Deriving vegetation indices for phenology analysis using genetic programming

Deriving vegetation indices for phenology analysis using genetic programming

Author Almeida, Jurandy Autor UNIFESP Google Scholar
Santos, Jefersson A. dos Google Scholar
Miranda, Waner O. Google Scholar
Alberton, Bruna Google Scholar
Morellato, Leonor Patricia C. Google Scholar
Torres, Ricardo da S. Google Scholar
Institution Universidade Federal de São Paulo (UNIFESP)
Universidade Federal de Minas Gerais (UFMG)
São Paulo State Univ UNESP
Universidade Estadual de Campinas (UNICAMP)
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. (C) 2015 Elsevier B.V. All rights reserved.
Keywords Remote phenology
Digital cameras
Image analysis
Vegetation indices
Genetic programming
Language English
Sponsor Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Microsoft Research Virtual Institute
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)
Grant number Microsoft Research Virtual Institute: 2010/52113-5
Microsoft Research Virtual Institute: 2013/50169-1
Microsoft Research Virtual Institute: 2013/50155-0
FAPESP: 2014/00215-0
FAPESP: 2007/52015-0
FAPESP: 2007/59779-6
FAPESP: 2009/18438-7
FAPESP: 2010/51307-0
CNPq: 306243/2010-5
CNPq: 306587/2009-2
CNPq: 449638/2014-6
FAPEMIG: APQ-00768-14
Date 2015-03-01
Published in Ecological Informatics. Amsterdam: Elsevier B.V., v. 26, p. 61-69, 2015.
ISSN 1574-9541 (Sherpa/Romeo, impact factor)
Publisher Elsevier B.V.
Extent 61-69
Origin http://dx.doi.org/10.1016/j.ecoinf.2015.01.003
Access rights Closed access
Type Article
Web of Science ID WOS:000353744700007
URI http://repositorio.unifesp.br/handle/11600/38829

Show full item record




File

File Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Search


Browse

Statistics

My Account