Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1028693
Title: SiRCub - Brazilian Agricultural Crop Recognition System.
Authors: TOMÀS, J. C.
FARIA, F. A.
ESQUERDO, J. C. D. M.
COUTINHO, A. C.
MEDEIROS, C. B.
Affiliation: JORDI CREUS TOMÀS, IC/Unicamp; FABIO AUGUSTO FARIA, IC/Unicamp; JÚLIO CÉSAR DALLA MORA ESQUERDO, CNPTIA; ALEXANDRE CAMARGO COUTINHO, CNPTIA; CLAUDIA BAUZER MEDEIROS, IC/UNICAMP.
Date Issued: 2015
Citation: In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015.
Pages: p. 6273-6280.
Description: This paper presents a novel approach to classify agricultural crops using NDVI time series. The novelty lies in i) extracting a set of features from the each and every NDVI curve, and ii) using them to train a crop classification model using a Support Vector Machine (SVM). Specifically, we use the TIMESAT program package to: 1) smooth the time series, 2) decompose them into agricultural seasons?a season is the period between sowing and harvesting?, and 3) extract the features for each season.
Thesagro: Uso da terra
NAL Thesaurus: Time series analysis
Land use
Land cover
Keywords: Séries temporais
LULC
Cobertura da terra
NDVI
Support Vector Machine
Notes: SBSR 2015.
Type of Material: Artigo em anais e proceedings
Access: openAccess
Appears in Collections:Artigo em anais de congresso (CNPTIA)

Files in This Item:
File Description SizeFormat 
SBSRTomas.pdf3.24 MBAdobe PDFThumbnail
View/Open

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace