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 EFFECTIVENESS OF CLASSIFICATION METHOD AND COLOR SYMBOL SCHEME ON CHOROPLETH MAP OF POPULATION DENSITY IN SPECIAL REGION OF YOGYAKARTA

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 55-61
Author(s):  
Z. N. 'Afifah ◽  
Keyword(s):  
Decision Making ◽  
Population Density ◽  
Test Method ◽  
Classification Method ◽  
Classification Methods ◽  
Color Scheme ◽  
Choropleth Map ◽  
Scientific Fields ◽  
Special Region ◽  
Color Symbol

Abstract. The need for presenting information in maps is increasingly high in various scientific fields. All scientific fields need to present effective data for decision making. Good decision making based on maps requires good understanding but not all scientific fields are familiar with using maps. Supporting factors for easy maps to understand are classification method and color symbol scheme. The purpose of this study was to select and test the classification method and the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The classification methods used in this study are constant interval, arithmetic progression, geometric progression, quantile, standard deviation and dispersal graph. The effectiveness test method for the most effective classification method is the proportion assessment. The color symbol scheme used in this study is a sequential color scheme, diverging color schemes, Corel Draw color schemes and color symbol schemes provided in ArcMap 10.3 software. The effectiveness test method for the most effective color symbol scheme is conventional eye tracking. The results showed that according to the proportion test the most effective classification method was the arithmetic interval classification method with results of 0.26. The most effective color symbol scheme in accordance with the effectiveness test using the conventional eye tracking method shows that the most effective color symbol scheme is a diverging color scheme. The important aspects to consider are average answering duration of 8.15 seconds, the accuracy of the answer is 98.9%, and easiness level of symbolization readings is 341. This research can be one of the references on the most effective classification method and reference regarding the selection of the most effective color symbol scheme on Choropleth Map of Population Density in Special Region of Yogyakarta, so that further research can continue the analysis of appropriate classification methods for demographic data. The method discussed in this study is also expected to be applicable to other data.

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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