Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do UNIOESTE |
Texto Completo: | http://tede.unioeste.br/handle/tede/3062 |
Resumo: | The spatio-temporal dynamics of agricultural crops can be monitored through Vegetation Indices (VI) on multiple dates. The use of IV in a given period of crop development or throughout its cycle, has generated good relations with agronomic parameters. There are several IV, the NDVI (Normalized Difference Vegetation Index) being one of the most used. NDVI correlates with some agronomic variables such as plant height, leaf area index (LAI), dry matter, chlorophyll index (CI), soil cover degree, plant height and photosynthetically active intercepted radiation (PAIR). Hence, the objective of this work is to compare and intercalibrate NDVI spectral-temporal profiles obtained by different terrestrial remote Sensors, and to use these profiles to estimate biophysical parameters (LAI, CI, PAIR, and Plant Height) for soybean and bean, in addition to estimating and studying soybean yield through models with spectral-temporal data obtained by different terrestrial remote sensors. The ground sensors used are the GreenSeeker 505 Handheld active sensor and the passive hyperspectral FieldSpec4 Standard-Res model. The NDVI values of the passive (NDVI FS) and active (NDVI GS) sensors presented high correlation (soybean rs = 0.90 and bean rs = 0.93) and the linear models respond well to an intercalibration considering the entire phenological cycle of soybean (R² = 0.83, RMSE = 0.0161 e dr = 0.85) and beans (R² = 0.92, RMSE = 0.0038 e dr = 0.89). The saturation of the NDVI values at the survey dates that are located during the vegetative peak of the crops and the presence of adverse climatic events decreased the precision of the models in certain periods of the phenological cycle of the crops. The variables LAI and Height for both crops and CI for the soybean crop obtained better results when estimated by the values of NDVI GS. PAIR for both crops and CI for bean obtained better adjustments considering the models using NDVI FS values. For the variable productivity, there was no significant correlation with the NDVI GS and NDVI FS. However, it presented relations with the accumulation of reflectance observed in the RED and NIR bands for both sensors as a result of different collection dates. The best relations of productivity were with the accumulation of reflectance values of the spectroradiometer bands on DAS76 and DAS71 dates. |
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Mercante, Eriveltohttp://lattes.cnpq.br/4061800207647478Johann, Jerry Adrianihttp://lattes.cnpq.br/3499704308301708Maggi, Marcio Furlanhttp://lattes.cnpq.br/8677221771738301Souza, Carlos Henrique Wachholz dehttp://lattes.cnpq.br/2804633646710952http://lattes.cnpq.br/6154929133513022Prudente, Victor Hugo Rohden2017-09-18T12:59:07Z2017-02-09PRUDENTE, Victor Hugo Rohden. Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre. 2017. 122 f. Dissertação (Mestrado - Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Estadual do Oeste do Paraná, Cascavel, 2017.http://tede.unioeste.br/handle/tede/3062The spatio-temporal dynamics of agricultural crops can be monitored through Vegetation Indices (VI) on multiple dates. The use of IV in a given period of crop development or throughout its cycle, has generated good relations with agronomic parameters. There are several IV, the NDVI (Normalized Difference Vegetation Index) being one of the most used. NDVI correlates with some agronomic variables such as plant height, leaf area index (LAI), dry matter, chlorophyll index (CI), soil cover degree, plant height and photosynthetically active intercepted radiation (PAIR). Hence, the objective of this work is to compare and intercalibrate NDVI spectral-temporal profiles obtained by different terrestrial remote Sensors, and to use these profiles to estimate biophysical parameters (LAI, CI, PAIR, and Plant Height) for soybean and bean, in addition to estimating and studying soybean yield through models with spectral-temporal data obtained by different terrestrial remote sensors. The ground sensors used are the GreenSeeker 505 Handheld active sensor and the passive hyperspectral FieldSpec4 Standard-Res model. The NDVI values of the passive (NDVI FS) and active (NDVI GS) sensors presented high correlation (soybean rs = 0.90 and bean rs = 0.93) and the linear models respond well to an intercalibration considering the entire phenological cycle of soybean (R² = 0.83, RMSE = 0.0161 e dr = 0.85) and beans (R² = 0.92, RMSE = 0.0038 e dr = 0.89). The saturation of the NDVI values at the survey dates that are located during the vegetative peak of the crops and the presence of adverse climatic events decreased the precision of the models in certain periods of the phenological cycle of the crops. The variables LAI and Height for both crops and CI for the soybean crop obtained better results when estimated by the values of NDVI GS. PAIR for both crops and CI for bean obtained better adjustments considering the models using NDVI FS values. For the variable productivity, there was no significant correlation with the NDVI GS and NDVI FS. However, it presented relations with the accumulation of reflectance observed in the RED and NIR bands for both sensors as a result of different collection dates. The best relations of productivity were with the accumulation of reflectance values of the spectroradiometer bands on DAS76 and DAS71 dates.A dinâmica espaço-temporal das culturas agrícolas pode ser monitorada por meio de Índices de Vegetação (IV) em múltiplas datas. A utilização do IV, em um determinado período do desenvolvimento das culturas, ou, ainda, em todo o seu ciclo, possui boas relações com parâmetros agronômicos. Há diversos IVs, sendo o NDVI (Normalized Difference Vegetation Index) um dos mais utilizados. O NDVI possui relação com algumas variáveis agronômicas como altura de planta, Índice de Área Foliar (IAF), matéria seca, índice de clorofila (IC), grau de cobertura do solo, altura de planta e radiação fotossinteticamente ativa interceptada (RFAI). Neste sentido, o objetivo deste trabalho foi comparar perfis espectro-temporais NDVI obtidos por diferentes sensores remotos terrestres, e utilizar esses perfis para estimar parâmetros biofísicos (IAF, IC, RFAI e altura de planta) para a soja e o feijão, além de estimar/estudar a produtividade da soja por meio de modelos com dados espectro-temporais obtidos por diferentes sensores remotos terrestres. Utilizou-se o sensor ativo GreenSeeker 505 Handheld e o sensor passivo hiperespectral FieldSpec4 modelo Standard-Res. Os valores de NDVI dos sensores passivos (NDVI FS) e ativos (NDVI GS) apresentaram alta correlação (soja rs = 0,90 e feijão rs = 0,93), e os modelos lineares respondem bem a um ajuste, ao se considerar todo o ciclo fenológico da soja (R² = 0,83, RMSE = 0,0161 e dr = 0,85) e feijão (R² = 0,92, RMSE = 0,0038 e dr = 0,89). A saturação dos valores de NDVIs nas datas de levantamento que se situam durante o pico vegetativo das culturas e a presença de eventos climáticos adverso diminuíram a precisão dos modelos em determinados períodos do ciclo fenológico das culturas. As variáveis IAF e altura para a soja e o feijão e IC para a soja obtiveram melhores resultados ao ser estimadas por meio dos valores de NDVI GS. RFAI para ambas as culturas e IC para o feijão obtiveram melhores ajustes por meio dos modelos que se utilizavam de valores de NDVI FS. Para a produtividade, não houve correlação significativa com os NDVI GS e NDVI FS. Entretanto, apresentou relações com o acúmulo de refletância observados nas bandas RED e NIR para ambos os sensores em diferentes datas de coleta. As melhores relações da produtividade foram com o acúmulo de refletância das bandas do espectroradiômetro nas datas DAS76 e DAS71.Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2017-09-18T12:59:07Z No. of bitstreams: 1 Victor_Prudente2017.pdf: 2943373 bytes, checksum: 9bc7b35805d7987e01d85665f9ba8802 (MD5)Made available in DSpace on 2017-09-18T12:59:07Z (GMT). No. of bitstreams: 1 Victor_Prudente2017.pdf: 2943373 bytes, checksum: 9bc7b35805d7987e01d85665f9ba8802 (MD5) Previous issue date: 2017-02-09Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqapplication/pdfpor6588633818200016417500Universidade Estadual do Oeste do ParanáCascavelPrograma de Pós-Graduação em Engenharia AgrícolaUNIOESTEBrasilCentro de Ciências Exatas e TecnológicasEstimativasÍndices de vegetaçãoParâmetros biofísicosEstimatesVegetation indexesBiophysical parametersCIENCIAS AGRARIAS::ENGENHARIA AGRICOLADinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestreSpectrum-temporal dynamics of soybean and bean using terrestrial remote sensinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-534769245041605212960060060060022143744428683820159185445721588761555-2555911436985713659info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações do UNIOESTEinstname:Universidade Estadual do Oeste do Paraná (UNIOESTE)instacron:UNIOESTEORIGINALVictor_Prudente2017.pdfVictor_Prudente2017.pdfapplication/pdf2943373http://tede.unioeste.br:8080/tede/bitstream/tede/3062/2/Victor_Prudente2017.pdf9bc7b35805d7987e01d85665f9ba8802MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://tede.unioeste.br:8080/tede/bitstream/tede/3062/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede/30622017-09-18 09:59:07.963oai:tede.unioeste.br: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Biblioteca Digital de Teses e Dissertaçõeshttp://tede.unioeste.br/PUBhttp://tede.unioeste.br/oai/requestbiblioteca.repositorio@unioeste.bropendoar:2017-09-18T12:59:07Biblioteca Digital de Teses e Dissertações do UNIOESTE - Universidade Estadual do Oeste do Paraná (UNIOESTE)false |
dc.title.por.fl_str_mv |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
dc.title.alternative.eng.fl_str_mv |
Spectrum-temporal dynamics of soybean and bean using terrestrial remote sensing |
title |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
spellingShingle |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre Prudente, Victor Hugo Rohden Estimativas Índices de vegetação Parâmetros biofísicos Estimates Vegetation indexes Biophysical parameters CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
title_short |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
title_full |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
title_fullStr |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
title_full_unstemmed |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
title_sort |
Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre |
author |
Prudente, Victor Hugo Rohden |
author_facet |
Prudente, Victor Hugo Rohden |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Mercante, Erivelto |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/4061800207647478 |
dc.contributor.advisor-co1.fl_str_mv |
Johann, Jerry Adriani |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/3499704308301708 |
dc.contributor.referee1.fl_str_mv |
Maggi, Marcio Furlan |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/8677221771738301 |
dc.contributor.referee2.fl_str_mv |
Souza, Carlos Henrique Wachholz de |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/2804633646710952 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6154929133513022 |
dc.contributor.author.fl_str_mv |
Prudente, Victor Hugo Rohden |
contributor_str_mv |
Mercante, Erivelto Johann, Jerry Adriani Maggi, Marcio Furlan Souza, Carlos Henrique Wachholz de |
dc.subject.por.fl_str_mv |
Estimativas Índices de vegetação Parâmetros biofísicos |
topic |
Estimativas Índices de vegetação Parâmetros biofísicos Estimates Vegetation indexes Biophysical parameters CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
dc.subject.eng.fl_str_mv |
Estimates Vegetation indexes Biophysical parameters |
dc.subject.cnpq.fl_str_mv |
CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
description |
The spatio-temporal dynamics of agricultural crops can be monitored through Vegetation Indices (VI) on multiple dates. The use of IV in a given period of crop development or throughout its cycle, has generated good relations with agronomic parameters. There are several IV, the NDVI (Normalized Difference Vegetation Index) being one of the most used. NDVI correlates with some agronomic variables such as plant height, leaf area index (LAI), dry matter, chlorophyll index (CI), soil cover degree, plant height and photosynthetically active intercepted radiation (PAIR). Hence, the objective of this work is to compare and intercalibrate NDVI spectral-temporal profiles obtained by different terrestrial remote Sensors, and to use these profiles to estimate biophysical parameters (LAI, CI, PAIR, and Plant Height) for soybean and bean, in addition to estimating and studying soybean yield through models with spectral-temporal data obtained by different terrestrial remote sensors. The ground sensors used are the GreenSeeker 505 Handheld active sensor and the passive hyperspectral FieldSpec4 Standard-Res model. The NDVI values of the passive (NDVI FS) and active (NDVI GS) sensors presented high correlation (soybean rs = 0.90 and bean rs = 0.93) and the linear models respond well to an intercalibration considering the entire phenological cycle of soybean (R² = 0.83, RMSE = 0.0161 e dr = 0.85) and beans (R² = 0.92, RMSE = 0.0038 e dr = 0.89). The saturation of the NDVI values at the survey dates that are located during the vegetative peak of the crops and the presence of adverse climatic events decreased the precision of the models in certain periods of the phenological cycle of the crops. The variables LAI and Height for both crops and CI for the soybean crop obtained better results when estimated by the values of NDVI GS. PAIR for both crops and CI for bean obtained better adjustments considering the models using NDVI FS values. For the variable productivity, there was no significant correlation with the NDVI GS and NDVI FS. However, it presented relations with the accumulation of reflectance observed in the RED and NIR bands for both sensors as a result of different collection dates. The best relations of productivity were with the accumulation of reflectance values of the spectroradiometer bands on DAS76 and DAS71 dates. |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-09-18T12:59:07Z |
dc.date.issued.fl_str_mv |
2017-02-09 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
PRUDENTE, Victor Hugo Rohden. Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre. 2017. 122 f. Dissertação (Mestrado - Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Estadual do Oeste do Paraná, Cascavel, 2017. |
dc.identifier.uri.fl_str_mv |
http://tede.unioeste.br/handle/tede/3062 |
identifier_str_mv |
PRUDENTE, Victor Hugo Rohden. Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre. 2017. 122 f. Dissertação (Mestrado - Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Estadual do Oeste do Paraná, Cascavel, 2017. |
url |
http://tede.unioeste.br/handle/tede/3062 |
dc.language.iso.fl_str_mv |
por |
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por |
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600 600 600 600 |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual do Oeste do Paraná Cascavel |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Agrícola |
dc.publisher.initials.fl_str_mv |
UNIOESTE |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Centro de Ciências Exatas e Tecnológicas |
publisher.none.fl_str_mv |
Universidade Estadual do Oeste do Paraná Cascavel |
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