Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires

Living Edition
| Editors: Samuel L. Manzello

Ground-Based Fire Detection

  • Azarm NowzadEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-51727-8_143-1



Ground-based fire detection is defined as a terrestrial monitoring system for wildland fire detection and prevention.


Manned watchtowers are the most established method for the spotting of wildland fires. They have been employed for centuries and are still in use in many places around the world. There, fire detection is done with the naked eye and requires a vast expenditure of manpower. Observers tend to spot first smoke and only much later, or in case of fires very near to the observation point, flames (in this entry the term “fire” is used to refer to an event in which both flame and smoke may be present).

With the advances in camera technology and in computational power, different remote sensing fire detection technologies have been developed in recent years to assist and replace human observers. Camera-based monitoring systems, commonly installed on watchtowers,...

This is a preview of subscription content, log in to check access.


  1. Allison RS, Johnston JM, Craig G, Jennings S (2016) Airborne optical and thermal remote sensing for wildfire detection and monitoring. J MDPI.  https://doi.org/10.3390/s16081310 CrossRefGoogle Scholar
  2. Arrue BC, Ollero A, Matinez De Dios JR (2000) An intelligent system for false alarm reduction in infrared forest-fire detection. IEEE Int Syst:64–73.  https://doi.org/10.1109/5254.846287 CrossRefGoogle Scholar
  3. Hijazi S, Kumar R, Rowen C (2015) Using convolutional neural networks for image recognition. Technical Report, 2015. Available: http://ip.cadence.com/uploads/901/cnn-wp-pdf.
  4. Nowzad A, Jock A, Krane U, Jaeckel K, Vogel H (2014) Development of an automatic smoke detection algorithm using color images and a fuzzy logic approach for real-time forest fire detection applications. 15th international conference on automatic fire detection proceeding. DuisburgGoogle Scholar
  5. Patel P, Tiwari S (2012) Flame detection using image processing techniques. J Int J Comput Appl 58(18):13–16 CrossRefGoogle Scholar
  6. Qian Y, Yan G, Duan S, Kong X (2009) A contextual fire detection algorithm for simulated HJ-1B imagery. Sensors 9(2):961–979.  https://doi.org/10.3390/s90200961 CrossRefGoogle Scholar
  7. Stula M, Krstinic D, Seric L (2012) Intelligent forest fire monitoring system. Information Systems Frontiers 14(3):725–739. Springer Google Scholar
  8. Utkin AB, Fernandes A, Simões F, Lavrov A, Vilar R (2003) Feasibility of forest-fire smoke detection using lidar. J Wildland Fire 12:159–166.  https://doi.org/10.1071/WF02048 CrossRefGoogle Scholar
  9. Wren CR, Azarbayejani A, Darrell T, Pentland AP (1997) Pfinder: real-time tracking of the human body. J IEEE Pattern Anal Mach Intell 19(7).  https://doi.org/10.1109/34.598236 CrossRefGoogle Scholar
  10. Yoon SH, Min J (2013) An intelligent automatic early detection system of forest fire smoke signatures using Gaussian mixture model. J Info Procee Syst 9:621–632 MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceHumboldt University of BerlinBerlinGermany

Section editors and affiliations

  • Sayaka Suzuki
    • 1
  1. 1.National Research Institute of Fire and DisasterTokyoJapan