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Kozoderov V. V. Kondranin T. V. Dmitriev E. V. 《Izvestiya Atmospheric and Oceanic Physics》2017,53(9):1132-1141
Izvestiya, Atmospheric and Oceanic Physics - The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of... 相似文献
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V. V. Kozoderov T. V. Kondranin E. V. Dmitriev V. P. Kamentsev 《Izvestiya Atmospheric and Oceanic Physics》2012,48(9):941-948
The characteristic features of airspace hyperspectral remote sensing (RS) are considered in order to develop classification techniques for relevant images. Currently available approaches to constructing classifiers (computational procedures) are described for recognizing natural and anthropogenic objects in hyperspectral images. We confirm that the methods under development are effective enough with the reduced dimensionality of the feature space of original spectra and the decreased sample volumes in supervising procedures for the selected object classes. Data from joint hyperspectral and aerial photography provide examples of the spectral distributions smoke of different intensities from forest and peat fires in the presence and absence of fire sources, for the smoke coverage of water surfaces, and for the forest vegetation without ignition sources within a selected area. The results obtained in the supervising procedures are used for pattern recognition and scene analysis in airborne images obtained for the test areas during forest-fire season. 相似文献
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Izvestiya, Atmospheric and Oceanic Physics - Computational schemes for forest vegetation identification on airborne hyperspectral images are implemented using the feature of the red edge in the... 相似文献
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Izvestiya, Atmospheric and Oceanic Physics - The pattern recognition of a forest surface from remote sensing data (both airborne hyperspectral data and WorldView-2 multichannel satellite data of... 相似文献
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Models of Pattern Recognition and Forest State Estimation Based on Hyperspectral Remote Sensing Data
Izvestiya, Atmospheric and Oceanic Physics - Model applications of airborne hyperspectral remote sensing data for the recognition of forest stand objects and parameterization of the environmental... 相似文献
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Kozoderov V. V. Dmitriev E. V. Melnik P. G. Donskoi S. A. 《Izvestiya Atmospheric and Oceanic Physics》2018,54(9):1374-1380
Izvestiya, Atmospheric and Oceanic Physics - The application of hyperspectral remote sensing of high spatial resolution is compared to conventional ground-based forest surveys on sample plots and... 相似文献
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For the problem of pattern recognition of natural and man-made objects using remote hyperspectral imaging data, we propose
an approach that is based on both the criterion of a minimal Euclidean distance relative to spectra of some reference objects
and specific features of wavelength shift of the area of transition from the chlorophyll absorption band to the spectral reflectivity
maximum that is characteristic to vegetation. The database of this pattern-recognition method is constructed on the basis
of pixel radiance histograms for particular spectral channels. The histogram in the maximum separability wavelength of object
classes characteristic of the chosen test area is divided into a certain number of spectral intervals, which are grouped with
respect to the above-mentioned shift. Using computational techniques for separating out these spectral groups, we point to
new possibilities in the recognition of different vegetation types with the help of high-resolution spatial and spectral air
sounding data. 相似文献
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E. A. Sharkov Ya. N. Shramkov I. V. Pokrovskaya V. G. Bondur S. A. Pulinets S. S. Karimova O. Yu. Lavrova D. M. Solov’ev V. V. Kozoderov T. V. Kondranin E. V. Dmitriev V. P. Kamentsev A. N. Safronov E. V. Fokeeva V. S. Rakitin L. N. Yurganov E. I. Grechko 《Izvestiya Atmospheric and Oceanic Physics》2014,50(2):224-224
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