Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/92392
Type of publication: Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Miškotyra / Forestry (A004)
Author(s): Mozgeris, Gintautas;Gadal, Sébastien;Jonikavičius, Donatas;Straigytė, Lina;Ouerghemmi, Walid;Juodkienė, Vytautė
Title: Hyperspectral and color-infrared imaging from ultra-light aircraft: Potential to recognize tree species in urban environment
Is part of: 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016, Los Angeles, CA, USA, August 21-24, 2016. Los Angeles: IEEE, 2016
Extent: p. 1-5
Date: 2016
Note: eISBN: 9781509006083, USB ISBN: 9781509006076.ISBN: 9781538605905
Keywords: hyperspectral imaging;color-infrared images;ultra-light aircraft;urban tree species identification;discriminant analysis
Abstract: Imaging system based on simultaneous use of Rikola hyperspectral and RGB/NIR cameras installed on a manned ultra-light aircraft is introduced in this study. Simultaneously acquired hyperspectral and color-infrared (CIR) images were tested for their potential to identify deciduous tree species and estimate tree health in Kaunas city, Lithuania. Six urban deciduous tree species were separated using tree crown level statistics, extracted from 16 visible-near infrared spectral band hyperspectral images, and discriminant analyses with an overall classification accuracy of 63.1 %. Classification accuracy increased by 3 percent when hyperspectral images were integrated with simultaneously acquired CIR images. The accuracy in identifying tree health using fused hyperspectral and CIR images, ranged from poor to moderate
Internet: https://hdl.handle.net/20.500.12259/92392
Affiliation(s): Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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