Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Deriving Vegetation Indices For Phenology Analysis Using Genetic Programming
Author: Almeida J.
dos Santos J.A.
Miranda W.O.
Alberton B.
Morellato L.P.C.
da S. Torres R.
Abstract: Plant phenology studies recurrent plant life cycle events and is a key component for understanding the impact of climate change. To increase accuracy of observations, new technologies have been applied for phenological observation, and one of the most successful strategies relies on the use of digital cameras, which are used as multi-channel imaging sensors to estimate color changes that are related to phenological events. We monitor leaf-changing patterns of a cerrado-savanna vegetation by taking daily digital images. We extract individual plant color information and correlate with leaf phenological changes. For that, several vegetation indices associated with plant species are exploited for both pattern analysis and knowledge extraction. In this paper, we present a novel approach for deriving appropriate vegetation indices from vegetation digital images. The proposed method is based on learning phenological patterns from plant species through a genetic programming framework. A comparative analysis of different vegetation indices is conducted and discussed. Experimental results show that our approach presents higher accuracy on characterizing plant species phenology.
Editor: Elsevier
Rights: fechado
Identifier DOI: 10.1016/j.ecoinf.2015.01.003
Date Issue: 2015
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-84922719400.pdf1.22 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.