@Article{FreitasAAFYSRAR:2011:ViMOEV,
author = "Freitas, Ramon Morais de and Arai, Egidio and Adami, Marcos and
Ferreira, A. S. and Yuzo, Fernando and Shimabukuro, Yosio Edemir
and Rosa, Reinaldo Roberto and Anderson, Liana Oighenstein and
Rudorff, Bernardo Friedrich Theodor",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and 2University
of Oxford, Environmental Change Institute – ECI, Oxford, UK. and
{Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Virtual laboratory of remote sensing time series: visualization of
MODIS EVI2 data set over South America",
journal = "Journal of Computational Interdisciplinary Sciences",
year = "2011",
volume = "2",
number = "1",
pages = "57--64",
note = "Setores de Atividade: Agricultura, Pecu{\'a}ria,
Produ{\c{c}}{\~a}o Florestal, Pesca e Aq{\"u}icultura.",
keywords = "MODIS, EVI2, wavelets transform, time series analysis, virtual
globe, land use and land cover changes, forest, agriculture, South
America, instantaneous visualization.",
abstract = "Over the last ten years millions of gigabytes of MODIS (Moderate
Resolution Imaging Spectroradiometer) data have been generated
which is forcing the remote sensing users community to a new
paradigm in data processing for image analysis and visualization
of these time series. In this context this paper aims to present
the development of a tool to integrate the 10 years time series of
MODIS images into a virtual globe to support LULC change studies.
Initially the development of a tool for instantaneous
visualization of remote sensing time series within the concept of
a virtual laboratory framework is described. The virtual
laboratory is composed by a data set with more than 500 million
EVI2 (Enhanced Vegetation Index 2) time series derived from MODIS
16-day composite data. The EVI2 time series were filtered with
sensor ancillary data and Daubechies (Db8) orthogonal Discrete
Wavelets Transform. Then EVI2 time series were integrated into the
virtual globe using Google Maps and Google Visualization
Application Programming Interface functionalities. The Land Use
Land Cover changes for forestry and agricultural applications are
presented using the proposed time series visualization tool. The
tool demonstrated to be useful for rapid LULC change analysis, at
the pixel level, over large regions. Next steps are to further
develop the Virtual Laboratory of Remote Sensing Time Series
Framework by extending this work for other geographical regions,
incorporating new computational algorithms, testing data from
other sensors and updating the MODIS time series.",
issn = "1983-8409 and 2177-8833",
label = "lattes: 7514918598084999 9 FreitasAAFYSRAR:2011:ViOfMO",
language = "pt",
targetfile = "freitas.pdf",
urlaccessdate = "15 jun. 2024"
}