Title: VP-Hotspot: tool for visualising and predicting hotspot occurrences

Authors: Sunsika Chaikul; Santi Phithakkitnukoon

Addresses: Department of Computer Engineering and Excellence Centre in Infrastructure Technology and Transportation Engineering, Faculty of Engineering, Chiang Mai University, Muang District, Chiang Mai, Thailand ' Department of Computer Engineering and Excellence Centre in Infrastructure Technology and Transportation Engineering, Faculty of Engineering, Chiang Mai University, Muang District, Chiang Mai, Thailand

Abstract: Hotspot data can be used to identify a heat source, which can represent vegetation fires, such as forest, grass, cropland, or logging debris. This article presents a development of a tool namely VP-Hotspot, which is a visualisation tool that allows the user to observe and analyse hotspot occurrence patterns of any selected geographical areas. The tool provides two modes of operation: regression and similarity search. Regression mode provides fitted regression models to the selected area data as well as its forecast. Similarity search mode allows the user to search for areas with similar hotspot occurrence patterns. Two case studies are discussed to demonstrate the use of the tool. A user experience study was conducted to evaluate the tool with the real users (130 subjects) from which the tool is highly received for its usefulness and being easy to start using. We believe that the tool is useful for analysing hotspot data, and beneficial to regional and city planning - and more specifically, agricultural planning and fire control, for instance.

Keywords: urban informatics; big data; hotspot; visualisation tool; vegetation fire; wildfire.

DOI: 10.1504/IJCAT.2019.098600

International Journal of Computer Applications in Technology, 2019 Vol.59 No.3, pp.252 - 268

Available online: 22 Mar 2019 *

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