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Annals of Data Science

Separation Axioms on Spatial Topological Space and Spatial Data Analysis

  • 07-05-2022
Published in:
Authors
Rakhal Das
Binod Chandra Tripathy
Published in
Annals of Data Science | Issue 2/2024

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Abstract

The article delves into the use of separation axioms in spatial topological spaces and their application in spatial data analysis, particularly within the context of GIS data. It introduces the fundamental concepts of spatial data representation and analysis, emphasizing the importance of topological properties such as connectivity and adjacency. The study explores how these properties can be utilized to tackle complex real-world problems, such as crime analysis, health issues, and economic challenges. By applying topological separation axioms, the article demonstrates how spatial data can be effectively analyzed and separated, providing valuable insights into spatial relationships and interactions. The research also includes a case study on the road network of Agartala City, highlighting the practical applications of spatial data analysis in urban planning and infrastructure development. The article concludes by emphasizing the potential of spatial topology in solving various social problems and enhancing decision-making processes.
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next article Problem of Compromise Allocation in Multivariate Stratified Sampling Using Intuitionistic Fuzzy Programming
Title
Separation Axioms on Spatial Topological Space and Spatial Data Analysis
Authors
Rakhal Das
Binod Chandra Tripathy
Publication date
07-05-2022
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 2/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-022-00393-w
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