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Proceedings Paper

Aerial image mosaics built using images with vegetation index pre-calculated
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Paper Abstract

Precision agriculture (PA) has offered a multitude of benefits to farmers, such as cost reduction, accuracy and speed in decision making. Among the tools that work with PA, the aerial image mosaics have key role in accurate mapping of diseases and pests in crops. A mosaic is the combination of multiple images, creating a new image that covers the property or plots accurately. One of the important analysis for farmers is based on the properties of the reflectance in each range of the electromagnetic spectrum of vegetation. Performing mathematical combinations of the different spectral bands has a better understanding of the spectral response of the vegetation. These combinations are called vegetation index (VI) and are useful for the control of the biomass, water content in leaf, chlorophyll content and others. It is usually calculated VI after the construction of the mosaic, as well the farmer has an accurate analysis of its vegetation. However, building a mosaic of images, it has a high computational cost, taking hours to complete and then apply the VI and to have the first test results. In order to reduce the computational cost of this process, this work aims to present a mosaic of images constructed from images with the VI already pre-calculated providing faster analysis to the farmer, given the fact that applying VI on the image came a this reduction in density image and thus have the gain in computational cost to build the mosaic.

Paper Details

Date Published: 25 October 2016
PDF: 6 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980K (25 October 2016); doi: 10.1117/12.2241066
Show Author Affiliations
Leandro Rosendo Candido, Escola de Engenharia de São Carlos (Brazil)
Lúcio André de Castro Jorge, Empresa Brasileira de Pesquisa Agropecuária (Brazil)
Maximiliam Luppe, Escola de Engenharia de São Carlos (Brazil)


Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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