Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4

Detalhes bibliográficos
Autor(a) principal: Pessi, Dhonatan Diego
Data de Publicação: 2021
Outros Autores: Vieira José, Jefferson, Mioto, Camila Leonardo, Diodato, Marco Antonio, Grigio, Alfredo Marcelo, Paranhos Filho, Antonio Conceição, Matos da Silva, Normandes
Tipo de documento: Artigo
Idioma: por
eng
Título da fonte: Revista de Geociências do Nordeste
Texto Completo: https://periodicos.ufrn.br/revistadoregne/article/view/20423
Resumo: The purpose of this study was to estimate the height of invasive plants from UAV images using the GNSS integrated into the UAV and to evaluate the accuracy of the GNSS. DSM and DTM elevation models were produced from images collected by remotely piloted aircraft (RPA). The production of CHIS occurred through the subtraction of the DSM and the DTM. In order to assess the accuracy of the CHIS+GNSS model, the CHIS+RTK model was generated as the observed variable. The comparison between the models took place in two sample areas represented by typical vegetation of Cerrado and Brachiaria grass. The statistical tests adopted were: Spearman correlation, RMSE, MAE and Wilcoxon test. The visual interpretation of the selected images showed that the CHIS+GNSS model presented errors in the identification of the ground cover represented by invasive grasses when compared to the CHIS+RTK model, being less accurate in the classification of the canopy heights of the invasive species. Statistical tests indicated that the CHIS+GNSS model showed significant differences in the identification of invasive species, with greater height error (0.24 cm) in the sample area. From these results it can be seen that the CHIS+RTK model is more assertive in detecting ground cover composed by exotic grasses than the CHIS+GNSS model.
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spelling Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4The purpose of this study was to estimate the height of invasive plants from UAV images using the GNSS integrated into the UAV and to evaluate the accuracy of the GNSS. DSM and DTM elevation models were produced from images collected by remotely piloted aircraft (RPA). The production of CHIS occurred through the subtraction of the DSM and the DTM. In order to assess the accuracy of the CHIS+GNSS model, the CHIS+RTK model was generated as the observed variable. The comparison between the models took place in two sample areas represented by typical vegetation of Cerrado and Brachiaria grass. The statistical tests adopted were: Spearman correlation, RMSE, MAE and Wilcoxon test. The visual interpretation of the selected images showed that the CHIS+GNSS model presented errors in the identification of the ground cover represented by invasive grasses when compared to the CHIS+RTK model, being less accurate in the classification of the canopy heights of the invasive species. Statistical tests indicated that the CHIS+GNSS model showed significant differences in the identification of invasive species, with greater height error (0.24 cm) in the sample area. From these results it can be seen that the CHIS+RTK model is more assertive in detecting ground cover composed by exotic grasses than the CHIS+GNSS model.O objetivo desse capítulo foi comparar a precisão dos resultados do modelo CHIS+GPS/GLONASS do capítulo 1, sem correção de acurácia posicional com RTK (Real-time Kinematic), com os resultados do modelo CHIS corrigidos. Houve a produção dos modelos de elevação MDS e MDT a partir das imagens coletadas em campo com aeronave remotamente pilotada (RPA) conhecida popularmente como drone, que foram processadas para geração de ortomosaico corrigido com pontos de controle, obtidos por RTK. A produção do CHIS ocorreu por meio de um modelo digital fruto da extração do Modelo Digital de Superfície (MDS) e do Modelo Digital do Terreno (MDT). Para aferir a precisão do modelo CHIS+GPS/GLONASS foi gerado o modelo CHIS+RTK como variável observada. A comparação entre os modelos se deu em duas áreas amostrais representadas por vegetação típica de cerrado e capim Braquiária. Os testes estatísticos adotados foram: coeficientes de correlação de Spearman (SCC), erro quadrático médio da raiz da altura de dossel (RMSEz), erro absoluto médio da altura de dossel (MAEz) e teste de Wilcoxon. A interpretação visual das imagens classificadas demonstrou que o modelo CHIS+GPS/GLONASS apresentou falhas na identificação da cobertura do solo representada por gramíneas invasoras, quando comparado ao modelo CHIS+RTK, sendo menos preciso na classificação das alturas de dossel das espécies invasoras. Os testes estatísticos indicaram que o modelo CHIS+GPS/GLONASS demonstrou diferenças significativas na identificação de espécies invasoras, com maior erro de altura (0.24 cm) na área amostral. A partir desses resultados verifica-se que o modelo CHIS+RTK é mais assertivo na detecção de cobertura do solo composta por gramíneas exóticas que o modelo CHIS+GOS/GLONASS.Universidade Federal do Rio Grande do Norte2021-09-16info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://periodicos.ufrn.br/revistadoregne/article/view/2042310.21680/2447-3359.2021v7n2ID20423Revista de Geociências do Nordeste; v. 7 n. 2 (2021); 140-1522447-335910.21680/2447-3359.2021v7n2reponame:Revista de Geociências do Nordesteinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNporenghttps://periodicos.ufrn.br/revistadoregne/article/view/20423/14728https://periodicos.ufrn.br/revistadoregne/article/view/20423/14729Copyright (c) 2021 Revista de Geociências do Nordesteinfo:eu-repo/semantics/openAccessPessi, Dhonatan DiegoVieira José, JeffersonMioto, Camila Leonardo Diodato, Marco AntonioGrigio, Alfredo MarceloParanhos Filho, Antonio ConceiçãoMatos da Silva, Normandes 2021-11-18T22:41:40Zoai:periodicos.ufrn.br:article/20423Revistahttps://periodicos.ufrn.br/revistadoregne/indexPUBhttps://periodicos.ufrn.br/revistadoregne/oairegneufrn@gmail.com || periodicos@bczm.ufrn.br2447-33592447-3359opendoar:2021-11-18T22:41:40Revista de Geociências do Nordeste - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.none.fl_str_mv Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
title Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
spellingShingle Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
Pessi, Dhonatan Diego
title_short Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
title_full Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
title_fullStr Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
title_full_unstemmed Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
title_sort Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
author Pessi, Dhonatan Diego
author_facet Pessi, Dhonatan Diego
Vieira José, Jefferson
Mioto, Camila Leonardo
Diodato, Marco Antonio
Grigio, Alfredo Marcelo
Paranhos Filho, Antonio Conceição
Matos da Silva, Normandes
author_role author
author2 Vieira José, Jefferson
Mioto, Camila Leonardo
Diodato, Marco Antonio
Grigio, Alfredo Marcelo
Paranhos Filho, Antonio Conceição
Matos da Silva, Normandes
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Pessi, Dhonatan Diego
Vieira José, Jefferson
Mioto, Camila Leonardo
Diodato, Marco Antonio
Grigio, Alfredo Marcelo
Paranhos Filho, Antonio Conceição
Matos da Silva, Normandes
description The purpose of this study was to estimate the height of invasive plants from UAV images using the GNSS integrated into the UAV and to evaluate the accuracy of the GNSS. DSM and DTM elevation models were produced from images collected by remotely piloted aircraft (RPA). The production of CHIS occurred through the subtraction of the DSM and the DTM. In order to assess the accuracy of the CHIS+GNSS model, the CHIS+RTK model was generated as the observed variable. The comparison between the models took place in two sample areas represented by typical vegetation of Cerrado and Brachiaria grass. The statistical tests adopted were: Spearman correlation, RMSE, MAE and Wilcoxon test. The visual interpretation of the selected images showed that the CHIS+GNSS model presented errors in the identification of the ground cover represented by invasive grasses when compared to the CHIS+RTK model, being less accurate in the classification of the canopy heights of the invasive species. Statistical tests indicated that the CHIS+GNSS model showed significant differences in the identification of invasive species, with greater height error (0.24 cm) in the sample area. From these results it can be seen that the CHIS+RTK model is more assertive in detecting ground cover composed by exotic grasses than the CHIS+GNSS model.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-16
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv https://periodicos.ufrn.br/revistadoregne/article/view/20423
10.21680/2447-3359.2021v7n2ID20423
url https://periodicos.ufrn.br/revistadoregne/article/view/20423
identifier_str_mv 10.21680/2447-3359.2021v7n2ID20423
dc.language.iso.fl_str_mv por
eng
language por
eng
dc.relation.none.fl_str_mv https://periodicos.ufrn.br/revistadoregne/article/view/20423/14728
https://periodicos.ufrn.br/revistadoregne/article/view/20423/14729
dc.rights.driver.fl_str_mv Copyright (c) 2021 Revista de Geociências do Nordeste
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Revista de Geociências do Nordeste
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio Grande do Norte
publisher.none.fl_str_mv Universidade Federal do Rio Grande do Norte
dc.source.none.fl_str_mv Revista de Geociências do Nordeste; v. 7 n. 2 (2021); 140-152
2447-3359
10.21680/2447-3359.2021v7n2
reponame:Revista de Geociências do Nordeste
instname:Universidade Federal do Rio Grande do Norte (UFRN)
instacron:UFRN
instname_str Universidade Federal do Rio Grande do Norte (UFRN)
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institution UFRN
reponame_str Revista de Geociências do Nordeste
collection Revista de Geociências do Nordeste
repository.name.fl_str_mv Revista de Geociências do Nordeste - Universidade Federal do Rio Grande do Norte (UFRN)
repository.mail.fl_str_mv regneufrn@gmail.com || periodicos@bczm.ufrn.br
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