the inner suburbs. It implies that urban transportation improvements had limited effects on inducing people to move to suburban areas and controlling center city＇s population in Beijing. Therefore, it should be stressed the differenti- ated effects of urban transportation improvements on population distribution in the process of urban planning and population control.

The change in population density from 2000 to 2010 and its influencing factors in China at the county scale

Studying the change in population distribution and density can provide important basis for regional development and planning. The spatial patterns and driving factors of the change in population density in China were not clear yet. Therefore, using the population census data in 2000 and 2010, this study firstly analyzed the change of population density in China and divided the change in all 2353 counties into 4 types, consisting of rapid increase, slow increase, slow decrease and rapid decrease. Subsequently, based on the partial least square （PLS） regression method, we recognized the significant factors （among 11 natural and social-economic factors） impacting population density change for the whole country and counties with different types of population change. The results showed that： （1） compared to the population density in 2000, in 2010, the population density in most of the counties （over 60%） increased by 21 persons per km2 on average, while the population density in other counties decreased by 13 persons per km2. Of all the 2353 counties, 860 and 589 counties respectively showed rapid and slow increase in population density, while 458 and 446 coun- ties showed slow and rapid decrease in population density, respectively. （2） Among the 11 factors, social-economic factors impacted population density change more significantly than natural factors. The higher economic development level, better medical condition and stronger communication capability were the main pull factors of population increase. The dense population density was the main push factor of population decrease. These conclusions clarified the spatial pattern of population change and its influencing factors in China over the past 10 years and could provide helpful reference for the future population planning.