Estimating invasive grasses heights with images from a remotely piloted aircraft in Brazilian Cerrado: accuracy of Global Navigation Satellite System from Phantom 4
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
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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oai:periodicos.ufrn.br:article/20423 |
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Revista de Geociências do Nordeste |
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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 |
format |
article |
status_str |
publishedVersion |
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) |
instacron_str |
UFRN |
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 |
_version_ |
1797052929074528256 |