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Full text
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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.
[2]
Total Authors: 6
|
| Affiliation: | [1] Fed Univ Sao Paulo UNIFESP, Inst Sci & Technol, BR-12247014 Sao Jose Dos Campos, SP - Brazil
[2] Univ Campinas UNICAMP, RECOD Lab, Inst Comp, BR-13083852 Campinas, 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) |
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| FAPESP's process: |
07/52015-0 - Approximation methods for visual computing
|
| Grantee: | Jorge Stolfi |
| Support type: |
Research Projects - Thematic Grants
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| FAPESP's process: |
09/18438-7 - Large-scale classification and retrieval for complex data
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| Grantee: | Ricardo da Silva Torres |
| Support type: |
Regular Research Grants
|
|
|
| FAPESP's process: |
10/52113-5 - e-phenology: the application of new technologies to monitor plant phenology and track climate changes in the tropics
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| Grantee: | Leonor Patricia Cerdeira Morellato |
| Support type: |
Research Program on Global Climate Change - Regular Grants
|
|
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| FAPESP's process: |
13/50169-1 - Towards an understanding of tipping points within tropical South American biomes
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| Grantee: | Ricardo da Silva Torres |
| Support type: |
Research Grants - Research Partnership for Technological Innovation - PITE
|
|
|
| FAPESP's process: |
10/51307-0 - Floristic diversity and seasonal patterns of rupestrian fields and cerrado
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| Grantee: | Leonor Patricia Cerdeira Morellato |
| 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: |
14/00215-0 - Remote phenology and leaf exchange patterns towards a sazonality gradient
|
| Grantee: | Bruna de Costa Alberton |
| Support type: |
Scholarships in Brazil - Doctorate
|
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