Título:	SiRCub - Brazilian Agricultural Crop Recognition System.
Autor:	TOMÀS, J. C. FARIA, F. A. ESQUERDO, J. C. D. M. COUTINHO, A. C. MEDEIROS, C. B.
Afiliación:	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.
Año:	2015
Referencia:	In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015.
Páginas:	p. 6273-6280.
Descripción:	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
Palabras clave:	Séries temporais LULC Cobertura da terra NDVI Support Vector Machine
Notas:	SBSR 2015.
Tipo de Material:	Artigo em anais e proceedings
Acceso:	openAccess
Aparece en las colecciones:	Artigo em anais de congresso (CNPTIA)