Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/65543
Title: VP-Hotspot: Tool for visualising and predicting hotspot occurrences
Authors: Sunsika Chaikul
Santi Phithakkitnukoon
Authors: Sunsika Chaikul
Santi Phithakkitnukoon
Keywords: Computer Science;Engineering
Issue Date: 1-Jan-2019
Abstract: Copyright © 2019 Inderscience Enterprises Ltd. 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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85063901583&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/65543
ISSN: 09528091
Appears in Collections:CMUL: Journal Articles

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