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Hyperspectral Remote Sensing Imagery Processing Focused on Forest Applications

Vladimir V. Kozoderov(1*), Timofei V. Kondranin(2), Egor V. Dmitriev(3)

(1) M.V. Lomonosov Moscow State University, Russian Federation
(2) Moscow Institute of Physics and Technology (State University), Russian Federation
(3) Institute of Numerical Mathematics of Russian Academy of Science, Russian Federation
(*) Corresponding author


DOI: https://doi.org/10.15866/irease.v10i5.12893

Abstract


Imaging spectrometers with hundreds of spectral channels in visible and infrared regions are designed by various companies to enhance the information content of the relevant hyperspectral imagery processing compared to common-used multispectral systems. We review some sources on this particular subject to show the priorities of the hyperspectral approach before the multispectral one in forest and agriculture applications. There is also a discussion about some results of the information products obtained by an imaging spectrometer produced in Russia for a test area, where the ground-based forest inventory map is available to compare the traditional approaches and the newly defined ones. The related applications concern the pattern recognition of forest classes with different species and age on the test area using the airborne hyperspectral imagery processing.
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Keywords


Remote Sensing; Multispectral Images; Hyperspectral Images; Pattern Recognition; Forest Vegetation; Agriculture

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References


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