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Proceedings Paper

Unmanned Aerial Vehicle (UAV) data analysis for fertilization dose assessment
Author(s): Antonis Kavvadias; Emmanouil Psomiadis; Maroulio Chanioti; Alexandros Tsitouras; Leonidas Toulios; Nicholas Dercas
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Paper Abstract

The growth rate monitoring of crops throughout their biological cycle is very important as it contributes to the achievement of a uniformly optimum production, a proper harvest planning, and reliable yield estimation. Fertilizer application often dramatically increases crop yields, but it is necessary to find out which is the ideal amount that has to be applied in the field. Remote sensing collects spatially dense information that may contribute to, or provide feedback about, fertilization management decisions. There is a potential goal to accurately predict the amount of fertilizer needed so as to attain an ideal crop yield without excessive use of fertilizers cause financial loss and negative environmental impacts. The comparison of the reflectance values at different wavelengths, utilizing suitable vegetation indices, is commonly used to determine plant vigor and growth. Unmanned Aerial Vehicles (UAVs) have several advantages; because they can be deployed quickly and repeatedly, they are flexible regarding flying height and timing of missions, and they can obtain very high-resolution imagery. In an experimental crop field in Eleftherio Larissa, Greece, different dose of pre-plant and in-season fertilization was applied in 27 plots. A total of 102 aerial photos in two flights were taken using an Unmanned Aerial Vehicle based on the scheduled fertilization. Α correlation of experimental fertilization with the change of vegetation indices values and with the increase of the vegetation cover rate during those days was made. The results of the analysis provide useful information regarding the vigor and crop growth rate performance of various doses of fertilization.

Paper Details

Date Published: 2 November 2017
PDF: 9 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 1042121 (2 November 2017);
Show Author Affiliations
Antonis Kavvadias, En Agris LLC (Greece)
Emmanouil Psomiadis, Agricultural Univ. of Athens (Greece)
Maroulio Chanioti, Inforest Research O.C. (Greece)
Alexandros Tsitouras, Hellenic Agricultural Organization (Greece)
Leonidas Toulios, Hellenic Agricultural Organization (Greece)
Nicholas Dercas, Agricultural Univ. of Athens (Greece)

Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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