Next Article in Journal
Three-Axis Ground Reaction Force Distribution during Straight Walking
Next Article in Special Issue
Multipass Target Search in Natural Environments
Previous Article in Journal
A Search-and-Rescue Robot System for Remotely Sensing the Underground Coal Mine Environment
Previous Article in Special Issue
Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(10), 2413; doi:10.3390/s17102413

Assessing Lightning and Wildfire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining in Alberta, Canada

Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N1N4, Canada
*
Author to whom correspondence should be addressed.
Received: 19 September 2017 / Revised: 14 October 2017 / Accepted: 15 October 2017 / Published: 23 October 2017
(This article belongs to the Special Issue Remote Sensing and GIS for Geo-Hazards and Disasters)
View Full-Text   |   Download PDF [13782 KB, uploaded 24 October 2017]   |  

Abstract

Hotspot analysis was implemented to find regions in the province of Alberta (Canada) with high frequency Cloud to Ground (CG) lightning strikes clustered together. Generally, hotspot regions are located in the central, central east, and south central regions of the study region. About 94% of annual lightning occurred during warm months (June to August) and the daily lightning frequency was influenced by the diurnal heating cycle. The association rule mining technique was used to investigate frequent CG lightning patterns, which were verified by similarity measurement to check the patterns’ consistency. The similarity coefficient values indicated that there were high correlations throughout the entire study period. Most wildfires (about 93%) in Alberta occurred in forests, wetland forests, and wetland shrub areas. It was also found that lightning and wildfires occur in two distinct areas: frequent wildfire regions with a high frequency of lightning, and frequent wild-fire regions with a low frequency of lightning. Further, the preference index (PI) revealed locations where the wildfires occurred more frequently than in other class regions. The wildfire hazard area was estimated with the CG lightning hazard map and specific land use types. View Full-Text
Keywords: association rule mining; cloud to ground (CG) lightning; hotspot analysis; wildfire hazard in Alberta association rule mining; cloud to ground (CG) lightning; hotspot analysis; wildfire hazard in Alberta
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Cha, D.; Wang, X.; Kim, J.W. Assessing Lightning and Wildfire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining in Alberta, Canada. Sensors 2017, 17, 2413.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top