Classification Method of Population Density Map Based on Lorenz Curve

2010 ◽  
Vol 11 (6) ◽  
pp. 833-838 ◽  
Author(s):  
Jiafu HAN ◽  
Hongsheng LI ◽  
Zhong ZHANG
Keyword(s):  
Population Density ◽  
Lorenz Curve ◽  
Classification Method ◽  
Density Map

scholarly journals Mapping current and future European public water withdrawals and consumption

2014 ◽  
Vol 18 (2) ◽  
pp. 407-416 ◽  
Author(s):  
I. Vandecasteele ◽  
A. Bianchi ◽  
F. Batista e Silva ◽  
C. Lavalle ◽  
O. Batelaan
Keyword(s):  
Population Density ◽  
Temporal Trends ◽  
Absolute Error ◽  
Reference Scenario ◽  
Total Water ◽  
Country Level ◽  
European Public ◽  
Density Map ◽  
Per Capita ◽  
Water Withdrawals

Abstract. In Europe, public water withdrawals make up on average 30% and in some cases up to 60% of total water withdrawals. These withdrawals are becoming increasingly important with growing population density; hence there is a need to understand the spatial and temporal trends involved. Pan-European public/municipal water withdrawals and consumption were mapped for 2006 and forecasted for 2030. Population and tourism density were assumed to be the main driving factors for withdrawals. Country-level statistics on public water withdrawals were disaggregated to a combined population and tourism density map (the "user" density map) computed for 2006. The methodology was validated using actual regional withdrawal statistics from France for 2006. The total absolute error (TAE) calculated was proven to be reduced by taking into account the tourism density in addition to the population density. In order to forecast the map to 2030 we considered a reference scenario where per capita withdrawals were kept constant in time. Although there are large variations from region to region, this resulted in a European average increase of water withdrawals of 16%. If we extrapolate the average reduction in per capita withdrawals seen between 2000 and 2008, we forecast a reduction in average total water withdrawals of 4%. Considering a scenario where all countries converge to an optimal water use efficiency, we see an average decrease of 28%.

GIS Based Spatialization of Population Data in Meijiang River Basin

2013 ◽  
Vol 295-298 ◽  
pp. 2378-2383 ◽  
Author(s):  
Xiang Gui Zeng ◽  
Ge Ying Lai ◽  
Fa Zhao Yi ◽  
Ling Ling Zhang
Keyword(s):  
Land Use ◽  
Population Density ◽  
River Basin ◽  
Population Distribution ◽  
Population Data ◽  
Fusion Technology ◽  
Processing Technologies ◽  
Source Data ◽  
Density Map ◽  
Main Factors

This paper used GIS spatial analysis and data processing technologies and multi-source data fusion technology to spatialize the population data of Meijiang river basin. Land use was selected as the index factor and the settlements as the indicative factor. Selected terrain, roads and rivers were the main influencing factors and were further classified into several sub-factors. During the simulation, we first calculated the weight indexes of sub-factors on the settlements distribution and then fused the indexes to calculate the weight indexes of the main factors. Second we calculated the weight indexes of settlements on the population distribution. Last we fused the weight indexes of the main factors and the weight indexes of settlements to obtain the population density indexes of whole region and then generated the 100m×100m resolution raster population density map.

A Population Density Map of European Russia

1926 ◽  
Vol 16 (2) ◽  
pp. 341 ◽  
Author(s):  
Sten de Geer ◽  
Benjamin Semenov-Tian-Shansky
Keyword(s):  
Population Density ◽  
European Russia ◽  
Density Map

scholarly journals Improvement of a Dasymetric Method for Implementing Sustainable Development Goal 11 Indicators at an Intra-Urban Scale

2021 ◽  
Vol 13 (14) ◽  
pp. 2835
Author(s):  
Mariella Aquilino ◽  
Maria Adamo ◽  
Palma Blonda ◽  
Angela Barbanente ◽  
Cristina Tarantino
Keyword(s):  
Sustainable Development ◽  
Population Density ◽  
Absolute Error ◽  
Specific Weight ◽  
Sustainable Development Goal ◽  
Development Goal ◽  
Density Map ◽  
The Mean ◽  
Regional Authorities ◽  
Basic Input

Local and Regional Authorities require indicators at the intra-urban scale to design adequate policies to foster the achievement of the objectives of Sustainable Development Goal (SDG) 11. Updated high-resolution population density and settlement maps are the basic input products for such indicators and their sub-indicators. When provided at the intra-urban scale, these essential variables can facilitate the extraction of population flows, including both local and regular migrant components. This paper discusses a modification of the dasymetric method implemented in our previous work, aimed at improving the population density estimation. The novelties of our paper include the introduction of building height information and site-specific weight values for population density correction. Based on the proposed improvements, selected indicators/sub-indicators of four SDG 11 targets were updated or newly implemented. The output density map error values are provided in terms of the mean absolute error, root mean square error and mean absolute percentage indicators. The values obtained (i.e., 2.3 and 4.1 people, and 8.6%, respectively) were lower than those of the previous dasymetric method. The findings suggest that the new methodology can provide updated information about population fluxes and processes occurring over the period 2011–2020 in the study site—Bari city in southern Italy.

scholarly journals Mapping current and future European public water withdrawals and consumption

2013 ◽  
Vol 10 (7) ◽  
pp. 9889-9914 ◽  
Author(s):  
I. Vandecasteele ◽  
A. Bianchi ◽  
F. Batista e Silva ◽  
C. Lavalle ◽  
O. Batelaan
Keyword(s):  
Population Density ◽  
Temporal Trends ◽  
Absolute Error ◽  
Maximal Increase ◽  
Country Level ◽  
European Public ◽  
Level Statistics ◽  
Density Map ◽  
Water Withdrawals ◽  
Spatial And Temporal Trends

Abstract. In Europe, public water withdrawals make up on average 30%, and in some cases up to 60% of total water withdrawals. These withdrawals are becoming increasingly important with growing population density; hence there is a need to understand the spatial and temporal trends involved. Pan-European public/municipal water withdrawals and consumption were mapped for 2006 and forecasted for 2030. Population and tourism density were assumed to be the main driving factors for withdrawals. Country-level statistics on public water withdrawals were disaggregated to a combined population and tourism density map (the "user" density map) computed for 2006. In order to forecast the map to 2030 we assumed the water withdrawals per user to remain constant in time, so that the future withdrawals reflected the projected population and tourism trends. The methodology was validated using actual regional withdrawal statistics from France for 2006. The Total Absolute Error (TAE) calculated was proven to be reduced by taking into account the tourism density in addition to the population density. Our results show that although there are large variations from region to region, in general public water withdrawals will increase significantly over the period 2006 to 2030. The European average increase is 16%, with a maximal increase of 53% in Ireland.

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