Papers by Fabio Marcelo Breunig
<strong>Title</strong>: Unmanned Aerial Vehicle (UAV) data acquired over a subtropica... more <strong>Title</strong>: 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 <strong>Keywords</strong> Images, Drone, UAV, Forest, UFSM, Remote Sensing, GIS. <strong>Data description:</strong> The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) 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): <strong>Parameters</strong> 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, breunig@ufsm.br 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 [...]
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Ra'e Ga, Apr 22, 2023
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Revista Brasileira de Geografia Física, Dec 31, 2021
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Acta Iguazu, 2018
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Revista Brasileira de Ciências Agrárias (Agrária), Sep 27, 2017
Knowledge of aboveground biomass stock in Seasonal Deciduous Forests is imperative for the implem... more Knowledge of aboveground biomass stock in Seasonal Deciduous Forests is imperative for the implementation of mechanisms to reduce emissions from deforestation, forest degradation, and land reclamation. The present study analyzed the vertical distribution of aboveground biomasses in a Seasonal Deciduous Forest in Rio Grande do Sul state, Brazil. Seven 12 x 12 m plots were established, and all trees inside the plots were weighed directly in the field. Subplots of 5 x 5 m and 1 x 1 m were marked within the main plots to quantify the remaining vegetation. Average dry aboveground biomass was 316.5 Mg ha-1, trees with diameter at breast height (DBH) greater than 10 cm accounting for over 89% of this biomass. Therefore, biomass determination of large trees deserves special attention, since they represent a large part of the biomass of this forest ecosystem. Biomass of plants taller than 1.3 m and with diameter at breast height < 5 cm was 6.9 Mg ha-1, and that of plants lower than 1.3 m was 1.5 Mg ha-1. Average litter mass was 15.6 Mg ha-1. Trees of large diameters must be analyzed very carefully for quantify the biomass and carbon in the forests, because few individuals might represent a large part of the biomass of a forest ecosystem.
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International Journal of Remote Sensing, Sep 17, 2015
We investigated the relationships between 11 phenological metrics, topographic shade, and anomalo... more We investigated the relationships between 11 phenological metrics, topographic shade, and anomalous temperature patterns detected using wavelet analysis in seasonal deciduous forests of south Brazil. To obtain the metrics, we applied the TIMESAT algorithm to the enhanced vegetation index (EVI) from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra. MODIS acquires data from the study area under a large seasonal amplitude in the solar zenith angle (SZA). We evaluated the effect of topography on phenological metrics by correlating the metrics with shaded relief values. To analyse the inter-annual phenological metric variations with anomalous and regular temperature patterns, we calculated standard anomalies for each metric. Finally, we established relationships between the metrics and the minimum, maximum, and mean temperatures from growing seasons that spanned over 10 seasonal cycles between 2002 and 2012. The correlation results with shaded relief showed that the left (LD) and right derivative (RD), small integral (SInt), seasonal amplitude (SA), base level (BL), and maximum VI value (MV) were sensitive to topographic effects. The seasonal cycles with the highest temperatures in the growing season (2006/2007 and 2009/2010) exhibited a delay at the end of the cycle and a higher interval of duration and productivity, which was indicated by the positive standard anomalies for end of season (EOS), length of season (LOS), large integral (LInt), and SInt. We observed a different result for the lowest temperature cycle (2003/2004). The means for these metrics in anomalous seasons differed significantly from the metrics of other regular cycles at the 0.05 significance level using paired t-tests. Statistically significant correlations were observed between the metrics and minimum and mean temperature values of the 10 seasonal cycles.
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Dec 1, 2016
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Science of The Total Environment, 2017
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Knowledge of aboveground biomass stock in Seasonal Deciduous Forests is imperative for the implem... more Knowledge of aboveground biomass stock in Seasonal Deciduous Forests is imperative for the implementation of mechanisms to reduce emissions from deforestation, forest degradation, and land reclamation. The present study analyzed the vertical distribution of aboveground biomasses in a Seasonal Deciduous Forest in Rio Grande do Sul state, Brazil. Seven 12 x 12 m plots were established, and all trees inside the plots were weighed directly in the field. Subplots of 5 x 5 m and 1 x 1 m were marked within the main plots to quantify the remaining vegetation. Average dry aboveground biomass was 316.5 Mg ha-1, trees with diameter at breast height (DBH) greater than 10 cm accounting for over 89% of this biomass. Therefore, biomass determination of large trees deserves special attention, since they represent a large part of the biomass of this forest ecosystem. Biomass of plants taller than 1.3 m and with diameter at breast height < 5 cm was 6.9 Mg ha-1, and that of plants lower than 1.3 m ...
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Journal of Applied Remote Sensing, 2019
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Ciência Florestal, 2022
Considerando a importância das florestas na retenção das águas oriundas da precipitação pluviomét... more Considerando a importância das florestas na retenção das águas oriundas da precipitação pluviométrica e a sua função estratégica na recarga de aquíferos, este estudo teve por objetivo estimar a recarga direta e natural do aquífero raso da zona de alteração dos basaltos da Formação Serra Geral, subjacente à Floresta Estacional Decidual nativa, bioma de Mata Atlântica. Para estimar a recarga do aquífero, foi aplicado o método Water Table Fluctuation (WTF), com base na análise de séries temporais do nível freático e da precipitação, coletadas durante o período de 50 dias (de janeiro a março) no Parque Estadual do Turvo - PET (RS). Para a análise sistemática da variação do nível de água subterrânea (N.A.), foram coletados dados sub-horários com medidores de pressão automáticos (CTD), em três piezômetros localizados no PET. Em simultâneo (com igual periodicidade), foram coletados dados de precipitação pluviométrica no interior do PET, com uma estação experimental. A recarga média, direta...
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Title: Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM cam... more Title: 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 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 <em>Drone</em>) 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): 20191029 Time of day (BRT = -3) 12:00 h UAV – Drone - Camera Phantom 4 Fly high (meters above ground) 200 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 ∞ 587 photos Along track coverage 85% Cross-track coverage 80% Fly planning software Drone Deploy For more information contact: Fábio Marcelo Breunig, breunig@ufsm.br 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. Figure 2. The capture of an orthomosaic in the processing workflow of the X3 camera. The lowest quality was applied. Figure 3. The capture of a DEM in the processing [...]
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Remote Sensing Applications: Society and Environment, Aug 1, 2020
Abstract Remote sensing estimates of cover-crop aboveground biomass (AGB) have been used to delin... more Abstract Remote sensing estimates of cover-crop aboveground biomass (AGB) have been used to delineate management zones for smallholder farming in southern Brazil. In this study, we investigated the spatial resolution influence on the AGB estimates of rye, calculated from regression relationships with the Normalized Difference Vegetation Index (NDVI), and on the subsequent delineation of management zones using the Management Zone Analyst (MZA) software. Data acquired by an Unmanned Aerial Vehicle (UAV) Parrot Sequoia camera (0.20 m spatial resolution) in Brazil were compared with observations from the PlanetScope (PS) satellite constellation (3 m) and the Operational Land Imager (OLI)/Landsat-8 (30 m). A three-endmember mixture model (green vegetation, soil, and shadow) was applied to surface reflectance data of these instruments for evaluating the cover-crop development at two dates in August 2017. Because of the differences in the technical specifications of the sensors, we resampled the UAV dataset into four levels of spatial resolution (1, 3, 10, and 30 m). Using the UAV map (0.20 m) as a reference, we obtained confusion matrices for the original and resampled data. The results showed that the increasing amounts of rye AGB from the beginning to the end of August promoted significant changes in surface reflectance and in soil-green vegetation fractions calculated at variable spatial resolution. The performance of the regression models to estimate cover-crop AGB was approximately similar in the transition from the sub-metric (0.20 m) to the metric (3 m) spatial resolutions, or from the UAV camera to the PS data. For all datasets, the MZA detected two management zones with zone 2 having higher cover-crop AGB than zone 1. When compared to the UAV management zone map (reference), the PS map had a moderate-to-substantial agreement, while the OLI/Landsat-8 map had a fair-to-moderate concordance. Substantial agreements with the reference map were observed at simulated 1 m and 3 m data, as indicated by Kappa coefficients of 0.73 and 0.63 and overall accuracies of 86.40% and 81.40%, respectively. We conclude that the 3 m spatial resolution data of the PS comprise an alternative to delineate management zones for smallholder farming in southern Brazil when compared to the very-high spatial resolution observations of the UAV cameras.
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Geo UERJ, Dec 30, 2017
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Giscience & Remote Sensing, Sep 24, 2019
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Biofix Scientific Journal, Apr 11, 2023
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Ra'e Ga, Apr 22, 2023
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Revista Brasileira de Geografia Física, Jul 19, 2022
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Papers by Fabio Marcelo Breunig