Exploring geographic hotspots using topological data analysis

Rui Zhang, Jonas Lukasczyk, Feng Wang, David Ebert, Paulo Shakarian, Elizabeth A. Mack, Ross Maciejewski

Research output: Contribution to journalArticlepeer-review

Abstract

This article describes a scalar field topology (SFT)-based methodology for the interactive characterization and analysis of hotspots for density fields defined on a regular grid. In contrast to the common approach of simply identifying hotspots as areas that exceed a chosen density threshold, SFT provides various data abstractions—such as the merge tree and the Morse complex—to characterize hotspots and their boundaries at multiple scales. Moreover, SFT enables the ranking of hotspots based on analyst-defined importance measures, which also makes it possible to explore hotspots using a level-of-detail approach. We present a visual analytics system to support analysts in hotspot analysis and abstraction using SFT, and we demonstrate the merit of the proposed SFT-based methodology on two crime datasets.

Original languageEnglish (US)
Pages (from-to)3188-3209
Number of pages22
JournalTransactions in GIS
Volume25
Issue number6
DOIs
StatePublished - Dec 2021
Externally publishedYes

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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