Next Article in Journal
Assessing Field Spectroscopy Metadata Quality
Previous Article in Journal
L-Band SAR Backscatter Related to Forest Cover, Height and Aboveground Biomass at Multiple Spatial Scales across Denmark
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(4), 4473-4498; doi:10.3390/rs70404473

Forest Fire Smoke Detection Using Back-Propagation Neural Network Based on MODIS Data

State Key Laboratory of Fire Science, University of Science and Technology of China, Jinzhai 96, Hefei 2300027, China
*
Author to whom correspondence should be addressed.
Academic Editors: Ioannis Gitas and Prasad S. Thenkabail
Received: 14 December 2014 / Revised: 15 March 2015 / Accepted: 15 March 2015 / Published: 15 April 2015
View Full-Text   |   Download PDF [6960 KB, uploaded 15 April 2015]   |  

Abstract

Satellite remote sensing provides global observations of the Earth’s surface and provides useful information for monitoring smoke plumes emitted from forest fires. The aim of this study is to automatically separate smoke plumes from the background by analyzing the MODIS data. An identification algorithm was improved based on the spectral analysis among the smoke, cloud and underlying surface. In order to get satisfactory results, a multi-threshold method is used for extracting training sample sets to train back-propagation neural network (BPNN) classification for merging the smoke detection algorithm. The MODIS data from three forest fires were used to develop the algorithm and get parameter values. These fires occurred in (i) China on 16 October 2004, (ii) Northeast Asia on 29 April 2009 and (iii) Russia on 29 July 2010 in different seasons. Then, the data from four other fires were used to validate the algorithm. Results indicated that the algorithm captured both thick smoke and thin dispersed smoke over land, as well as the mixed pixels of smoke over the ocean. These results could provide valuable information concerning forest fire location, fire spreading and so on. View Full-Text
Keywords: smoke plumes; fire detection; MODIS; multi-threshold; neural network smoke plumes; fire detection; MODIS; multi-threshold; neural network
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

Li, X.; Song, W.; Lian, L.; Wei, X. Forest Fire Smoke Detection Using Back-Propagation Neural Network Based on MODIS Data. Remote Sens. 2015, 7, 4473-4498.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top