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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series

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Autor(es):
Adami, Marcos [1, 2] ; Bernardes, Sergio [3] ; Arai, Egidio [1] ; Freitas, Ramon M. [4] ; Shimabukuro, Yosio E. [1] ; Espirito-Santo, Fernando D. B. [5] ; Rudorff, Bernardo F. T. [6] ; Anderson, Liana O. [7]
Número total de Autores: 8
Afiliação do(s) autor(es):
[1] Natl Inst Space Res IPNE, Remote Sensing Div, Av Astronautas 1758, BR-12227010 Sao Jose Dos Campos, SP - Brazil
[2] Natl Inst Space Res IPNE, Ctr Reg Amazonia, Parque Ciencia & Tecnol Guama INPE, Av Perimetral, BR-26516607 Belem, Para - Brazil
[3] Univ Georgia, Dept Geog, Ctr Geospatial Res, Athens, GA 30602 - USA
[4] Aerial Photog & Imaging Sci, Rua Fagundes Varela 41, Curitiba, PR - Brazil
[5] Univ Lancaster, LEC, Lancaster LA1 4YQ - England
[6] Agrosatelite Geotecnol Aplicada Ltda, Rodovia SC 401, Km 5, 4850 Loja E-23-30, BR-88032005 Florianopolis, SC - Brazil
[7] Natl Ctr Monitoring & Early Warning Nat Disasters, Estr Dr Altino Bondensan 500, BR-12247016 Sao Jose Dos Campos, SP - Brazil
Número total de Afiliações: 7
Tipo de documento: Artigo Científico
Fonte: International Journal of Applied Earth Observation and Geoinformation; v. 69, p. 148-163, JUL 2018.
Citações Web of Science: 5
Resumo

The development, implementation and enforcement of policies involving the rational use of the land and the conservation of natural resources depend on an adequate characterization and understanding of the land cover, including its dynamics. This paper presents an approach for monitoring vegetation dynamics using high-quality time series of MODIS surface reflectance data by generating fraction images using Linear Spectral Mixing Model (LSMM) over South America continent. The approach uses physically-based fraction images, which highlight target information and reduce data dimensionality. Further dimensionality was also reduced by using the vegetation fraction images as input to a Principal Component Analysis (PCA). The RGB composite of the first three PCA components, accounting for 92.9% of the dataset variability, showed good agreement with the main ecological regions of South America continent. The analysis of 21 temporal profiles of vegetation fraction values and precipitation data over South America showed the ability of vegetation fractions to represent phenological cycles over a variety of environments. Comparisons between vegetation fractions and precipitation data indicated the close relationship between water availability and leaf mass/chlorophyll content for several vegetation types. In addition, phenological changes and disturbance resulting from anthropogenic pressure were identified, particularly those associated with agricultural practices and forest removal. Therefore the proposed method supports the management of natural and non-natural ecosystems, and can contribute to the understanding of key conservation issues in South America, including deforestation, disturbance and fire occurrence and management. (AU)

Processo FAPESP: 15/50392-8 - Fernando Espírito Santo | Lancaster University - Inglaterra
Beneficiário:Tomas Ferreira Domingues
Linha de fomento: Auxílio à Pesquisa - Pesquisador Visitante - Internacional