A new data mining framework for forest fire mapping

Xi C. Chen, Anuj Karpatne, Yashu Chamber, Varun Mithal, Michael Lau, Karsten Steinhaeuser, Shyam Boriah, Michael S Steinbach, Vipin Kumar, Christopher S. Potter, Steven A. Klooster, Teji Abraham, J. D. Stanley, Juan Carlos Castilla-Rubio

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Forests are an important natural resource that support economic activity and play a significant role in regulating the climate and the carbon cycle, yet forest ecosystems are increasingly threatened by fires caused by a range of natural and anthropogenic factors. Mapping these fires, which can range in size from less than an acre to hundreds of thousands of acres, is an important task for supporting climate and carbon cycle studies as well as informing forest management. Currently, there are two primary approaches to fire mapping: field- and aerial-based surveys, which are costly and limited in their extent; and remote sensing-based approaches, which are more cost-effective but pose several interesting methodological and algorithmic challenges. In this paper, we introduce a new framework for mapping forest fires based on satellite observations. Specifically, we develop unsupervised spatio-temporal data mining methods for Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate a history of forest fires. A systematic comparison with alternate approaches in two diverse geographic regions demonstrates that our algorithmic paradigm is able to overcome some of the limitations in both data and methods employed by prior efforts.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 Conference on Intelligent Data Understanding, CIDU 2012
Pages104-111
Number of pages8
DOIs
StatePublished - Dec 1 2012
Event2012 Conference on Intelligent Data Understanding, CIDU 2012 - Boulder, CO, United States
Duration: Oct 24 2012Oct 26 2012

Publication series

NameProceedings - 2012 Conference on Intelligent Data Understanding, CIDU 2012

Other

Other2012 Conference on Intelligent Data Understanding, CIDU 2012
Country/TerritoryUnited States
CityBoulder, CO
Period10/24/1210/26/12

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