2,012 research outputs found
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 1, 2019, Rio Grande do Sul, Brazil
No full textTitle:
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 1, 2019, Rio Grande do Sul, Brazil
Keywords
Images, Drone, UAV, Forest, UFSM, Remote Sensing, GIS.
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) covering a forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Please, see the PDF file.
Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20191101
Time of day (BRT = -3)
13:00 h
UAV – Drone - Camera
Phantom 4
Fly high (meters above ground)
250 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High-speed wind
Approximate data acquisition duration
30 minutes
Total of photographs acquired
Sensor 1/2.3” CMOS
Effective pixels:12.4 M
Lens FOV 94° 20 mm (35 mm format equivalent) f/2.8 focus at ∞
301 photos
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Drone Deploy
For more information contact: Fábio Marcelo Breunig, [email protected]
An example of the mosaic and DEM is showed below (Figure 2 e Figura 3), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.
Please, see the PDF file.
Figure 2. The capture of an orthomosaic in the processing workflow of X3 camera. The lowest quality was applied.
Please, see the PDF file.
Figure 3. The capture of a DEM in the processing workflow of X3 camera. The lowest quality was applied.
References to the main project/publications:
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat, and Sentinel-2 images to precision silviculture and agriculture in a subtropical region. Project. National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Acknowledgments:
This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grant 23830.388.22048.19092016).
Other considerations
PS. A pdf file is also attached with this description.
Declaration of Competing Interest
The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Fabio Marcelo Breunig, Eduardo Rieder, & Renato Souza Santos. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 22, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4559718
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 11, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4558044
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 5, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4558265
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4557790
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at February 18, 2021, Rio Grande do Sul, Brazil [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4557192
Breunig, Fábio Marcelo (2020, October 20). Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen, on October 20, 2020, in Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4354331
Breunig, Fábio Marcelo (2017, July 11). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 11, 2017, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4328340
Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 7, 2017, in Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943
Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
Breunig, Fábio Marcelo (2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
Breunig, Fábio Marcelo, Rafaelo Balbinot, Rafael Vendruscolo, and Renato Beppler Spohr, ‘Situação Ambiental Do Campus Da UFSM de Frederico Westphalen, RS’, in Anais XVI Simpósio Brasileiro de Sensoriamento Remoto - SBSR, ed. by Instituto Nacional De Pesquisas Espaciais - INPE (Foz do Iguaçu - PR, Brazil: INPE, 2013), pp. 7241–48
Bertani, Gabriel, Fabio Marcelo Breunig, and Renato Beppler Sphor, ‘Análise de crescimento da mancha urbana do município de Frederico Westphalen, RS-Brasil através de imagens Landsat 5 TM’, Revista Geografar, 7 (2012), 68–83
Rex, Franciel Eduardo, Pâmela Suélen Käfer, Fábio Marcelo Breunig, and Renato Beppler Spohr Renato Souza Santos, ‘CLASSIFICAÇÃO SUPERVISIONADA DE COPAS DE ÁRVORES EM IMAGEM DE ALTA RESOLUÇÃO ESPACIAL’, BIOFIX Scientific Journal, 3 (2018), 216–23
Eduardo Rieder, Renato Souza Santos, & Fabio Marcelo Breunig. (2021, February 26). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 2, 2019, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4560622
Sestari, Geovane (2019): RPAS orthomosaic over a remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil. PANGAEA, https://doi.org/10.1594/PANGAEA.910114
ORCID
Eduardo Rieder: https://orcid.org/0000-0003-3572-4941
Fábio Marcelo Breunig: https://orcid.org/0000-0002-0405-960
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 11, 2020, Rio Grande do Sul, Brazil
No full textTitle:
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) covering a forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20201105
Time of day (BRT = -3)
13:00 h a.m.
UAV – Drone - Camera
Matrice 100 (Sequoia Parrot – Multispectral and RGB)
Fly high (meters above ground)
250 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High speed wind
Approximate data acquisition duration
30 minutes
Total of photographs acquired
Sequoia Multi 1835+1686; Sequoia RGB 87 9
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Pix4D Capture (₢)
For more information contact: Fábio Marcelo Breunig, [email protected]
An example of the mosaic is showed below (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.
Figure 2. The capture of an orthomosaic and and de DEM in the processing workflow of X3 camera. Lowest quality was applied.
References to the main project/publications:
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat, and Sentinel-2 images to precision silviculture and agriculture in a subtropical region. Project. National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Acknowledgments:
This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grant 23830.388.22048.19092016).
Other considerations
PS. A pdf file is also attached with this description
Declaration of Competing Interest
The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4557790
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at February 18, 2021, Rio Grande do Sul, Brazil [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4557192
Breunig, Fábio Marcelo (2020, October 20). Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen, on October 20, 2020, in Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4354331
Breunig, Fábio Marcelo (2017, July 11). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 11, 2017, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4328340
Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 7, 2017, in Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943
Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
Breunig, Fábio Marcelo (2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
Breunig, Fábio Marcelo, Rafaelo Balbinot, Rafael Vendruscolo, and Renato Beppler Spohr, ‘Situação Ambiental Do Campus Da UFSM de Frederico Westphalen, RS’, in Anais XVI Simpósio Brasileiro de Sensoriamento Remoto - SBSR, ed. by Instituto Nacional De Pesquisas Espaciais - INPE (Foz do Iguaçu - PR, Brazil: INPE, 2013), pp. 7241–48
Bertani, Gabriel, Fabio Marcelo Breunig, and Renato Beppler Sphor, ‘Análise de crescimento da mancha urbana do município de Frederico Westphalen, RS-Brasil através de imagens Landsat 5 TM’, Revista Geografar, 7 (2012), 68–83
Sestari, Geovane (2019): RPAS orthomosaic over a remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil. PANGAEA, https://doi.org/10.1594/PANGAEA.910114
ORCID
Fábio Marcelo Breunig: https://orcid.org/0000-0002-0405-9603
Eduardo Rieder: https://orcid.org/0000-0003-3572-494
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 22, 2020, Rio Grande do Sul, Brazil
No full textTitle:
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 22, 2020, Rio Grande do Sul, Brazil
Keywords
Images, Drone, UAV, Forest, UFSM, Remote Sensing, GIS.
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) covering a forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (Alvares et al., 2013). The rainfall is well distributed throughout the year.
See the PDF file
Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20201022
Time of day (BRT = -3)
14:00 h a.m.
UAV – Drone - Camera
Matrice 100 (Sequoia Parrot – Multispectral and RGB)
Fly high (meters above ground)
250 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High-speed wind
Approximate data acquisition duration
30 minutes
Total of photographs acquired
X3 162; Sequoia Multi 1100+1672+1176; Sequoia RGB 277+420+296
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Pix4D Capture (₢)
For more information contact: Fábio Marcelo Breunig, [email protected]
An example of the mosaic and DEM is showed below (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.
See the PDF file
Figure 2. The capture of an orthomosaic and de DEM in the processing workflow of the X3 camera. The lowest quality was applied.
References to the main project/publications:
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat, and Sentinel-2 images to precision silviculture and agriculture in a subtropical region. Project. National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. The Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Acknowledgments:
This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do the Rio Grande do Sul (Grant 23830.388.22048.19092016).
Other considerations
PS. A pdf file is also attached with this description
Declaration of Competing Interest
The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 11, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4558044
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 5, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4558265
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4557790
Fabio Marcelo Breunig, & Eduardo Rieder. (2021). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on February 18, 2021, Rio Grande do Sul, Brazil [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4557192
Breunig, Fábio Marcelo (2020, October 20). Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen, on October 20, 2020, in the Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4354331
Breunig, Fábio Marcelo (2017, July 11). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 11, 2017, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4328340
Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 7, 2017, in the Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943
Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
Breunig, Fábio Marcelo (2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
Breunig, Fábio Marcelo, Rafaelo Balbinot, Rafael Vendruscolo, and Renato Beppler Spohr, ‘Situação Ambiental Do Campus Da UFSM de Frederico Westphalen, RS’, in Anais XVI Simpósio Brasileiro de Sensoriamento Remoto - SBSR, ed. by Instituto Nacional De Pesquisas Espaciais - INPE (Foz do Iguaçu - PR, Brazil: INPE, 2013), pp. 7241–48
Bertani, Gabriel, Fabio Marcelo Breunig, and Renato Beppler Sphor, ‘Análise de crescimento da mancha urbana do município de Frederico Westphalen, RS-Brasil através de imagens Landsat 5 TM’, Revista Geografar, 7 (2012), 68–83
Sestari, Geovane (2019): RPAS orthomosaic over a remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil. PANGAEA, https://doi.org/10.1594/PANGAEA.910114
ORCID
Fábio Marcelo Breunig: https://orcid.org/0000-0002-0405-9603
Eduardo Rieder: https://orcid.org/0000-0003-3572-4941
Renato Souza Santos: https://orcid.org/0000-0002-0984-630
Use of saline solution during the practice of endotracheal aspiration by different professional categories in a public hospital in Southern Brazil
No full textIntrodução: As UTIs oferecem atendimento multidisciplinar ao paciente crítico. Uma prática comum aos profissionais de saúde é a aspiração endotraqueal. Ainda não é consenso a utilização de soro fisiológico durante a aspiração. Objetivo: O objetivo desse estudo foi descrever o uso do soro fisiológico pelos técnicos de enfermagem, enfermeiros e fisioterapeutas durante a aspiração, em um hospital público no município de Porto Alegre. Materiais e Métodos: Trata-se de um estudo transversal, observacional e prospectivo, aprovado pelo Comitê de Ética e Pesquisa do Grupo Hospital Conceição, Porto Alegre, RS sob nº CEP 1742499. No presente estudo avaliamos a prática através da aplicação do questionário desenvolvida por Leddy R. e Wilkinson J. M. 2015, no qual foi adaptado, técnicos de enfermagem, enfermeiros e fisioterapeutas que trabalham na emergência e UTI de dois grandes hospitais públicos. Os dados foram analisados no programa estatístico SPSS 22.0 (SPSS Inc., EUA) para Windows. Os dados quantitativos foram apresentados em média +- desvio padrão e comparados entre grupos por uma análise de variância de uma via seguido de pós teste de Bonferroni. Dados categóricos foram apresentados em frequência absoluta (frequência relativa) e comparados entre grupos por um teste de Qui quadrado. Um nível de significância de p<0,05 foi adotado para todas as análises. Resultados: o estudo avaliou 83 profissionais da área da saúde, 27 técnicos de enfermagem, 28 enfermeiros e 28 fisioterapeutas. Houve diferença estatisticamente significativa nos seguintes critérios: aspiração como rotina, tipo de aspiração mais comum, existência de protocolo de higiene oral e ciência da taxa de PAV, utilização do solução fisiológica antes da aspiração, motivos de uso do soro fisiológico e sobre a possibilidade de aspirar sem soro fisiológico e em relação aos conhecimentos que se baseiam para o uso da instilação salina. Conclusão: Os dados demonstraram que os profissionais realizam a aspiração endotraqueal de forma rotineira, sendo que os enfermeiros e técnicos baseiam-se na prática clínica e os fisioterapeutas em evidências científicas. Os principais critérios para o uso de solução salina durante a aspiração endotraqueal em pacientes em VM entre enfermeiros e fisioterapeutas foi por observarem obstrução do tubo orotraqueal e para os técnicos de enfermagem foi para mobilizar secreções.Introduction: ICUs offer multidisciplinary care to critically ill patients. A common practice for health professionals is endotracheal aspiration. There is still no consensus on the use of saline solution during aspiration. Objective: The aim of this study was to describe the use of saline solution by nursing technicians, nurses and physiotherapists during aspiration, in a public hospital in the city of Porto Alegre. Materials and Methods: This is a cross-sectional, observational and prospective study, approved by the Ethics and Research Committee of the Hospital Conceição Group, Porto Alegre, RS under No. CEP 1742499. In the present study, we evaluated the practice through the application of a questionnaire developed by Leddy R. and Wilkinson JM 2015, in which nursing technicians, nurses and physiotherapists working in emergency and ICU of two large public hospitals were adapted. Data were analyzed using the SPSS 22.0 statistical program (SPSS Inc., USA) for Windows. Quantitative data were presented as mean +- standard deviation and compared between groups by one-way analysis of variance followed by Bonferroni post test. Categorical data were presented as absolute frequency (relative frequency) and compared between groups by a Chi-square test. A significance level of p<0.05 was adopted for all analyses. Results: the study evaluated 83 health professionals, 27 nursing technicians, 28 nurses and 28 physiotherapists. There was a statistically significant difference in the following criteria: aspiration as a routine, most common type of aspiration, existence of an oral hygiene protocol and awareness of the VAP rate, use of saline solution before aspiration, reasons for using saline solution and on the possibility of aspirating without saline solution and in relation to the knowledge that is based on the use of saline instillation. Conclusion: The data showed that professionals routinely perform endotracheal suctioning, with nurses and technicians relying on clinical practice and physiotherapists on scientific evidence. The main criteria for the use of saline solution during endotracheal aspiration in MV patients among nurses and physiotherapists was for observing obstruction of the orotracheal tube and for nursing technicians it was to mobilize secretions
Unmanned Aerial Vehicle (UAV) data acquired over a secondary subtropical forest area of the UFSM campus Frederico Westphalen, on June 14, 2021, Rio Grande do Sul, Brazil
No full textTitle:
Unmanned Aerial Vehicle (UAV) data acquired over a secondary subtropical forest area of the UFSM campus Frederico Westphalen, at June 14, 2021, Rio Grande do Sul, Brazil
Data description:
The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also Drone) covering a forest area of the Federal University of Santa Maria – UFSM in the municipality of Frederico Westphalen, in the Rio Grande do Sul, Brazil (Figure 1). The climate of the region is subtropical (Cfa in the Köppen-Geiger classification) with an average annual temperature of 18 °C and annual precipitation of 1919 mm (Alvares et al., 2013). The rainfall is well distributed throughout the year.
Figure 1. Location of the site of data acquisition.
UAV and camera settings for the acquisition (Specifications Table):
Parameters
Specification/value
Date (YYYYMMDD):
20210614
Time of day (BRT = -3)
14:40 h a.m.
UAV – Drone - Camera
Matrice 100 (X3)
Fly high (meters above ground)
80 m
View angle
90° automatic mode.
Sky conditions
( x ) Clear sky
( ) Low cloud coverage (some clouds)
( ) Completely cloudy
Wind condition
( x ) no wind
( ) Low speed
( ) High speed wind
Approximate data acquisition duration
12 minutes
Total of photographs acquired
X3 - 252
Across track coverage
80%
Cross-track coverage
80%
Fly planning software
Pix4D Capture (₢)
For more information contact: Fábio Marcelo Breunig, [email protected]
An example of the mosaic and DEM are showed below (Figure 2 and Figrue 3, respectively), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.
Figure 2. The capture of an orthomosaic of X3 camera.
Figure 3. The capture of an DEM
References to the main project/publications:
Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: .
Breunig, Fabio Marcelo. Integration of multiscale remote sensing data in the precision agriculture and silviculture (in Portuguese: Integração de dados multiescala de sensoriamento remoto na agricultura e silvicultura de precisão). Project. National Council for Scientific and Technological Development (CNPq). Grant 113769/2018-0
Breunig, Fabio Marcelo. Combination of UAV, PlanetScope, Landsat and Sentinel-2 images to precision silviculture and agriculture in a subtropical region (in Portuguese: Combinação de imagens de VANT, PlanetScope, Landsat e Sentinal-2 para a silvicultura e agricultura de precisão em uma região subtropical). Project of the National Council for Scientific and Technological Development (CNPq). Grant 305084/2020-8
Acknowledgments:
This work was supported by the National Council for Scientific and Technological Development (CNPq) (Grants 113769/2018-0, 312081/2013-8, 478085/2013-3 and, 305084/2020-8) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Grant 23830.388.22048.19092016).
Other considerations
PS. A pdf file is also attached with this description
Declaration of Competing Interest
The author declares that he has no competing interests or personal relationships that have or could be perceived to have influenced the work reported in this report.
References associated:
Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, Meteorologische Zeitschrift, 22 (2013), 711–28
Breunig, Fábio Marcelo (2021): Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen on December 13, 2017 in Rio Grande do Sul, Brazil. PANGAEA, PDF. https://doi.pangaea.de/10.1594/PANGAEA.930004
Eduardo Rieder, Geovani Sestari, & Fabio Marcelo Breunig. (2021, February 27). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 29, 2019, in the Rio Grande do Sul State, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4565584
Eduardo Rieder, & Fabio Marcelo Breunig. (2021, February 26). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 1, 2019, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4564677
Eduardo Rieder, Renato Souza Santos, & Fabio Marcelo Breunig. (2021, February 26). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 2, 2019, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4560622
Fabio Marcelo Breunig, Eduardo Rieder, & Renato Souza Santos. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on October 22, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4559718
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 24). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 5, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4558265
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on November 11, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4558044
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on December 23, 2020, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4557790
Fabio Marcelo Breunig, & Eduardo Rieder. (2021, February 23). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on February 18, 2021, Rio Grande do Sul, Brazil [Data set]. Zenodo. PDF. http://doi.org/10.5281/zenodo.4557192
Breunig, Fábio Marcelo (2020, October 20). Unmanned Aerial Vehicle (UAV) data acquired over an experimental area of the UFSM campus Frederico Westphalen, on October 20, 2020, in the Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4354331
Breunig, Fábio Marcelo (2017, July 11). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 11, 2017, Rio Grande do Sul, Brazil. Zenodo. PDF. http://doi.org/10.5281/zenodo.4328340
Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, on July 7, 2017, in the Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943
Breunig, Fábio Marcelo(2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897548
Breunig, Fábio Marcelo(2019): UAV derived orthomosaic over the “prainha” in the municipality of Iraí, Rio Grande do Sul, Brazil. Universidade Federal de Santa Maria, PANGAEA, https://doi.org/10.1594/PANGAEA.897909
Sestari, Geovane (2019): RPAS orthomosaic over a remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil. PANGAEA, https://doi.org/10.1594/PANGAEA.91011
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