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|Title:||Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs||Authors:||Papadavid, Georgios
Hadjimitsis, Diofantos G.
|Keywords:||Agricultural education;Field spectroscopy;Remote sensing;Satellite data||Category:||Civil Engineering||Field:||Engineering and Technology;Agricultural Sciences||Issue Date:||1-Jan-2016||Source:||4th International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2016, Paphos, Cyprus, 4 April 2016 through 8 April 2016||Conference:||International Conference on Remote Sensing and Geoinformation of the Environment||Abstract:||© 2016 SPIE. Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.||Description:||Proceedings of SPIE - The International Society for Optical Engineering, Volume 9688, 2016, Article number 96881T||URI:||https://ktisis.cut.ac.cy/handle/10488/14241||ISSN:||0277786X||DOI:||10.1117/12.2242911||Type:||Conference Papers|
|Appears in Collections:||Δημοσιεύσεις σε συνέδρια /Conference papers - poster -presentation|
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