Early Forest Fire Detection Using Radio-Acoustic Sounding System

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires.

[1]  Stefan Emeis,et al.  Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements , 2004 .

[2]  Stefan Emeis,et al.  Remote Sensing Methods to Investigate Boundary-layer Structures relevant to Air Pollution in Cities , 2006 .

[3]  Andrei B. Utkin,et al.  Development of neural network committee machines for automatic forest fire detection using lidar , 2004, Pattern Recognit..

[4]  E. Krider,et al.  Lightning Direction-Finding Systems for Forest Fire Detection , 1980 .

[5]  Thomas Pj.  Near-infrared forest fire detection concept , 1993 .

[6]  A. Weintraub,et al.  Forest management challenges for operational researchers , 1998 .

[7]  Ankush Mittal,et al.  An Efficient Contextual Algorithm to Detect Subsurface Fires With NOAA/AVHRR Data , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Dennis W. Thomson,et al.  Acoustic Tomographic Monitoring of the Atmospheric Surface Layer , 1994 .

[9]  Peter Kourtz.  The Need for Improved Forest Fire Detection , 1987 .

[10]  S. Ustin,et al.  Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging , 2007 .

[11]  Joanne Vining,et al.  The Influence of Proximity to a National Forest on Emotions and Fire-Management Decisions , 2008, Environmental management.

[12]  J. San Miguel-Ayanz,et al.  Combining AVHRR and ATSR satellite sensor data for operational boreal forest fire detection , 2003 .

[13]  S. Popescu,et al.  Sensitivity analysis of fire behavior modeling with LIDAR-derived surface fuel maps , 2008 .

[14]  Begoña C. Arrue,et al.  Techniques for reducing false alarms in infrared forest-fire automatic detection systems , 1999 .

[15]  Yrjö Rauste,et al.  Satellite-based forest fire detection for fire control in boreal forests , 1997 .

[16]  Maja Štula,et al.  Forest Fire Protection by Advanced Video Detection System - Croatian Experiences , 2006 .

[17]  Francisco Rego,et al.  Modelling the effects of distance on the probability of fire detection from lookouts , 2006 .

[18]  Feiniu Yuan,et al.  A fast accumulative motion orientation model based on integral image for video smoke detection , 2008, Pattern Recognit. Lett..

[19]  K. Hirsch,et al.  Fire-smart forest management: A pragmatic approach to sustainable forest management in fire-dominated ecosystems , 2001 .

[20]  Andrei B. Utkin,et al.  Optimisation of location and number of lidar apparatuses for early forest fire detection in hilly terrain , 2006 .

[21]  Emilio Chuvieco,et al.  A simple method for Are growth mapping using AVHRR channel 3 data , 1994 .

[22]  Josiane Zerubia,et al.  Forest fire detection by statistical analysis of rare events from thermical infrared images , 2007 .

[23]  Aníbal Ollero,et al.  An Intelligent System for False Alarm Reduction in Infrared Forest-Fire Detection , 2000, IEEE Intell. Syst..

[24]  Turker Ince,et al.  An S-band frequency-modulated continuous-wave boundary layer profiler: Description and initial results , 2003 .

[25]  Rui Vilar,et al.  Multi-objective optimisation of lidar parameters for forest-fire detection on the basis of a genetic algorithm , 2004 .

[26]  Philippe Guillemant,et al.  Real-time identification of smoke images by clustering motions on a fractal curve with a temporal embedding method , 2001 .

[27]  S. Running,et al.  Remote Sensing of Forest Fire Severity and Vegetation Recovery , 1996 .

[28]  Scott D. Peckham,et al.  Fire-induced changes in green-up and leaf maturity of the Canadian boreal forest , 2008 .

[29]  Peter Kourtz,et al.  Decision-Making for Centralized Forest Fire Management , 1984 .

[30]  Martin E. Alexander,et al.  Information systems in support of wildland fire management decision making in Canada , 2002 .

[31]  Aníbal Ollero,et al.  A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires , 2006, J. Field Robotics.

[32]  T. Loboda,et al.  A HYBRID REMOTE SENSING APPROACH TO QUANTIFYING CROP RESIDUE BURNING IN THE UNITED STATES , 2008 .

[33]  P J Thomas,et al.  Near-infrared forest fire detection concept. , 1993, Applied optics.

[34]  Yasar Guneri Sahin,et al.  Animals as Mobile Biological Sensors for Forest Fire Detection , 2007, Sensors.

[35]  R. Landry,et al.  Remote sensing of burn severity: experience from western Canada boreal fires* , 2008 .

[36]  K. Yoshihisa.  Calculation of the Absorption of Sound by the Atmosphere , 1997 .

[37]  I. Galindo,et al.  Real-time AVHRR forest fire detection in Mexico (1998-2000) , 2003 .

[38]  Xavier Descombes,et al.  Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques , 2007 .

[39]  Gary L. Hufford,et al.  Detection and growth of an Alaskan forest fire using GOES-9 3.9 µm imagery , 1999 .

[40]  R. Lasaponara,et al.  Evaluation of a new satellite-based method for forest fire detection , 2001 .

[41]  Warner L. Ecklund,et al.  Fluxes of Heat and Momentum Measured with a Boundary-Layer Wind Profiler Radar-Radio Acoustic Sounding System. , 1993 .

[42]  H. Jahn,et al.  A small satellite solution for the fire detection and monitoring from space , 1996 .

[43]  J. Kudoh,et al.  A new algorithm for forest fire detection method with statistical analysis using NOAA AVHRR images , 2006 .

[44]  Andrei B. Utkin,et al.  Application of lidar in ultraviolet, visible and infrared ranges for early forest fire detection , 2003 .

[45]  A A Barnes,et al.  Combined radar-acoustic sounding system. , 1972, Applied optics.

[46]  Armin Raabe,et al.  Near surface spatially averaged air temperature and wind speed determined by acoustic travel time tomography , 2001 .

[47]  Karolj Skala,et al.  Integrated System For Forest Fire Early Detection and Management , 2008 .

[48]  Li Jing,et al.  Forest fire risk assessment combining remote sensing and meteorological information , 2007 .

[49]  Andrei B. Utkin,et al.  Design of committee machines for classification of single-wavelength lidar signals applied to early forest fire detection , 2005, Pattern Recognit. Lett..

[50]  J. Dupuy,et al.  Thermal infrared emission–transmission measurements in flames from a cylindrical forest fuel burner , 2007 .

[51]  Jack Chambers.  Continuous flow for vermicomposting : Focus on California , 2002 .

[52]  Andrei B. Utkin,et al.  Evaluation of smoke dispersion from forest fire plumes using lidar experiments and modelling , 2006 .

[53]  Gareth Roberts,et al.  Fire Detection and Fire Characterization Over Africa Using Meteosat SEVIRI , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[54]  Yongqiang Liu,et al.  An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States , 2007 .

[55]  I. Sochet,et al.  On the experimental determination of flame front positions and of propagation parameters for a fire , 2008 .

[56]  Krištof Oštir,et al.  Application of satellite remote sensing in natural hazard management: The Mount Mangart landslide case study , 2003 .

[57]  Andrei B. Utkin,et al.  Feasibility of forest-fire smoke detection using lidar , 2003 .

[58]  Armin Raabe,et al.  Observations of area averaged near-surface wind- and temperature-fields in real terrain using acoustic travel time tomography , 2002 .