An experiment research for determination of oil-spills on the sea surface was performed by using a shipboard laser fluorosensor in Jiaozhou Bay. The laser-induced fluorescence(LIF) spectra of five kinds of oils were obtained. The results show that the LIF spectra of the in situ measurement are basically consistent with those of the laboratory measurement, and these spectra can be discriminated.
In this paper, we make research on the analysis and processing for some data from an in-flight absolutely radiometric calibration experiment of imaging spectrometer. We use two kinds of methods to retrieve the surface reflectance of some targets on the ground and make a comparison with measured results.
Infrared spectra from the several typical pollution clouds are observed remotely using a passive Fourier Transform Infrared Spectrometer. The primary purpose of the study is to determine an efficient method to distinguish hazardous-cloud from several clouds. Spectral pattern recognition techniques are employed to suppress the strong and highly varying background to extract the very weak emission features from measured spectra. It can be used to discriminate specific pollution cloud between several smokes and interferents.
Since LIF lidar has a higher sensitivity in detecting very thin oil spill, chlorophyll, gebstoff in water, it becomes a useful tool for monitoring marine environment and primary productive forces. Researches indicate especially that it is the unique technique in discriminating the sort of oil spill as comparing to the passive optical and the active microwave remote sensing techniques. In this paper we summarize the state-of-art of LIF lidar technique such as laser sources, optics and return analysis. Then we discuss its potential power in wider application aspects. Some suggestions for developing LIF lidar will be provided and assessed.
The development of effective methods in environmental pollution control is a main task of environmental research. Fourier-transform IR spectroscopy is an efficient technique for the detection and quantification of molecules in gas mixtures. A passive IR system designed to detect specific pollution clouds in the atmosphere and sound an alarm in time. The sensor is a Fourier transform spectrometer operating in the 8-12 micrometers atmosphere window region of the spectrum. The system can be operated unattended and be highly reliable and accurate in its decisions. An on-board microcomputer will be applied to achieve automatically control of system, acquire data, process it and make decisions. The paper describes the signal processing and spectral pattern recognition techniques. Measurement results for ambient air with the spectrometer are reported.
Computed Tomography (CT) is a modern medical diagnostic technique in which x-ray transmission measurements at numerous angles through the human body are processed by computer to produce cross-sectional pictures of the body. This technique also has found applications in such diverse fields as materials testing, astronomy, microscopy, image processing and oceanography.In this paper, a modification of this technique, using emitted IR or microwave radiation instead of transmitted x-ray radiation, can be applied to satellite radiance measurements taken along the orbital track at various angles. The channels of IR sensors for the CT retrieval are selected from HITRAN Database, and analyzed by Eigen-value analysis. We discuss in detail the effect retrieval result of CT technique form projection-angle. Finally, using the balloon sounding data, the result of CT are compared with the result of conventional method. Because the advantage over conventional remote sensing methods is the additional information acquired by viewing a given point in the atmosphere at several angles as well as several frequencies. The results show that the temperature profiles by CT retrieval are better than the conventional method.
KEYWORDS: Wavelets, Remote sensing, Infrared spectroscopy, Data processing, Spectroscopy, Signal processing, Neural networks, Algorithms, Data acquisition, Algorithm development
In this paper we will first introduce the basic theory and algorithms of wavelet techniques, and then will try to use it to process the remote sensing spectral data acquired by IR Fourier transform spectrometer, we also discuss that self- adaptive wavelet network applied to classify the spectra. The experimental results show that wavelet techniques is very efficient in processing and classification of spectral data.
A real-time compound identification system for Fourier Transform Infrared Spectroscopy data has been based on the direct comparison of interferograms. Statistical pattern- recognition methods are applied to the feature extraction of infrared interferograms. Using large training sets, a real- time classification filter has been developed that is able to discriminate the specific-compound of infrared interferograms, and it has a very high probability. Our system can be used to identify several specific-compounds (several chemical vapors) of infrared interferograms of remote detection.
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