Remote sensing of fruit tree micro environment plays a major role in both horticultural and soil mapping applications. In frame this study presented a novel method to survey the spatial distribution of physical and water management properties of soils. The examinations were carried out at an intensive experimental apple orchard in Debrecen-Pall...ag. The examination site is the part of the Experimental Pomology plantation of the University of Debrecen, Faculty of Agronomy. Particle-size distribution, plasticity according to Arany, metal content by XRF spectrometry, soil physical parameters, acidity, electric conductivity of soils, were measured to obtain appropriate information on the physical properties of the soil. Based on the results, the accurate spatial positions of those sites were characterized where soil loosening should be implemented in 0,3–0,4 m depth. Spatially precise soil physical barriers were determined for applied micro-irrigation system. Based on the micro-element content and pH, the accurate spatial positions of those sites were selected where melioration and micronutrient fertilization is needed. These detailed data sources also applied to calibrate the applied airborne hyperspectral images to extend spatially these point based information.
Nowadays 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 spectrosc...opy 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.