Dinâmica espectro-temporal da soja e do feijão por meio de sensoriamento remoto terrestre

Detalhes bibliográficos
Autor(a) principal: Prudente, Victor Hugo Rohden
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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spelling 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
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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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