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New evaluation method to detect physiological stress in fruit trees by airborne hyperspectral image spectroscopy
37-40.Views:163Nowadays airborne remote sensing data are increasingly used in precision agriculture. The fast space-time dependent localization of stresses in orchards, which allows for a more efficient application of horticultural technologies, could lead to improved sustainable precise management. The disadvantage of the near field multi and hyper spectroscopy is the spot sample taking, which can apply independently only for experimental survey in plantations. The traditional satellite images is optionally suitable for precision investigation because of the low spectral and ground resolution on field condition. The presented airborne hyperspectral image spectroscopy reduces above mentioned disadvantages and at the same time provides newer analyzing possibility to the user. In this paper we demonstrate the conditions of data base collection and some informative examination possibility. The estimating of the board band vegetation indices calculated from reflectance is well known in practice of the biomass stress examinations. In this method the N-dimension spectral data cube enables to calculate numerous special narrow band indexes and to evaluate maps. This paper aims at investigating the applied hyperspectral analysis for fruit tree stress detection. In our study, hyperspectral data were collected by an AISADUAL hyperspectral image spectroscopy system, with high (0,5-1,5 m) ground resolution. The research focused on determining of leaves condition in different fruit plantations in the peach orchard near Siófok. Moreover the spectral reflectance analyses could provide more information about plant condition due to changes in the absorption of incident light in the visible and near infrared range of the spectrum.
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Hyperspectral data in water stress detection
15-17.Views:172Remote sensing methods are applied widespread to investigate large land fields. Within these methods the status of certain vegetation can be determined based on the reflectance spectra of the chlorophyll, in order to support agriculture, forestry and the evaluation of soil pollution. The main aims of our study were to determine and validate the reflectance spectra of fruit tree species, in order to facilitate the identification and evaluation of stressed fruit trees in orchards.
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Precision geoinformatical system of the pear gene-collection orchard
43-50.Views:201The principle task of the sustainable development is the preservation of the genetic variety, which is similar challenge in the horticulture regarding the sublimation of fruit species. The breeders of the traditional fruit strains give stock to the sustenance diversity of the agro-environment on the species and landscape level. In 2009, hyperspectral images have been taken by AISA Dual sensors from the pear gene pool in Újfehértó, Hungary. The hyperspectral data cube (in the wavelength range of 400-2500 nm, with 1.5 m ground resolution) ensured possibility to make the spectral library of pear species. In the course of the simultaneously field work the spatial position and individual extent of all pear trees was defined to set up a detailed GIS data base. The water stress sensitivity of single species and the descriptive spectral curves were determined with common evaluation of the spectral and spatial data. Based on the unique methodology processing and the hyperspectral data base suitable strains can be chosen for agro-environment and let take adaptive stocks regarding climate change into the genetic grafting work. Furthermore we could determine and map the sparsely species in the region with the help of the hyperspectral data.