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 | Size | Format | |
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SBSRTomas.pdf | 3.24 MB | Adobe PDF | ![]() View/Open |