Spectral model for soybean yield estimate using MODIS/EVI data
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/89727 |
Resumo: | Attaining reliable and timely agricultural estimates is very important everywhere, and in Brazil, due to its characteristics, this is especially true. In this study, estimations of crop production were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images. The objective was to evaluate the coupled model (CM) performance of crop area and crop yield estimates based solely on MODIS/EVI as input data in Rio Grande do Sul State, which is characterized by high variability in seasonal soybean yields, due to different crop development conditions. The resulting production estimates from CM were compared to official agricultural statistics of Brazilian Institute of Geography and Statistics (IBGE) and the National Company of Food Supply (CONAB) at different levels from 2000/2001 to 2010/2011 crop years. Results obtained with CM indicate that its application is able to generate timely production estimates for soybean both at municipality and local levels. Validation estimates with CM at State level obtained R2 = 0.95. Combining all cropping years at municipality level, estimates were highly correlated to official statistics from IBGE, with R2 = 0.91 and RMSD = 10,840 tons. Spatially interpolated comparisons of yield maps obtained from the CM estimates and IBGE data also showed visual similarity in their spatial distribution. Local level comparisons were performed and presented R2 = 0.95. Implications of this work point out that time-series analysis of production estimates are able to provide anticipated spatial information prior to the soybean harvest. |
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Gusso, AníbalDucati, Jorge RicardoVeronez, Maurício RobertoArvor, DamienSilveira Junior, Luiz Gonzaga da2014-03-26T01:51:20Z20132156-8359http://hdl.handle.net/10183/89727000905666Attaining reliable and timely agricultural estimates is very important everywhere, and in Brazil, due to its characteristics, this is especially true. In this study, estimations of crop production were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images. The objective was to evaluate the coupled model (CM) performance of crop area and crop yield estimates based solely on MODIS/EVI as input data in Rio Grande do Sul State, which is characterized by high variability in seasonal soybean yields, due to different crop development conditions. The resulting production estimates from CM were compared to official agricultural statistics of Brazilian Institute of Geography and Statistics (IBGE) and the National Company of Food Supply (CONAB) at different levels from 2000/2001 to 2010/2011 crop years. Results obtained with CM indicate that its application is able to generate timely production estimates for soybean both at municipality and local levels. Validation estimates with CM at State level obtained R2 = 0.95. Combining all cropping years at municipality level, estimates were highly correlated to official statistics from IBGE, with R2 = 0.91 and RMSD = 10,840 tons. Spatially interpolated comparisons of yield maps obtained from the CM estimates and IBGE data also showed visual similarity in their spatial distribution. Local level comparisons were performed and presented R2 = 0.95. Implications of this work point out that time-series analysis of production estimates are able to provide anticipated spatial information prior to the soybean harvest.application/pdfporInternational journal of geosciences. Irvine, CA. Vol. 4, n. 9 (Nov. 2013), p. 1233-1241Sensoriamento remotoImagens de sateliteSojaRemote sensingCoupled modelSoy yieldForecastSatellite imagesSpectral model for soybean yield estimate using MODIS/EVI dataEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000905666.pdf000905666.pdfTexto completoapplication/pdf3801911http://www.lume.ufrgs.br/bitstream/10183/89727/1/000905666.pdf6fd4038c533d9503d16fc3a28075f52dMD51TEXT000905666.pdf.txt000905666.pdf.txtExtracted Texttext/plain42526http://www.lume.ufrgs.br/bitstream/10183/89727/2/000905666.pdf.txt3a55310d0f2fca966cc27584431779dfMD52THUMBNAIL000905666.pdf.jpg000905666.pdf.jpgGenerated Thumbnailimage/jpeg2213http://www.lume.ufrgs.br/bitstream/10183/89727/3/000905666.pdf.jpg713917b8178cfd1836a0eb664a4463c7MD5310183/897272018-10-18 08:56:25.647oai:www.lume.ufrgs.br:10183/89727Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2018-10-18T11:56:25Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Spectral model for soybean yield estimate using MODIS/EVI data |
title |
Spectral model for soybean yield estimate using MODIS/EVI data |
spellingShingle |
Spectral model for soybean yield estimate using MODIS/EVI data Gusso, Aníbal Sensoriamento remoto Imagens de satelite Soja Remote sensing Coupled model Soy yield Forecast Satellite images |
title_short |
Spectral model for soybean yield estimate using MODIS/EVI data |
title_full |
Spectral model for soybean yield estimate using MODIS/EVI data |
title_fullStr |
Spectral model for soybean yield estimate using MODIS/EVI data |
title_full_unstemmed |
Spectral model for soybean yield estimate using MODIS/EVI data |
title_sort |
Spectral model for soybean yield estimate using MODIS/EVI data |
author |
Gusso, Aníbal |
author_facet |
Gusso, Aníbal Ducati, Jorge Ricardo Veronez, Maurício Roberto Arvor, Damien Silveira Junior, Luiz Gonzaga da |
author_role |
author |
author2 |
Ducati, Jorge Ricardo Veronez, Maurício Roberto Arvor, Damien Silveira Junior, Luiz Gonzaga da |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Gusso, Aníbal Ducati, Jorge Ricardo Veronez, Maurício Roberto Arvor, Damien Silveira Junior, Luiz Gonzaga da |
dc.subject.por.fl_str_mv |
Sensoriamento remoto Imagens de satelite Soja |
topic |
Sensoriamento remoto Imagens de satelite Soja Remote sensing Coupled model Soy yield Forecast Satellite images |
dc.subject.eng.fl_str_mv |
Remote sensing Coupled model Soy yield Forecast Satellite images |
description |
Attaining reliable and timely agricultural estimates is very important everywhere, and in Brazil, due to its characteristics, this is especially true. In this study, estimations of crop production were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images. The objective was to evaluate the coupled model (CM) performance of crop area and crop yield estimates based solely on MODIS/EVI as input data in Rio Grande do Sul State, which is characterized by high variability in seasonal soybean yields, due to different crop development conditions. The resulting production estimates from CM were compared to official agricultural statistics of Brazilian Institute of Geography and Statistics (IBGE) and the National Company of Food Supply (CONAB) at different levels from 2000/2001 to 2010/2011 crop years. Results obtained with CM indicate that its application is able to generate timely production estimates for soybean both at municipality and local levels. Validation estimates with CM at State level obtained R2 = 0.95. Combining all cropping years at municipality level, estimates were highly correlated to official statistics from IBGE, with R2 = 0.91 and RMSD = 10,840 tons. Spatially interpolated comparisons of yield maps obtained from the CM estimates and IBGE data also showed visual similarity in their spatial distribution. Local level comparisons were performed and presented R2 = 0.95. Implications of this work point out that time-series analysis of production estimates are able to provide anticipated spatial information prior to the soybean harvest. |
publishDate |
2013 |
dc.date.issued.fl_str_mv |
2013 |
dc.date.accessioned.fl_str_mv |
2014-03-26T01:51:20Z |
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http://hdl.handle.net/10183/89727 |
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por |
language |
por |
dc.relation.ispartof.pt_BR.fl_str_mv |
International journal of geosciences. Irvine, CA. Vol. 4, n. 9 (Nov. 2013), p. 1233-1241 |
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openAccess |
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