Skip navigation
Please use this identifier to cite or link to this item: https://repositorio.unb.br/handle/10482/43537
Files in This Item:
There are no files associated with this item.
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSilva, Miriam Rodrigues da-
dc.contributor.authorCarvalho Júnior, Osmar Abílio de-
dc.contributor.authorGuimarães, Renato Fontes-
dc.contributor.authorGomes, Roberto Arnaldo Trancoso-
dc.contributor.authorSilva, Cristiano Rosa-
dc.date.accessioned2022-04-26T12:36:40Z-
dc.date.available2022-04-26T12:36:40Z-
dc.date.issued2020-
dc.identifier.citationSILVA, Miriam Rodrigues da et al. Wheat planted area detection from the MODIS NDVI time series classification using the nearest neighbour method calculated by the Euclidean distance and cosine similarity measures, Geocarto International, v. 35, n. 13, 1400-1414, 2020. DOI: https://doi.org/10.1080/10106049.2019.1581266.pt_BR
dc.identifier.urihttps://repositorio.unb.br/handle/10482/43537-
dc.language.isoInglêspt_BR
dc.publisherTaylor & Francispt_BR
dc.rightsAcesso Restritopt_BR
dc.titleWheat planted area detection from the MODIS NDVI time series classification using the nearest neighbour method calculated by the Euclidean distance and cosine similarity measurespt_BR
dc.typeArtigopt_BR
dc.subject.keywordSéries temporaispt_BR
dc.subject.keywordAgriculturapt_BR
dc.subject.keywordFenologia vegetalpt_BR
dc.identifier.doihttps://doi.org/10.1080/10106049.2019.1581266pt_BR
dc.relation.publisherversionhttps://www.tandfonline.com/doi/full/10.1080/10106049.2019.1581266pt_BR
dc.description.abstract1his research aims to detect the wheat crop in the Northwest region of Rio Grande do Sul (Brazil) using MODIS NDVI time series. Detection of wheat crops presents two difficulties: (a) high variation of wheat phenological curves due to climatic fluctuations during the crop cycle and (b) the plantations are in an environment with different types of rural and urban targets. In solving these problems, we propose a classification based on the nearest neighbour (a specific case of the k-NN method) from the similarity and distance metrics combined with the determination of the best threshold value to individualize the wheat mask. The nearest neighbour classification using minimum distance (Kappa of 0.75) obtained a result equivalent to that of cosine similarity (Kappa of 0.74) as attested by the McNemar test. The planted area result was comparable to official statistics from the Brazilian Institute of Geography and Statistics obtained through direct interviews.pt_BR
Appears in Collections:GEA - Artigos publicados em periódicos

Show simple item record Recommend this item " class="statisticsLink btn btn-primary" href="/handle/10482/43537/statistics">



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.