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  • Adami_2018

    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Applied Earth Observation and Geoinformation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Applied Earth Observation and Geoinformation, 69, 2018 DOI: 10.1016/j.jag.2018.02.010

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

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Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series. / Adami, Marcos; Bernardes, Sérgio; Arai, Egidio et al.
In: International Journal of Applied Earth Observation and Geoinformation, Vol. 69, 07.2018, p. 148-163.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Adami, M, Bernardes, S, Arai, E, Freitas, RM, Shimabukuro, YE, Espírito-Santo, FDB, Rudorff, BFT & Anderson, LO 2018, 'Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series', International Journal of Applied Earth Observation and Geoinformation, vol. 69, pp. 148-163. https://doi.org/10.1016/j.jag.2018.02.010

APA

Adami, M., Bernardes, S., Arai, E., Freitas, R. M., Shimabukuro, Y. E., Espírito-Santo, F. D. B., Rudorff, B. F. T., & Anderson, L. O. (2018). Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series. International Journal of Applied Earth Observation and Geoinformation, 69, 148-163. https://doi.org/10.1016/j.jag.2018.02.010

Vancouver

Adami M, Bernardes S, Arai E, Freitas RM, Shimabukuro YE, Espírito-Santo FDB et al. Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series. International Journal of Applied Earth Observation and Geoinformation. 2018 Jul;69:148-163. Epub 2018 Mar 26. doi: 10.1016/j.jag.2018.02.010

Author

Adami, Marcos ; Bernardes, Sérgio ; Arai, Egidio et al. / Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series. In: International Journal of Applied Earth Observation and Geoinformation. 2018 ; Vol. 69. pp. 148-163.

Bibtex

@article{05d773f4d5394f759a9bb655cb2b9d0e,
title = "Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series",
abstract = "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.",
keywords = "Vegetation dynamics, Land cover, Disturbance, Phenology, MODIS, Spectral mixing model, Principal component analysis, Time series",
author = "Marcos Adami and S{\'e}rgio Bernardes and Egidio Arai and Freitas, {Ramon M.} and Shimabukuro, {Yosio E.} and Esp{\'i}rito-Santo, {Fernando D.B.} and Rudorff, {Bernardo F.T.} and Anderson, {Liana O.}",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in International Journal of Applied Earth Observation and Geoinformation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Applied Earth Observation and Geoinformation, 69, 2018 DOI: 10.1016/j.jag.2018.02.010",
year = "2018",
month = jul,
doi = "10.1016/j.jag.2018.02.010",
language = "English",
volume = "69",
pages = "148--163",
journal = "International Journal of Applied Earth Observation and Geoinformation",
issn = "0303-2434",
publisher = "International Institute for Aerial Survey and Earth Sciences",

}

RIS

TY - JOUR

T1 - Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series

AU - Adami, Marcos

AU - Bernardes, Sérgio

AU - Arai, Egidio

AU - Freitas, Ramon M.

AU - Shimabukuro, Yosio E.

AU - Espírito-Santo, Fernando D.B.

AU - Rudorff, Bernardo F.T.

AU - Anderson, Liana O.

N1 - This is the author’s version of a work that was accepted for publication in International Journal of Applied Earth Observation and Geoinformation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Applied Earth Observation and Geoinformation, 69, 2018 DOI: 10.1016/j.jag.2018.02.010

PY - 2018/7

Y1 - 2018/7

N2 - 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.

AB - 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.

KW - Vegetation dynamics

KW - Land cover

KW - Disturbance

KW - Phenology

KW - MODIS

KW - Spectral mixing model

KW - Principal component analysis

KW - Time series

U2 - 10.1016/j.jag.2018.02.010

DO - 10.1016/j.jag.2018.02.010

M3 - Journal article

VL - 69

SP - 148

EP - 163

JO - International Journal of Applied Earth Observation and Geoinformation

JF - International Journal of Applied Earth Observation and Geoinformation

SN - 0303-2434

ER -