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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Deriving vegetation indices for phenology analysis using genetic programming

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Author(s):
Almeida, Jurandy [1, 2] ; dos Santos, Jefersson A. [3] ; Miranda, Waner O. [3] ; Alberton, Bruna [4] ; Morellato, Leonor Patricia C. [4] ; Torres, Ricardo da S. [1]
Total Authors: 6
Affiliation:
[1] Univ Campinas UNICAMP, RECOD Lab, Inst Comp, BR-13083852 Campinas, SP - Brazil
[2] Fed Univ Sao Paulo UNIFESP, Inst Sci & Technol, BR-12247014 Sao Jose Dos Campos, SP - Brazil
[3] Univ Fed Minas Gerais, Dept Comp Sci, BR-31270010 Belo Horizonte, MG - Brazil
[4] Sao Paulo State Univ UNESP, Dept Bot, Phenol Lab, BR-13506900 Rio Claro, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: ECOLOGICAL INFORMATICS; v. 26, n. 3, p. 61-69, MAR 2015.
Web of Science Citations: 11
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. (AU)

FAPESP's process: 14/00215-0 - Remote phenology and leaf exchange patterns towards a sazonality gradient
Grantee:Bruna de Costa Alberton
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 10/51307-0 - Floristic diversity and seasonal patterns of rupestrian fields and cerrado
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 07/52015-0 - Approximation methods for visual computing
Grantee:Jorge Stolfi
Support type: Research Projects - Thematic Grants
FAPESP's process: 13/50169-1 - Towards an understanding of tipping points within tropical South American biomes
Grantee:Ricardo da Silva Torres
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - University-Industry Cooperative Research (PITE)
FAPESP's process: 10/52113-5 - e-phenology: the application of new technologies to monitor plant phenology and track climate changes in the tropics
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - Regular Grants
FAPESP's process: 09/18438-7 - Large-scale classification and retrieval for complex data
Grantee:Ricardo da Silva Torres
Support type: Regular Research Grants