| 1. Identificação | ||||
| Tipo de Referência | Artigo em Revista Científica (Journal Article) | |||
| Site | mtc-m21c.sid.inpe.br | |||
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identificador | 8JMKD3MGP3W34R/3UM9KGL | |||
| Repositório | sid.inpe.br/mtc-m21c/2020/01.02.14.27 (acesso restrito) | |||
| Última Atualização | 2020:01.02.14.27.45 (UTC) simone | |||
| Repositório de Metadados | sid.inpe.br/mtc-m21c/2020/01.02.14.27.45 | |||
| Última Atualização dos Metadados | 2024:01.23.13.46.48 (UTC) simone | |||
| DOI | 10.1016/j.jag.2019.102004 | |||
| ISSN | 0303-2434 | |||
| Chave de Citação | BreunigGDDPSDC:2020:DeMaZo | |||
| Título | Delineation of management zones in agricultural fields using cover–crop biomass estimates from PlanetScope data  | |||
| Ano | 2020 | |||
| Mês | Mar. | |||
| Data de Acesso | 03 maio 2024 | |||
| Tipo de Trabalho | journal article | |||
| Tipo Secundário | PRE PI | |||
| Número de Arquivos | 1 | |||
| Tamanho | 10601 KiB | |||
| 2. Contextualização | ||||
| Autor | 1 Breunig, Fábio Marcelo 2 Galvão, Lênio Soares 3 Dalagnol da Silva, Ricardo 4 Dauve, Carlos Eduardo 5 Parraga, Adriane 6 Santi, Antônio Luiz 7 Della Flora, Diandra Pinto 8 Chen, Shuisen | |||
| Identificador de Curriculo | 1 2 8JMKD3MGP5W/3C9JHLF | |||
| Grupo | 1 2 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 3 DIDSR-CGOBT-INPE-MCTIC-GOV-BR | |||
| Afiliação | 1 Universidade Federal de Santa Maria (UFSM) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Fazenda Vila Morena 5 Universidade Estadual do Rio Grande do Sul (UERGRS) 6 Universidade Federal de Santa Maria (UFSM) 7 Universidade Federal da Grande Dourados (UFGD) 8 Guangzhou Institute of Geography | |||
| Endereço de e-Mail do Autor | 1 breunig@ufsm.br 2 lenio.galvao@inpe.br 3 ricardo.dalagnol@inpe.br | |||
| Revista | International Journal of Applied Earth Observation and Geoinformation | |||
| Volume | 85 | |||
| Páginas | e102004 | |||
| Nota Secundária | B1_GEOCIÊNCIAS | |||
| Histórico (UTC) | 2020-01-02 14:27:45 :: simone -> administrator :: 2020-01-02 14:27:45 :: administrator -> simone :: 2019 2020-01-02 14:28:58 :: simone -> administrator :: 2019 2020-01-03 16:26:19 :: administrator -> simone :: 2019 2020-03-02 12:15:30 :: simone :: 2019 -> 2020 2020-03-02 12:15:30 :: simone -> administrator :: 2020 2020-07-08 17:10:52 :: administrator -> simone :: 2020 2020-12-14 14:16:32 :: simone -> administrator :: 2020 2022-01-04 01:34:55 :: administrator -> simone :: 2020 | |||
| 3. Conteúdo e estrutura | ||||
| É a matriz ou uma cópia? | é a matriz | |||
| Estágio do Conteúdo | concluido | |||
| Transferível | 1 | |||
| Tipo do Conteúdo | External Contribution | |||
| Tipo de Versão | publisher | |||
| Palavras-Chave | Precision agriculture Remote sensing Biomass Satellite Machine learning Crop yield | |||
| Resumo | Several methods have been proposed to delineate management zones in agricultural fields, which can guide interventions of the farmers to increase crop yield. In this study, we propose a new approach using remote sensing data to delineate management zones at three farm sites located in southern Brazil. The approach is based on the hypothesis that the measured aboveground biomass (AGB) of the cover crops is correlated with the measured cash-crop yield and can be estimated from surface reflectance and/or vegetation indices (VIs). Therefore, we used seven different statistical models to estimate AGB of three cover crops (forage turnip, white oats, and rye) in the season prior to cash-crop planting. Surface reflectance and VIs were used as predictors to test the performance of the models. They were obtained from high spatial and temporal resolution data of the PlanetScope (PS) constellation of satellites. From the time series of 30 images acquired in 2017, we used the PS data that matched the dates of the field campaigns to build the models. The results showed that the satellite AGB estimates of the cover crops at the date of maximum VI response at the beginning of the flowering stage were useful to delineate the management zones. The cover-crop AGB models that presented the highest coefficient of determination (R-2) and the lowest root mean square (RMSE) in the validation and test datasets were Support Vector Machine (SVM), Cubist (CUB) and Stochastic Gradient Boosting (SGB). For most models and cover crops, the Enhanced Vegetation Index (EVI) and the Normalized Difference Vegetation Index (NDVI) were the two most important AGB predictors. At the date of maximum VI at the beginning of the flowering stage, the correlation coefficients (r) between the cover-crop AGB and the cash-crop yield (soybean and maize) ranged from +0.70 for forage turnip to +0.78 for rye. The fuzzy unsupervised classification of the cover-crop AGB estimates delineated two management zones, which were spatially consistent with those obtained from cash-crop yield. The comparison between both maps produced overall accuracies that ranged from 61.20% to 68.25% with zone 2 having higher cover-crop AGB and cash-crop yield than zone 1 over the three sites. We conclude that satellite AGB estimates of cover crops can be used as a proxy for generating management zone maps in agricultural fields. These maps can be further refined in the field with any other type of method and data, whenever necessary. | |||
| Área | SRE | |||
| Arranjo | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Delineation of management... | |||
| Conteúdo da Pasta doc | acessar | |||
| Conteúdo da Pasta source | não têm arquivos | |||
| Conteúdo da Pasta agreement |
| |||
| 4. Condições de acesso e uso | ||||
| Idioma | en | |||
| Arquivo Alvo | breunig_delineation.pdf | |||
| Grupo de Usuários | simone | |||
| Grupo de Leitores | administrator simone | |||
| Visibilidade | shown | |||
| Política de Arquivamento | denypublisher denyfinaldraft24 | |||
| Permissão de Leitura | deny from all and allow from 150.163 | |||
| Permissão de Atualização | não transferida | |||
| 5. Fontes relacionadas | ||||
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ER446E | |||
| Lista de Itens Citando | sid.inpe.br/bibdigital/2013/09.13.21.11 3 sid.inpe.br/mtc-m21/2012/07.13.14.53.28 1 | |||
| Divulgação | WEBSCI; PORTALCAPES; SCOPUS. | |||
| Acervo Hospedeiro | urlib.net/www/2017/11.22.19.04 | |||
| 6. Notas | ||||
| Notas | Prêmio CAPES Elsevier 2023 - ODS 2: Fome zero e Agricultura sustentável | |||
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url | |||
| 7. Controle da descrição | ||||
| e-Mail (login) | simone | |||
| atualizar | ||||