Andrei B. Utkin

Feasibility of forest-fire smoke detection using lidar

The feasibility and fundamentals of forest fire detection by smoke sensing with single-wavelength lidar are discussed with reference to results of 532-nm lidar measurements of smoke plumes from experimental forest fires in Portugal within the scope of the Gestosa 2001 project. The investigations included tracing smoke-plume evolution, estimating forest-fire alarm promptness, and smoke-plume location by azimuth rastering of the lidar optical axis. The possibility of locating a smoke plume whose source is out of line of sight and detection under extremely unfavourable visibility conditions was also demonstrated. The eye hazard problem is addressed and three possibilities of providing eye-safety conditions without loss of lidar sensitivity (namely, using a low energy-per-pulse and high repetition-rate laser, an expanded laser beam, or eye-safe radiation) are discussed.

Design of committee machines for classification of single-wavelength lidar signals applied to early forest fire detection

The application of committee machines composed of single-layer perceptrons for the automatic classification of lidar signals for early forest fire detection is analysed. The patterns used for classification are composed of normalised lidar curve segments, pre-processed in order to reduce noise. In contrast to the approach used in previous work, these patterns contain application-specific parameters, such as peak-to-noise ratio (PNR), average amplitude ratio (AvAR) and maximum amplitude ratio (MAR), in order to improve classification efficiency. Using this method a smoke signature detection efficiency of 93% and a false alarm percentage of 0.041% were achieved for small bonfires, using an optimised committee machine composed of four single-layer perceptrons. The same committee machine was able to detect 70% of the smoke signatures in lidar return signals from large-scale fires in an early stage of development. The possibility of using a second committee machine for detecting fully developed large-scale fires is discussed.

Eye-safe lidar measurements for detection and investigation of forest-fire smoke

The problem of eye safety in lidar-assisted wildland fire detection and investigation is considered as a problem of reduction of the hazard range within which the laser beam is dangerous for direct eye exposure. The dependence of this hazard range on the lidar characteristics is examined and possible eye-safety measures discussed. The potential of one of the cheapest ways of providing eye safety, which is based on placing the lidar in an elevated position and using a 1064-nm laser beam with increased divergence, is also investigated experimentally. It is demonstrated that a lidar system operating with wider beams maintains its ability to detect smoke plumes efficiently. Providing eye-safe conditions allows scanning of the internal 3D structure of smoke plumes in the vicinity of fire plots. Examples are given as layer-by-layer smoke concentration plots on the topographic map.

Water stress assessment of cork oak leaves and maritime pine needles based on LIF spectra

The aim of the present work was to develop a method for the remote assessment of the impact of fire and drought stress on Mediterranean forest species such as the cork oak (Quercus suber) and maritime pine (Pinus pinaster). The proposed method is based on laser induced fluorescence (LIF): chlorophyll fluorescence is remotely excited by frequency-doubled YAG:Nd laser radiation pulses and collected and analyzed using a telescope and a gated high sensitivity spectrometer. The plant health criterion used is based on the I685/I740 ratio value, calculated from the fluorescence spectra. The method was benchmarked by comparing the results achieved with those obtained by conventional, continuous excitation fluorometric method and water loss gravimetric measurements. The results obtained with both methods show a strong correlation between them and with the weight-loss measurements, showing that the proposed method is suitable for fire and drought impact assessment on these two species.

Simple eye-safe lidar for cloud height measurement and small forest fire detection

A simple and robust eye-safe lidar was developed on the basis of a rangefinder optical scheme comprising an Er:glass laser which generates 8 mJ pulses of 1540-nm radiation with the pulse repetition rate of 0.17 Hz and a 38-mm-diameter telescope. Reliable measurements of the cloud height up to 3700 m and early forest-fire detection with a range of 3000 m were experimentally demonstrated. Theoretical estimations indicate that using an optical scheme built around a 10 Hz Er:glass lasers and 150 mm light gathering optics early forest fire detection in a range up to 6500 m can be achieved.

Low-cost active optical system for fire surveillance

Detection of smoke plumes using active optical sensors provides many advantages with respect to passive methods of fire surveillance. However, the price of these sensors is often too high as compared to passive fire detection instruments, such as infrared and video cameras. This article describes robust and cost effective diode-laser optical sensor for automatic fire surveillance in industrial environment. Physical aspects of the sensing process allowing to simplify the hardware and software design, eventually leading to significant reduction of manufacturing and maintenance costs, are discussed.

Neural Network Based Recognition of Smoke Signatures from Lidar Signals

The automatic recognition of smoke signatures in lidar signals collected during very small-scale experimental forest fires using neural-network algorithms was studied. An algorithm for pre-processing of raw lidar signals is proposed, which selects suspicious backscattering peaks and makes them unbiased and scale independent. The resulting patterns can be successfully classified as corresponding to alarm or no-alarm conditions by a neural-network algorithm based on a simple one-neuron structure (perceptron). In the case of an alarm, the pre-processing algorithm provides the location of the smoke plume. Five algorithms selected from the literature, and one that was specially developed, all with learning rate adaptation, were used for training the perceptron. Their efficiencies and statistical properties were compared. The best perceptron classifier presented an efficiency of 97% in the classification of smoke-signature patterns and a false alarm rate of 0.9%.

Electromagnetic waves generated by line exponentially decaying current pulses

Electromagnetic pulses emanated by exponentially decaying currents propagating along a finite line segment with subluminal and luminal velocities are considered. Corresponding electromagnetic problem for the decaying unit-step current is solved by incomplete separation of variables and the basic solution is obtained for the magnetic field strength. This solution is a sum of an analytical expression and a quadrature term, the latter admitting good analytical approximation in the far zone (r/lgsim10), where the entire electromagnetic field can be assessed. Eventually, the results of this work represent feasible analytical expressions for the electromagnetic-pulse durations and maximum amplitude for different configurations of the source, including such practical models as a bipolar current and a current pulse partially reflected from the radiator end

Evaluation of oil spills by laser induced fluorescence spectra

A low cost modular system for automatic oil spill detection, based on laser induced fluorescence light detection and ranging (LIF LIDAR) technology, which may be installed aboard watercraft and used for intensive surveillance of harborages, rivers, channels, and coastal waters, is described. First experimental results obtained with the developed LIF LIDAR detector prototype in the laboratory conditions are reported.

Comparison of eye-safe UV and IR lidar for small forest-fire detection

Lidar is a promising tool for forest-fire monitoring because this active detection technique allows efficient location of tenuous smoke plumes resulting from forest fires at their early stages. For the technique to be generally usable instrumentation must be eye-safe, i.e. it must operate within the spectral range λ<0.4 or λ>1.4 micrometers . In this paper the lidar efficiency at the wavelengths 0.3472 micrometers (second harmonic of the ruby laser) and 1.54 micrometers (Er:glass laser) are compared using a theoretical model. The results of calculations show that the energy required for smoke-plume detection using 0.3472 micrometers becomes greater than the corresponding value for 1.54 micrometers when the distance exceeds some threshold, which ranges between 2 and 6 km depending on other parameters. Being caused by relatively higher absorption of the UV radiation in the atmosphere, this result is valid for any wavelength in the vicinity of 0.35 micrometers , for example, the third harmonic of Nd:YAG laser and the second harmonic of Ti:sapphire laser.