scholarly journals Multiple Global Population Datasets: Differences and Spatial Distribution Characteristics

2020 ◽  
Vol 9 (11) ◽  
pp. 637
Author(s):  
Ruxia Chen ◽  
Huimin Yan ◽  
Fang Liu ◽  
Wenpeng Du ◽  
Yanzhao Yang
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Spatial Data ◽  
Statistical Data ◽  
Population Distribution ◽  
Application Process ◽  
Tibet Autonomous Region ◽  
Relative Errors ◽  
The Uk ◽  
The Impact

Spatial data of regional populations are indispensable in studying the impact of human activities on resource utilization and the ecological environment. Because the differences between datasets and their spatial distribution are still unclear, this has become a puzzle in data selection and application. This study is based on four mainstream spatialized population datasets: the History Database of the Global Environment version 3.2.000 (HYDE), Gridded Population of the World version 4 (GPWv4), Global Human Settlement Layer (GHSL), and WorldPop. In view of possible influences of geographical factors, this study analyzes the differences in accuracy of population estimation by computing relative errors and population spatial distribution consistency in different regions by comparing datasets pixel by pixel. The results demonstrate the following: (1) Source data, spatialization methods, and case area features affect the precision of datasets. As the main data source is statistical data and the spatialization method maintains the population in the administrative region, the populations of GPWv4 and GHSL are closest to the statistical data value. (2) The application of remote sensing, mobile communication, and other geospatial data makes the datasets more accurate in the United Kingdom, with rich information, and the absolute value of relative errors is less than 4%. In the Tibet Autonomous Region of China, where data are hard to obtain, the four datasets have larger relative errors. However, the area where the four datasets are completely consistent is as high as 84.73% in Tibet, while in the UK it is only 66.76%. (3) The areas where the spatial patterns of the four datasets are completely consistent are mainly distributed in areas with low population density, or with developed urbanization and concentrated population distribution. Areas where the datasets have poor consistency are mainly distributed in medium population density areas with high urbanization levels. Therefore, in such areas, a more careful assessment should be made during the data application process, and more emphasis should be placed on improving data accuracy when using spatialization methods.

scholarly journals Population distribution characteristics and its relationship with natural factors in karst mountainous areas of Northwest Guangxi

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Shana Shi ◽  
Bingkang Xie ◽  
Baoqing Hu ◽  
Chuanyong Tang ◽  
Yan Yan ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Population Distribution ◽  
Basic Unit ◽  
Distribution Characteristics ◽  
Mountainous Areas ◽  
Mountain Area ◽  
Natural Factors ◽  
The Impact ◽  
Population Spatial Distribution

The smallest administrative unit of the sixth national census-township (town) is selected as the basic unit, the population spatial distribution characteristics at the township (town) level in karst mountainous areas of northwest Guangxi are analyzed by using Lorenz curve and spatial correlation analysis method, and the influence intensity of natural factors on regional population spatial distribution is detected by using geographic detector method. The results show that: 1. the spatial distribution of population at the township (town) level has the characteristics of imbalance, showing generally significant positive correlation and certain aggregation; 2. there are significant differences in the impact of the spatial distribution of various natural factors on the population distribution. For the towns without karst distribution in the northwest and central south of the study area, the population density increases with the increase of factors conducive to human residence, but the average population density is only 79 people / km2. In the towns with karst distribution in the East and south, the spatial distribution of population density and natural factors is not a simple increase or decrease relationship, but fluctuates with the change of karst distribution area. 3. The factor detection results of the geographic detector show that the altitude has the greatest impact on the spatial distribution of population. The interactive detection results show that the impact intensity of any two natural factors after superposition and interaction presents nonlinear enhancement and two factor enhancement. It can be seen that the karst mountain area in northwest Guangxi is similar to other areas. Altitude is one of the main factors affecting the spatial distribution of population, but the river network density and unique geological landform of karst mountain area have a strong catalytic effect on the spatial distribution of population. The superposition and interaction with other factors can further strengthen the impact on population distribution.

scholarly journals Simulation of the spatial distribution of urban populations based on first-aid call data

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Yinan Zhou ◽  
Qin Zhong Zhu ◽  
Li Luo
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Cell Size ◽  
Population Distribution ◽  
Grid Cell ◽  
First Aid ◽  
M Cell ◽  
Urban Populations ◽  
Digital Maps ◽  
The Impact

We examined the feasibility of estimating the spatial distribution of urban populations based on first-aid calls based on one high-density place, the Shanghai urban area and one low-density place, the Nanhai District of Foshan City in Guangdong Province. We aggregated the population and the total number of first-aid calls on digital maps divided by grids based on a Geographic Information System (GIS). Geographically weighted regression was applied to test the correlation between the population distribution simulated by first-aid call data and the actual residency. The impact of different population densities, different grid cell sizes and different types of first-aid calls on simulation correlation were tested. We found that the use of first-aid call data could explain 60-95% of the actual population distribution in Shanghai using a grid with 1000*1000 m cell size, while the Nanhai experience was that first-aid calls could only explain 4-76% of the actual population distribution using a grid with 2000*2000 m cell size. Thus, the higher the population density, the better the simulation effect. For a high-population density area, the overall accuracy of simulation can reach as high as 0.878 at the 1-km2 resolution. However, there are different kinds of first-aid calls and for the best estimation of the population distribution in densely populated areas, we suggest using first-aid calls from people requiring acute medical care rather than all first-aid call data.

scholarly journals A Quantitative Evaluation of the Multiple Narratives of the Recent Sahelian Regreening*

2016 ◽  
Vol 8 (1) ◽  
pp. 67-83 ◽  
Author(s):  
Mimi Stith ◽  
Alessandra Giannini ◽  
John del Corral ◽  
Susana Adamo ◽  
Alex de Sherbinin
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Environmental Change ◽  
Burkina Faso ◽  
Social Dimensions ◽  
Adaptation To Climate Change ◽  
Southern Central ◽  
Second Category ◽  
The Impact

Abstract A spatial analysis is presented that aims to synthesize the evidence for climate and social dimensions of the “regreening” of the Sahel. Using an independently constructed archival database of donor-funded interventions in Burkina Faso, Mali, Niger, and Senegal in response to the persistence of drought in the 1970s and 1980s, the spatial distribution of these interventions is examined in relation to population density and to trends in precipitation and in greenness. Three categories of environmental change are classified: 1) regions at the northern grassland/shrubland edge of the Sahel where NDVI varies interannually with precipitation, 2) densely populated cropland regions of the Sahel where significant trends in precipitation and NDVI decouple at interannual time scales, and 3) regions at the southern savanna edge of the Sahel where NDVI variation is independent of precipitation. Examination of the spatial distribution of environmental change, number of development projects, and population density brings to the fore the second category, covering the cropland areas where population density and regreening are higher than average. While few, regions in this category coincide with emerging hotspots of regreening in northern Burkina Faso and southern central Niger known from case study literature. In examining the impact of efforts to rejuvenate the Sahelian environment and livelihoods in the aftermath of the droughts of the 1970s and 1980s against the backdrop of a varying and uncertain climate, the transition from desertification to regreening discourses is framed in the context of adaptation to climate change.

scholarly journals Exploring Ethnicity in Hospital Patients with COVID-19 in South London

The Physician ◽  
2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Anna Zatorska ◽  
Niladri Konar ◽  
Pratyasha Saha ◽  
Alice Moseley ◽  
Jessica Denman ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Population Distribution ◽  
Local Population ◽  
Case Series ◽  
Risk Of Death ◽  
Hospitalised Patients ◽  
Hospital Patients ◽  
The Usa ◽  
The Uk ◽  
The Impact

Ethnicity was found to be an independent risk factor in COVID-19 outcomes in the UK and the USA during the pandemic surge. London, being in the epicentre and having one of the most ethnically diverse population in the UK, was likely to have experienced a much higher intensity of this phenomenon. Black Asian and Minority ethnic groups were more likely to be admitted, more likely to require admission to intensive care, and more likely to die from COVID-19. We undertook an analysis of a case series to explore the impact of ethnicity in hospitalised patients with confirmed COVID-19 during the 3 months of the pandemic. Our results demonstrated that although the proportion of Asian and Black patients were representative of the local population distribution, they were much younger. The prevalence of comorbidities was similar but logistic regression analysis showed that male sex (OR 1.4, 95% CI 1.1-1.9; p=0.02), age (OR 1.03, 95% CI 1.02 - 1.04, p<0.001), those in the ‘Other’ [Odds ratio 1.7 (1.1-2.6) p = 0.01] and ‘Asian’[Odds ratio 1.8 (1.1-2.7) p=0.01], category were at higher risk of death in this cohort. Our results, therefore, are consistent with the overall data from the UK and USA indicating that ethnicity remains a significant additional risk and hence our clinical services must ensure that adequate provision is made to cater to this risk and research must be designed to understand the causes.   

scholarly journals Population Distribution in the Wake of a Sphere

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1498 ◽  
Author(s):  
Taraprasad Bhowmick ◽  
Yong Wang ◽  
Michele Iovieno ◽  
Gholamhossein Bagheri ◽  
Eberhard Bodenschatz
Keyword(s):  
Reynolds Number ◽  
Spatial Distribution ◽  
Population Density ◽  
Density Distribution ◽  
Population Distribution ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Wake Flow ◽  
Sample Number ◽  
Scalar Fluxes

The physics of heat and mass transfer from an object in its wake has significant importance in natural phenomena as well as across many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration, and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). Our findings show that the spatial population distributions of the fluid and the transported scalar quantities in the wake follow a Cauchy-Lorentz or Lorentzian trend, indicating a variation in its sample number density inversely proportional to the squared of its magnitude. We observe this universal form of population distribution both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number. Descriptive statistics in the form of population density distribution of the spatial distribution of the fluid velocity and the transported scalar quantities is important for understanding the transport and local reaction processes in specific regions of the wake, which can be used e.g., for understanding the microphysics of cloud droplets and aerosol interactions, or in the technical flows where droplets interact physically or chemically with the environment.

scholarly journals Mapping Changing Population Distribution on the Qinghai–Tibet Plateau since 2000 with Multi-Temporal Remote Sensing and Point-of-Interest Data

2020 ◽  
Vol 12 (24) ◽  
pp. 4059
Author(s):  
Lanhui Li ◽  
Yili Zhang ◽  
Linshan Liu ◽  
Zhaofeng Wang ◽  
Huamin Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Population Density ◽  
Rural Areas ◽  
Population Distribution ◽  
Local Population ◽  
Tibet Plateau ◽  
Point Of Interest ◽  
Tibet Autonomous Region ◽  
Multi Temporal ◽  
Qinghai Tibet Plateau

Advanced developments have been achieved in urban human population estimation, however, there is still a considerable research gap for the mapping of remote rural populations. In this study, based on demographic data at the town-level, multi-temporal high-resolution remote sensing data, and local population-sensitive point-of-interest (POI) data, we tailored a random forest-based dasymetric approach to map population distribution on the Qinghai–Tibet Plateau (QTP) for 2000, 2010, and 2016 with a spatial resolution of 1000 m. We then analyzed the temporal and spatial change of this distribution. The results showed that the QTP has a sparse population distribution overall; in large areas of the northern QTP, the population density is zero, accounting for about 14% of the total area of the QTP. About half of the QTP showed a rapid increase in population density between 2000 and 2016, mainly located in the eastern and southern parts of Qinghai Province and the central-eastern parts of the Tibet Autonomous Region. Regarding the relative importance of variables in explaining population density, the variables “Distance to Temples” is the most important, followed by “Density of Villages” and “Elevation”. Furthermore, our new products exhibited higher accuracy compared with five recently released gridded population density datasets, namely WorldPop, Gridded Population of the World version 4, and three national gridded population datasets for China. Both the root-mean-square error (RMSE) and mean absolute error (MAE) for our products were about half of those of the compared products except for WorldPop. This study provides a reference for using fine-scale demographic count and local population-sensitive POIs to model changing population distribution in remote rural areas.

scholarly journals Frequency and spatial distribution of animal and object hoarder behavior in Curitiba, Paraná State, Brazil

2017 ◽  
Vol 33 (2) ◽  
Author(s):  
Graziela Ribeiro da Cunha ◽  
Camila Marinelli Martins ◽  
Marília de Fátima Ceccon-Valente ◽  
Liana Ludielli da Silva ◽  
Flavia Dias Martins ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Population Distribution ◽  
Distribution Patterns ◽  
Spatial Cluster ◽  
Monthly Income ◽  
The North ◽  
Neighborhood Income ◽  
Overall Ratio ◽  
The City

Abstract: This study aimed to establish the frequency and spatial distribution of animal and object hoarding in Curitiba (Paraná State), the eighth most populous city in Brazil. All hoarding complaints received by the City Secretaries of Health, Environment and Social Assistance between September 2013 and April 2015 were collected (n = 226) and suspicious cases were individually investigated. A total of 113/226 (50%) of complaints were confirmed as hoarding cases, representing an overall ratio of 6.45 cases per 100,000 inhabitants in Curitiba, of which 48/113 (42.5%) involved object hoarders, 41/113 (36.3%) animal hoarders and 24/113 (21.2%) both animal and object hoarders. A correlation of total identified cases with neighborhood population density and all population stratums analyzed (total, gender, age) was significantly positive (p < 0.01), and with neighborhood mean monthly income (r = -0.2; p = 0.03) significantly negative. A spatial cluster of cases was found in the north of the city (OR = 8.57; p < 0.01). Hoarding cases were relatively frequent in Curitiba and were associated with population distribution patterns and inversely related to neighborhood income.

scholarly journals An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data—A Case Study of the City of Shenzhen

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5032 ◽  
Author(s):  
Qiang Zhou ◽  
Yuanmao Zheng ◽  
Jinyuan Shao ◽  
Yinglun Lin ◽  
Haowei Wang
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Spatial Resolution ◽  
Urban Population ◽  
Road Network ◽  
Population Distribution ◽  
Small Scale ◽  
Human Settlement ◽  
Nighttime Light ◽  
The City

Previously published studies on population distribution were based on the provincial level, while the number of urban-level studies is more limited. In addition, the rough spatial resolution of traditional nighttime light (NTL) data has limited their fine application in current small-scale population distribution research. For the purpose of studying the spatial distribution of populations at the urban scale, we proposed a new index (i.e., the road network adjusted human settlement index, RNAHSI) by integrating Luojia 1-01 (LJ 1-01) NTL data, the enhanced vegetation index (EVI), and road network density (RND) data based on population density relationships to depict the spatial distribution of urban human settlements. The RNAHSI updated the high-resolution NTL data and combined the RND data on the basis of human settlement index (HSI) data to refine the spatial pattern of urban population distribution. The results indicated that the mean relative error (MRE) between the population estimation data based on the RNAHSI and the demographic data was 34.80%, which was lower than that in the HSI and WorldPop dataset. This index is suitable primarily for the study of urban population distribution, as the RNAHSI can clearly highlight human activities in areas with dense urban road networks and can refine the spatial heterogeneity of impervious areas. In addition, we also drew a population density map of the city of Shenzhen with a 100 m spatial resolution for 2018 based on the RNAHSI, which has great reference significance for urban management and urban resource allocation.

scholarly journals The impact of environmental factors on distribution of Scops Owl Otus scops in the wider area of Kras (SW Slovenia)

Acrocephalus ◽  
2011 ◽  
Vol 32 (148-149) ◽  
pp. 11-28 ◽  
Author(s):  
Tina Šušmelj
Keyword(s):  
Environmental Factors ◽  
Spatial Data ◽  
Goodness Of Fit ◽  
Agricultural Land ◽  
Population Distribution ◽  
Spatial Scales ◽  
Regional Scale ◽  
Goodness Of Fit Test ◽  
The Impact ◽  
Sw Slovenia

The impact of environmental factors on distribution of Scops Owl Otus scops in the wider area of Kras (SW Slovenia) The aim of the study was to determine the key environmental factors affecting Scops Owl Otus scops occurrence in the wider Kras plateau area (SW Slovenia, 665 km2). Scops Owl was systematically censused in 2006 (180 calling males) and in 2008 (167 calling males). Males were distributed either solitarily or clumped in groups, mostly situated in villages and its surroundings, indicating the species' synanthropic character. Crude densities were 0.3 males/km2 in 2006 and 2008, respectively, while ecological densities were 1.0 males/km2 in 2006 and 0.9 males/km2 in 2008. Population distribution remained roughly the same in both years, with the highest densities in the western and central parts of the Kras plateau, on Kraški rob and on Podgorski kras plateau. Habitat selection was analyzed at three spatial scales (regional, settlement and territory scales), based on spatial data layers (22 environmental variables), using Chi-square goodness-of-fit test and logistic regression. Results revealed that at the regional scale, Scops Owl preferably selected open habitats (extensively managed orchards, built-up areas, vineyards, permanent grasslands) and avoided dense forest and agricultural land with forest trees. As far as settlements were concerned, Scops Owl was more prone to select those that were more distant from the highway, with better preserved traditional agricultural landscape (with more hedgerows) and with higher average annual air temperature. In territory selection, Scops Owl occurrence was associated with longer distance from the highway, larger number of old buildings and higher landscape mosaics. The species seems to be threatened by traffic noise, habitat loss through abandonment and intensification of land and, potentially, by lack of breeding niches within settlements. Conservation measures should include the preservation of mosaic farmland, promotion of extensive agricultural practices, prevention of scrub and forest expansion, and maintenance of breeding niches (old trees, cavities in buildings).

scholarly journals Analysis of the impact of geographic features, population distribution and power load on heat island effects in the metropolis of Shenzhen

MAUSAM ◽  
2021 ◽  
Vol 65 (4) ◽  
Author(s):  
LI LEI ◽  
ZHANG LIJIE ◽  
ZHANG XIAOLI ◽  
LU CHAO ◽  
ZHANG LI ◽  
...  
Keyword(s):  
Population Density ◽  
Population Distribution ◽  
Dominant Factor ◽  
Strong Impact ◽  
Heat Island ◽  
Coverage Area ◽  
Average Wind Speed ◽  
Power Load ◽  
Yearly Average ◽  
The Impact

Based on the air temperature data collected from automated weather stations, the urban heat island (UHI) intensity in Shenzhen metropolis is calculated and the impact of several factors, including land-sea distribution, population density, road coverage area and power load, on the UHI intensity are analyzed. The analysis shows that the land-sea distribution is the dominant factor for the UHI distribution in Shenzhen, with the climate-adjusting effect of the sea clearly reducing the UHI intensity in the east and west parts of Shenzhen. The middle part of Shenzhen is adjacent to Hong Kong and the climate-adjusting effect of the sea is weak, which leads to UHI intensity being centered around this area. The population density and road coverage area do impact the UHI in Shenzhen, with strong dependency between the UHI intensity and the two factors (p < 0.01). However, in the area with the densest roads, the UHI intensity is not high, which may be related to the high yearly-average wind speed in this area. Comparing the data from 2011 and 2010 shows strong impact of the power load on the UHI intensity in Shenzhen, and the increase of the UHI intensity in 2011 is highly likely to be due to the increase of the power load in the colder winter and the hotter summer of 2011.

Sign in / Sign up

Export Citation Format

Share Document