Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
05/11/2013
05/11/2013
2012
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Resumo |
Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast. FAPESP CNPq CAPES Embrapa Microsoft Research |
Identificador |
INTERNATIONAL JOURNAL OF REMOTE SENSING, ABINGDON, v. 33, n. 15, Special Issue, pp. 4653-4672, SEP, 2012 0143-1161 http://www.producao.usp.br/handle/BDPI/40985 10.1080/01431161.2011.638334 |
Idioma(s) |
eng |
Publicador |
TAYLOR & FRANCIS LTD ABINGDON |
Relação |
INTERNATIONAL JOURNAL OF REMOTE SENSING |
Direitos |
restrictedAccess Copyright TAYLOR & FRANCIS LTD |
Palavras-Chave | #AVHRR IMAGE NAVIGATION #LEAF-AREA INDEX #VEGETATION INDEXES #REMOTE SENSING #IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY |
Tipo |
article original article publishedVersion |