scholarly journals Spatial Distribution Patterns of the Elderly Ratio and Their Association with the Density of the Elderly Population

2012 ◽  
Vol 85 (6) ◽  
pp. 608-617
Author(s):  
MORITA Masatoshi ◽  
OKUNUKI Kei-ichi ◽  
SHIODE Shino
Keyword(s):  
Spatial Distribution ◽  
Elderly Population ◽  
Distribution Patterns ◽  
The Elderly ◽  
Spatial Distribution Patterns

scholarly journals A Data-Driven Framework for Analyzing Spatial Distribution of the Elderly Cardholders by Using Smart Card Data

2021 ◽  
Vol 10 (11) ◽  
pp. 728
Author(s):  
Zhicheng Shi ◽  
Xintao Liu ◽  
Jianhui Lai ◽  
Chengzhuo Tong ◽  
Anshu Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Smart Card ◽  
Population Aging ◽  
Distribution Patterns ◽  
The Elderly ◽  
Spatial Distribution Patterns ◽  
Public Facilities ◽  
Home Location ◽  
Smart Card Data ◽  
Rule Based Approach

In this era of population aging, it is essential to understand the spatial distribution patterns of the elderly. Based on the smart card data of the elderly, this study aims to detect the home location and examine the spatial distribution patterns of the elderly cardholders in Beijing. A framework is proposed that includes three methods. First, a rule-based approach is proposed to identify the home location of the elderly cardholders based on individual travel pattern. The result has strong correlation with the real elderly population. Second, the clustering method is adopted to group bus stops based on the elderly travel flow. The center points of clusters are utilized to construct a Voronoi diagram. Third, a quasi-gravity model is proposed to reveal the elderly mobility between regions, using the public facilities index. The model measures the elderly travel number between regions, according to public facilities index on the basis of the total number of point of interest (POI) data. Beijing is used as an example to demonstrate the applicability of the proposed methods, and the methods can be widely used for urban planning, design and management regarding the aging population.

scholarly journals Energy–water and seasonal variations in climate underlie the spatial distribution patterns of gymnosperm species richness in China

2020 ◽  
Vol 10 (17) ◽  
pp. 9474-9485
Author(s):  
Bikram Pandey ◽  
Janak R. Khatiwada ◽  
Lin Zhang ◽  
Kaiwen Pan ◽  
Mohammed A. Dakhil ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Species Richness ◽  
Seasonal Variations ◽  
Distribution Patterns ◽  
Spatial Distribution Patterns
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