Laboratory experimental studies have been carried out on a method for detecting oil pollution on the earth's surface in the near-infrared range. In the spectral range of 900-2500 nm, reflection spectra of samples were obtained after spills on soil and sand of various brands of gasoline, commercial oil and motor oil, as well as kerosene, diesel fuel, gas condensate, engine coolant and vegetable oil. It has been shown that in the spectral range of about 1730 nm, dips appear in the reflection spectra caused by the absorption of hydrocarbons on a surface contaminated with oil products, which are especially pronounced in the case of an oil spill on sand. In the spectral range around 2300 nm, dips in the reflectance spectra are more noticeable in the case of oil spills on soil. Therefore, to increase the efficiency of the method for detecting oil pollution on the earth's surface in the near-infrared range, it is necessary to use measurement data both in the spectral region of about 1730 nm and in the spectral region of about 2300 nm.
The results of the leaves and needles samples reflection spectra measurements on a laboratory installation in the range of 0.4-2.4 μm during the summer-autumn period are presented. It has been shown that there may be cases when the summer (for green leaves) and autumn (for yellow-green leaves) leaves or needles samples reflection spectra differ slightly in the visible range (0.4-0.75 μm), and in the near-infrared range (1.4-2.4 μm) stronger. It has also been noted that the information index R value (which is equal to the ratio of the vegetation reflectivity in the narrow spectral bands near wavelengths of 1.65 and 2.03 μm) is significantly higher for green vegetation samples (in summer period) compared to yellow or began to turn yellow samples (in autumn period).
The work is devoted to the optimal wavelengths selection for the task of methane monitoring using an acousto-optical spectrometer installed on board a satellite. The results of mathematical modeling are given. It is shown that the spectral width of the instrumental function has a significant impact on the selection result, while the atmosphere model used does not have a significant effect.
The paper shows the woody vegetation reflectivity dependence on the storage conditions of the samples. The results of leaves and needles samples spectral reflectivity measurements in the range of 0.4-0.9 μm for several days after cutting the samples from trees when storing samples in a special refrigerator and without a refrigerator were presented. It was shown that woody vegetation samples storage in a special temperature-regulated refrigerator make it possible to ensure the stability of the reflectivity for coniferous trees for two or three days and for most deciduous tree species in a time interval ranging from a few hours to one day.
The purpose of the study is to analyze the possibilities of forest areas hyperspectral monitoring. The mathematical modeling of the forest territories elements classification on the created neural network using experimentally measured reflection coefficients is presented. The simulation results show that hyperspectral monitoring in the spectral range of 400-2400 nm allows for classification of forest elements (different species of deciduous and coniferous trees, deadwood, swamps, water bodies, soils without vegetation, different types of mosses and lichens, post-fire areas, different shrubby plants) with the probability of correct classification of more than 0.73 and the probability of incorrect classification of less than 0.037. The use of additional information from the laser altimeter allows to significantly improve the classification. The created neural network, using hyperspectral monitoring data and lidar data on the height of trees, provides the probabilities of correct forest area elements classification of more than 0.8 and the probabilities of incorrect classification of less than 0.025.
The paper presents a capability analysis of the laser reflection method for remote monitoring of the forestland condition and species composition. A mathematical simulation using the spectral libraries of plant reflection coefficients shows that monitoring of forestland condition and species composition can be based on the laser method. Laser sounding at wavelengths 355, 1540, 2030 nm or 532, 1540, 2030 nm allows us to monitor the forestland condition and species composition with a probability of correct detection close to one and a probability of false alarms ~ second decimal places.
The paper focuses on the experimental study of optical methods of plant stress detection. The results of measurements of the spectral characteristics of fluorescence and reflectance of alfalfa (Medicágo satíva) in the normal and stress conditions are presented. The results of statistical processing of measurement data are given.
The report focuses on the study of a flash lamp using for fluorescence excitation of oil pollution for their detection on the terrestrial surface. Experimental results of fluorescence images registration are presented. The fluorescence image was processed using support vector machine (SVM) and random forest (RF) classifiers. The possibility of oil pollution detection on the terrestrial surface using a flash tube is shown.
The paper deals with the experimental studies of laser-induced fluorescence (LIF) spectra of plants under adverse development conditions at the eye-safe 355 nm wavelength of fluorescence excitation. It has been shown that in the spectral band of 670 - 750 nm a fluorescence spectra shape analysis makes it possible to detect vegetation under adverse development conditions. However, in the spectral band of 375 – 650 nm the resulting data do not give evidence of steady relationship between the fluorescence intensity and the plant conditions.
The paper provides a capability analysis of optical sensors for remote monitoring of vegetation condition in visible (VIS) and near infrared (NIR) bands. Mathematical modelling based on the spectral libraries of vegetation reflection coefficients shows that a hyper-spectral sensor with narrow spectral channels (or a laser sensor) allows us to detect the vegetation under adverse conditions with correct detection probability close to one and false alarm probability ~ second decimal places both in VIS and NIR bands below 1 μm and in the near infrared band above 1.4 μm. Data sharing in various spectral bands enables enhancing measurement reliability.
We have experimentally studied laser-induced fluorescence spectra of plants under man-made soil pollution at the fluorescence excitation wavelength of 355 nm. The paper describes a laboratory setup, presents measurement data of laser-induced fluorescence spectra of plants in the normal condition and under stress caused by man-made soil pollution and shows that the man-made soil pollution has a strong impact on the laser-induced fluorescence spectrum of plants.
We have experimentally studied laser-induced fluorescence spectra of petroleum products at the fluorescence excitation wavelength of 355 nm. The paper depicts a schematic diagram of the laboratory setup and gives data resulted from laserinduced fluorescence spectra processing of oil and petroleum products. A comparative analysis of laser-induced fluorescence spectra of oil and petroleum products has shown that laser-induced fluorescence spectra of oil have a shift toward the longer wavelength spectral region and that their spectral bandwidth is far wider. The paper presents the efficient bands to detect fluorescence emission of oil and petroleum products when exciting at the wavelength of 355 nm.
The paper presents a comparative analysis of efficiency to detect vegetation under adverse conditions using a passive optical method and a laser reflection one at the eye-safe sensing wavelengths. A mathematical simulation based on the spectral library of the reflection coefficients of vegetation shows that the laser reflection method (at two eye-safe wavelengths in the NIR band or in the NIR and UV ones) can be good advantage for vegetation monitoring. Sensing at the eye-safe wavelengths of 1.54 and 2.03 μm or 2.03 and 0.355 μm allows us to detect vegetation under adverse conditions with a probability of correct detection close to one and a probability of false alarm ~ second decimal places.
Parameters of aerosol inhomogenuities in the atmosphere planetary boundary layer (PBL) at the wavelength of 1.06 μm have been experimentally studied. The paper describes a lidar and a data processing technique and presents measurement data of the spatiotemporal distribution of fluctuations of variations of a volume aerosol backscattering coefficient of atmosphere, histograms of sizes, and variation coefficient of a volume aerosol backscattering coefficient in the atmosphere PBL. A comparison with known measurement data in visible and UV spectral bands has been presented.
We present the results of experimental studies of aerosol inhomogeneities characteristics in atmosphere planetary boundary layer (PBL) at eye-safety 355 nm wavelength. For developed lidar system for monitoring aerosol inhomogeneities technical specifications of the key components are described. It includes a diode-pumped solid state (DPSS) laser with pulse energy 1.3 mJ, duration 7 ns and pulse repetition rate up to 500 Hz, Cassegrian telescope with prime mirror diameter 100 mm and photomultiplier tube (PMT) as photodetector. Lidar provides registration of aerosol elastic backscattering signal with high spatial (0.6 m) and temporal (0.002 s) resolution up to 1 km depending on atmosphere condition. The preprocessing algorithm to form lidar signal variation coefficient fields in "Range-Time" coordinates is discussed. Examples of these fields for different weather conditions are presented. Accumulated measurement data from 2015 to 2017 for spring-autumn period in Moscow region was analyzed and for more than 1 500 inhomogeneities shown histograms of size and average contrast. The obtained results are compared with the known measurement data in the visible spectral range.
We investigate the possibilities to use a laser reflection method for vegetation monitoring at eye-safe sensing wavelengths. A mathematical simulation involving spectral libraries of the vegetation reflection coefficients shows that the laser method (at the eye-safe sensing wavelengths in the ultra-violet and the near infrared spectral bands) can be accepted as a basis for vegetation monitoring. Laser sensing at the wavelengths of 2 and 0.38 μm or of 2 and 0.355 μm allows us to detect vegetation under adverse conditions with a probability of correct detection close to one and a probability of false alarm ~ second decimal places.
Laser induced fluorescence spectra of different types of petroleum products on various types of soils as well as natural and anthropogenic objects of underlying surface were measured for 355 nm excitation wavelength. Experimental setup was described. Results of fluorescence spectra processing were obtained. It was outlined, that fluorescence intensity of oil pollutions could have same value as fluorescence intensity of natural objects on underlying surface.
Experimental investigations of different factors influencing on stability of laser induced fluorescence spectra of plants were conducted for 532 nm wavelength of fluorescence excitation. The experimental setup was described and processing results of laser induced fluorescence spectra of plants were presented. Stability of the fluorescence intensity ratio R at wavelengths of 685 and 740 nm versus type of soil, and wide variance of the R ratio for different plants were demonstrated.
Experimental laboratory investigations of the laser-induced fluorescence spectra of watercress were conducted. The fluorescence spectra were excited by a YAG:Nd laser emitting at 532 nm. The laboratory setup was described and fluorescence spectra of watercress in stressed states caused by lack and excess of water were presented. It was established that the influence of stress caused by lack and excess of watering is manifested in changes of fluorescence spectra.
Oil spills detection algorithm for different underlying surfaces was developed. It was shown, that in order to detect oil
spills with high probability of correct detection and low probability of false alarm it wasn’t enough to use correlation
analysis only. An average intensity of fluorescence and the intensity of elastic scattering were used as additional
classification features, which enabled to reduce probability of false alarm.
Laser remote method of oil pollution detection on the rough sea surface is described. The method uses additional information about near-water wind and a special geometrical scheme for surface illumination. It is demonstrated that the offered method allows control of two effects independently and simultaneously: wind wave smoothing and changes of sea surface reflection coefficient. And consequently it allows decision making about oil contamination presence on the sea surface with a high reliability.
A numerical modeling of heterodyne efficiency of coherent laser imaging system at nonlinear scanning has been developed on the basis of Monte-Carlo method. A hysteresis effect of receiving field of view (FOV) has been analyzed at high-speed nonlinear scanning. The numerical mathematical modeling for coherent nonlinear scanning laser imaging system has been conducted at the nonlinear harmonic scanning with 160Hz frequency; 64x32 pixels image size and 10 frames per second. The numerical modeling showed that imaging pixels with 20% threshold of heterodyne efficiency were about 17 at the 20dB SNR, 10 frames per second and 2400m detecting distance.
A retrieval technique for some hydrocarbon compounds (ethylene, ethanol, methanol, and isopropanol) concentration from opto-acoustic measurements of total absorption at several fixed wavelengths of the CO2-laser is presented in the report. In the gases concentration reconstructing, the method of least squares (LSM) as well as linear programming (LPM) and regularization (RM) methods were used. The problem of accuracy of the gases concentration retrieval depending on the quantity of simultaneously analyzed hydrocarbon compounds is discussed. Monitoring of gas composition of the atmospheric air by the optical absorption methods calls for instruments which are highly sensitive to absorption, highly selective, and capable of determining the concentration of trace gases in multicomponent mixtures. One of such instruments an opto-acoustic (OA) gas analyzer with a resonance cell. To analyze the content of gases under study, the atmospheric air, preliminary purified from atmospheric aerosol is pumped through the OA cell. Our work is aimed at studying of the accuracy of gas concentration reconstruction from OA measurements depending on: (1) error in determining the absorption coefficients Kij; (2) available model of continuous absorption ac(vi); (3) random error in measuring signals.
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