@Article{SantosFontSilvRudo:2014:IdSpTe,
author = "Santos, Juliana Silveira dos and Fontana, Denise C. and Silva,
Thiago S. F. and Rudorff, Bernardo Friedrich Theodor",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and CEPSRM,
UFRGS and UNESP and {Agrosat{\'e}lite Geotecnologia Aplicada}",
title = "Identification of the spatial and temporal dynamics for estimating
soybean crop area from MODIS images in the Rio Grande do Sul,
Brazil / Identifica{\c{c}}{\~a}o da din{\^a}mica
espa{\c{c}}o-temporal para estimar {\'a}rea cultivada de soja a
partir de imagens MODIS no Rio Grande do Sul",
journal = "Revista Brasileira de Engenharia Agr{\'{\i}}cola e Ambiental",
year = "2014",
volume = "18",
number = "1",
pages = "54--63",
month = "Jan.",
keywords = "imagens multitemporais, fenologia, previs{\~a}o de safras,
sensoriamento remoto, multitemporal imagery, phenology, crop yield
predictive, remote sensing.",
abstract = "Com este trabalho prop{\~o}e-se definir um m{\'e}todo para
estimar a {\'a}rea cultivada de soja na regi{\~a}o norte do Rio
Grande do Sul. Foram propostos seis m{\'e}todos baseados no
perfil espectro-temporal e de valores m{\'{\i}}nimos e
m{\'a}ximos de imagens NDVI/MODIS referentes {\`a}s etapas de
semeadura, m{\'a}ximo desenvolvimento e colheita das {\'a}reas
de soja. As estimativas obtidas foram comparadas com dados
oficiais do IBGE a partir de an{\'a}lises estat{\'{\i}}sticas e
da an{\'a}lise espacial fuzzy. Os resultados indicaram que
estimativas agr{\'{\i}}colas satisfat{\'o}rias s{\~a}o
dependentes de caracter{\'{\i}}sticas como o tamanho, o tipo de
manejo e a {\'e}poca de plantio e de colheita das lavouras. Para
todos os m{\'e}todos avaliados foram obtidos valores de
coeficientes de determina{\c{c}}{\~a}o e da an{\'a}lise fuzzy
superiores a 0,8 e 0,45, respectivamente. O m{\'e}todo limiar
emp{\'{\i}}rico aplicado {\`a} imagem diferen{\c{c}}a com
inclus{\~a}o do final de ciclo, gerou estimativas iguais {\`a}s
dos dados oficiais do IBGE, caracter{\'{\i}}stica que ressalta a
utiliza{\c{c}}{\~a}o deste m{\'e}todo em programas operacionais
de previs{\~a}o de safras. Para an{\'a}lises espaciais
recomenda-se a aplica{\c{c}}{\~a}o do m{\'e}todo
Classifica{\c{c}}{\~a}o de imagens multitemporais que gerou um
mapa de melhor qualidade. A efici{\^e}ncia dos m{\'e}todos deve
ser avaliada em {\'a}reas de expans{\~a}o de soja no Estado.
ABSTRACT: The objective of this study was to define a method for
estimating soybean crop area in the Northern Rio Grande do Sul
state (Brazil). Overall, six different remote sensing methods were
proposed based on spectral-temporal profile and minimum and
maximum values of NDVI/MODIS related to the stages of sowing,
maximum development and harvesting of soybean areas. The resulting
estimates were compared to official crop area data provided by the
Brazilian government, using statistical analysis and the fuzzy
similarity method. The performance of each method depended on
information such as crop size, type of crop management, and
sowing/harvesting dates. Regression coefficients of determination
and fuzzy agreement values were above 0.8 and 0.45, respectively,
for all methods. For operational monitoring of soybean crop area,
the empirical threshold applied to the image difference with
inclusion of harvest image method was the most effective,
producing estimates that matched closely the official data. For
spatial analysis the application of multitemporal images
classification method is recommended that generated a map of
better quality. The efficiency of these methods should be
evaluated in the areas of soybean expansion in the state.",
doi = "10.1590/S1415-43662014000100008",
url = "http://dx.doi.org/10.1590/S1415-43662014000100008",
issn = "1415-4366",
label = "scopus 2014-05 SantosFontSilvRudo:2014:IdSpTe",
language = "en",
targetfile = "v18n1a08.pdf",
url = "http://dx.doi.org/10.1590/S1415-43662014000100008",
urlaccessdate = "15 jun. 2024"
}