INNOVATIVE TECHNIQUES OF HYPER-SPECTRAL AIRBORNE IMAGERY PROCESSING ON TEST AREA AS COMPARED WITH GROUND-BASED FOREST INVENTORY DATA IN TVER REGION, RUSSIA

Авторы: Kozoderov V.V., Dmitriev E.V.
Журнал: The Complex Systems
Том: 29
Номер: 4
Год издания: 2018
Первая страница: 3
Последняя страница: 12
Аннотация: Remote sensing systems might be considered as an alternative to groundbased forest inventory dealing with laborious works on test sites. Pre-requisites of the newly defined techniques are presented to recognize remote sensing images and to estimate parameters relating to the forest canopy of different species and age on the test area, where common-used ground-based map of forest inventory is available. The test site is described of the area in Tver region of Russia based on domestic hyper-spectral imagery processing using spectral and texture features of the forest objects extracted from the images. The recognition procedures are presented of the airborne imagery processing with the errors of the relevant validation together with such parameters of the forest canopy as the projective cover and biomass amount retrieved by the related techniques for different types of forests. The accuracy category is typical within 5-15% for the trial plots in the inventory maps. The accuracy of our pattern recognition techniques for hyper-spectral imagery processing is not worse of this level. This opens up prospects for the newly defined applications of remote sensing imagery processing.
Добавил в систему: Козодеров Владимир Васильевич

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