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401 results for “UAVs”
Orthophoto & DEM (MNE) issues d'images drone, UAV, Ermitage, Saint-Gilles, Réunion - 20230722 - 02_1
<p>"Ce jeu de données présente les résultats des traitements photogrammétriques d'images de drone DJI Mavic 2 Pro UAV acquises sur le site de Ermitage, Saint-Gilles, Réunion à la date suivante : 20230722. <br>Les traitements ont été réalisés avec le logiciel OpenDroneMap à partir des images brutes fournies dans la première version de ce DOI. <br>Les vols ont été réalisés dans le but de créer des modèles numériques d'élévations pour cartographier la rugosité récifale du lagon jusqu'à la pente externe. Les données seront utilisées dans le cadre du projet TELEMAC. <br><br><br>Le paramétrage du logiciel OpenDroneMap est partagé pour permettre la reproductibilité ou l'amélioration des traitements proposés:<br>[ <br>{ <br>'name': 'orthophoto-resolution', <br>'value': 1 <br>}, <br>{ <br>'name': 'auto-boundary', <br>'value': true <br>}, <br>{ <br>'name': 'dem-resolution', <br>'value': '2.0' <br>}, <br>{ <br>'name': 'dsm', <br>'value': true <br>} <br>] <br><br><strong>Le dépôt est composé des éléments suivants:</strong> <br>- 00_: Planche d'aperçu des images <br>- DCIM.zip: Images brutes issues du drone <br>- GPS.zip: Geopackage contenant l'emprise du survol ainsi que la géolocalisation des images accompagnées de leurs miniatures dans la table d'attribut en base64. RINEX et LLH issus d'un Emlid Reach M2 synchronisé avec la LED de navigation (événement envoyé dans le log du récepteur GNSS lors du déclenchement d'une image). Le but est de pouvoir réaliser un PPK (similaire au RTK en post-traitement) et ainsi disposer d'une position centrimétrique sur chaque image. <br>- METADATA.zip: Métadonnées au format ISO19115, Rapports avec miniatures des images de drone (dossier tb) et statistiques de vols. <br>- PROCESSED_DATA.zip: Orthophoto, DEM, nuages de points, ... <br><br><strong>Arborescence d'origine:</strong> <br>│ └─ 20230722_REU-ermitage_UAV-02_1 <br>│-------- └─ DCIM <br>│-------- └─ GPS <br>│-------- └─ METADATA <br>│---------------- └─ tb <br>│-------- └─ PROCESSED_DATA <br><br><strong>Informations de survol:</strong> <br>- Camera model and parameters: <br>Make: Hasselblad <br>Model: L1D-20c <br>Width: 5472 <br>Height: 3648 <br>Focal: 28 <br>WhiteBalance: Manual <br>ExposureMode: Auto Exposure <br>ColoSpace: sRGB <br>EV: -0.7 <br>MeteringMode: CenterWeightedAverage <br>Camera Pitch: -70.00 <br><br>- Survey informations: <br>No Images: 277 <br>Median height: 70 meters <br>Survey area: 5.87 hectares <br>Survey from: 2023:07:22 10:33:06 to: 2023:07:22 10:48:40 <br>"</p>
Orthophoto & DEM (MNE) issues d'images drone, UAV, Ermitage, Saint-Gilles, Réunion - 20230801 - 02_1
<p>"Ce jeu de données présente les résultats des traitements photogrammétriques d'images de drone DJI Mavic 2 Pro UAV acquises sur le site de Ermitage, Saint-Gilles, Réunion à la date suivante : 20230801. <br>Les traitements ont été réalisés avec le logiciel OpenDroneMap à partir des images brutes fournies dans la première version de ce DOI. <br>Les vols ont été réalisés dans le but de créer des modèles numériques d'élévations pour cartographier la rugosité récifale du lagon jusqu'à la pente externe. Les données seront utilisées dans le cadre du projet TELEMAC. <br><br><br>Le paramétrage du logiciel OpenDroneMap est partagé pour permettre la reproductibilité ou l'amélioration des traitements proposés:<br>[ <br>{ <br>'name': 'orthophoto-resolution', <br>'value': 1 <br>}, <br>{ <br>'name': 'auto-boundary', <br>'value': true <br>}, <br>{ <br>'name': 'dem-resolution', <br>'value': '2.0' <br>}, <br>{ <br>'name': 'dsm', <br>'value': true <br>} <br>] <br><br><strong>Le dépôt est composé des éléments suivants:</strong> <br>- 00_: Planche d'aperçu des images <br>- DCIM.zip: Images brutes issues du drone <br>- GPS.zip: Geopackage contenant l'emprise du survol ainsi que la géolocalisation des images accompagnées de leurs miniatures dans la table d'attribut en base64. RINEX et LLH issus d'un Emlid Reach M2 synchronisé avec la LED de navigation (événement envoyé dans le log du récepteur GNSS lors du déclenchement d'une image). Le but est de pouvoir réaliser un PPK (similaire au RTK en post-traitement) et ainsi disposer d'une position centrimétrique sur chaque image. <br>- METADATA.zip: Métadonnées au format ISO19115, Rapports avec miniatures des images de drone (dossier tb) et statistiques de vols. <br>- PROCESSED_DATA.zip: Orthophoto, DEM, nuages de points, ... <br><br><strong>Arborescence d'origine:</strong> <br>│ └─ 20230802_REU-ermitage_UAV-02_1 <br>│-------- └─ DCIM <br>│-------- └─ GPS <br>│-------- └─ METADATA <br>│---------------- └─ tb <br>│-------- └─ PROCESSED_DATA <br><br><strong>Informations de survol:</strong> <br>- Camera model and parameters: <br>Make: Hasselblad <br>Model: L1D-20c <br>Width: 5472 <br>Height: 3648 <br>Focal: 28 <br>WhiteBalance: Manual <br>ExposureMode: Auto Exposure <br>ColoSpace: sRGB <br>EV: -0.7 <br>MeteringMode: CenterWeightedAverage <br>Camera Pitch: -80.00 <br><br>- Survey informations: <br>No Images: 352 <br>Median height: 30 meters <br>Survey area: 3.25 hectares <br>Survey from: 2023:08:01 06:59:36 to: 2023:08:01 07:16:47 <br>"</p>
Orthophoto & DEM (MNE) issues d'images drone, UAV, Ermitage, Saint-Gilles, Réunion - 20230524 - 02_3
"Ce jeu de données présente les résultats des traitements photogrammétriques d'images de drone DJI Mavic 2 Pro UAV acquises sur le site de Ermitage, Saint-Gilles, Réunion à la date suivante : 20230524. <br>Les traitements ont été réalisés avec le logiciel OpenDroneMap à partir des images brutes fournies dans la première version de ce DOI. <br>Les vols ont été réalisés dans le but de créer des modèles numériques d'élévations pour cartographier la rugosité récifale du lagon jusqu'à la pente externe. Les données seront utilisées dans le cadre du projet TELEMAC. <br> <br><br>Le paramétrage du logiciel OpenDroneMap est partagé pour permettre la reproductibilité ou l'amélioration des traitements proposés:<br> [ <br> { <br> 'name': 'orthophoto-resolution', <br> 'value': 1 <br> }, <br> { <br> 'name': 'auto-boundary', <br> 'value': true <br> }, <br> { <br> 'name': 'dem-resolution', <br> 'value': '2.0' <br> }, <br> { <br> 'name': 'dsm', <br> 'value': true <br> } <br> ] <br> <br><b>Le dépôt est composé des éléments suivants:</b> <br> - 00_: Planche d'aperçu des images <br> - DCIM.zip: Images brutes issues du drone <br> - GPS.zip: Geopackage contenant l'emprise du survol ainsi que la géolocalisation des images accompagnées de leurs miniatures dans la table d'attribut en base64. RINEX et LLH issus d'un Emlid Reach M2 synchronisé avec la LED de navigation (événement envoyé dans le log du récepteur GNSS lors du déclenchement d'une image). Le but est de pouvoir réaliser un PPK (similaire au RTK en post-traitement) et ainsi disposer d'une position centrimétrique sur chaque image. <br> - METADATA.zip: Métadonnées au format ISO19115, Rapports avec miniatures des images de drone (dossier tb) et statistiques de vols. <br> - PROCESSED_DATA.zip: Orthophoto, DEM, nuages de points, ... <br> <br><b>Arborescence d'origine:</b> <br>│ └─ 20230524_REU-ermitage_UAV-02_3 <br>│-------- └─ DCIM <br>│-------- └─ GPS <br>│---------------- └─ base_2023_05_24_pascal <br>│---------------- └─ reach_2023_05_24_drone <br>│------------------------ └─ reachsylvai_raw_202305240249_RINEX_3_03 <br>│------------------------ └─ reachsylvai_raw_202305240330_RINEX_3_03 <br>│---------------- └─ reach_2023_05_24_rover <br>│-------- └─ METADATA <br>│---------------- └─ tb <br>│-------- └─ PROCESSED_DATA <br> <br><b>Informations de survol:</b> <br>- Camera model and parameters: <br> Make: Hasselblad <br> Model: L1D-20c <br> Width: 5472 <br> Height: 3648 <br> Focal: 28 <br> WhiteBalance: Manual <br> ExposureMode: Auto Exposure <br> ColoSpace: sRGB <br> EV: -0.7 <br> MeteringMode: CenterWeightedAverage <br> Camera Pitch: -70.00 <br> <br>- Survey informations: <br> No Images: 336 <br> Median height: 70 meters <br> Survey area: 7.35 hectares <br> Survey from: 2023:05:24 09:33:18 to: 2023:05:24 09:49:53 <br>"
Orthophoto & DEM (MNE) issues d'images drone, UAV, Ermitage, Saint-Gilles, Réunion - 20230524 - 02_2
"Ce jeu de données présente les résultats des traitements photogrammétriques d'images de drone DJI Mavic 2 Pro UAV acquises sur le site de Ermitage, Saint-Gilles, Réunion à la date suivante : 20230524. <br>Les traitements ont été réalisés avec le logiciel OpenDroneMap à partir des images brutes fournies dans la première version de ce DOI. <br>Les vols ont été réalisés dans le but de créer des modèles numériques d'élévations pour cartographier la rugosité récifale du lagon jusqu'à la pente externe. Les données seront utilisées dans le cadre du projet TELEMAC. <br> <br><br>Le paramétrage du logiciel OpenDroneMap est partagé pour permettre la reproductibilité ou l'amélioration des traitements proposés:<br> [ <br> { <br> 'name': 'orthophoto-resolution', <br> 'value': 1 <br> }, <br> { <br> 'name': 'auto-boundary', <br> 'value': true <br> }, <br> { <br> 'name': 'dem-resolution', <br> 'value': '2.0' <br> }, <br> { <br> 'name': 'dsm', <br> 'value': true <br> } <br> ] <br> <br><b>Le dépôt est composé des éléments suivants:</b> <br> - 00_: Planche d'aperçu des images <br> - DCIM.zip: Images brutes issues du drone <br> - GPS.zip: Geopackage contenant l'emprise du survol ainsi que la géolocalisation des images accompagnées de leurs miniatures dans la table d'attribut en base64. RINEX et LLH issus d'un Emlid Reach M2 synchronisé avec la LED de navigation (événement envoyé dans le log du récepteur GNSS lors du déclenchement d'une image). Le but est de pouvoir réaliser un PPK (similaire au RTK en post-traitement) et ainsi disposer d'une position centrimétrique sur chaque image. <br> - METADATA.zip: Métadonnées au format ISO19115, Rapports avec miniatures des images de drone (dossier tb) et statistiques de vols. <br> - PROCESSED_DATA.zip: Orthophoto, DEM, nuages de points, ... <br> <br><b>Arborescence d'origine:</b> <br>│ └─ 20230524_REU-ermitage_UAV-02_2 <br>│-------- └─ DCIM <br>│-------- └─ GPS <br>│---------------- └─ base_2023_05_24_pascal <br>│---------------- └─ reach_2023_05_24_drone <br>│------------------------ └─ reachsylvai_raw_202305240249_RINEX_3_03 <br>│------------------------ └─ reachsylvai_raw_202305240330_RINEX_3_03 <br>│---------------- └─ reach_2023_05_24_rover <br>│-------- └─ METADATA <br>│---------------- └─ tb <br>│-------- └─ PROCESSED_DATA <br> <br><b>Informations de survol:</b> <br>- Camera model and parameters: <br> Make: Hasselblad <br> Model: L1D-20c <br> Width: 5472 <br> Height: 3648 <br> Focal: 28 <br> WhiteBalance: Manual <br> ExposureMode: Auto Exposure <br> ColoSpace: sRGB <br> EV: -0.7 <br> MeteringMode: CenterWeightedAverage <br> Camera Pitch: -80.00 <br> <br>- Survey informations: <br> No Images: 341 <br> Median height: 70 meters <br> Survey area: 162474.07 hectares <br> Survey from: 2023:05:24 09:05:25 to: 2023:05:24 09:26:24 <br>"
ADM1_UAV
<p>This dataset contains five sets (each set from a different spectra) of images taken by an UAV equipped with a downward looking multispectral camera (Parrot Sequoia), in one flight. The region in which the UAV flyed was Arroio do Meio, a city from Rio Grande do Sul, Brazil. In addition to the sets of images, there are also a folder with five satellite images from Arroio do Meio, a README file, a .kml and a .DAT file.</p> <p>This dataset was used in the experiments of: </p> <p>R. Westhauser, M. Mantelli, D. Pittol, R. Maffei, E. Prestes, M. Kolberg, "λ-BRIEF: a new binary descriptor for multispectral images applied to the global localization of UAVs."</p>
UFRGS_UAV
<p>This dataset contains five sets (each set from a different spectra) of images taken by an UAV equipped with a downward looking multispectral camera (Parrot Sequoia), in one flight. The region in which the UAV flyed was Porto Alegre (more specifically, Federal University of Rio Grande do Sul, Campus do Vale), a city from Rio Grande do Sul, Brazil. In addition to the sets of images, there are also a folder with twelve satellite images from Porto Alegre, a README file, a .kml and a .DAT file.</p> <p>This dataset was used in the experiments of: </p> <p>R. Westhauser, M. Mantelli, D. Pittol, R. Maffei, E. Prestes, M. Kolberg, "λ-BRIEF: a new binary descriptor for multispectral images applied to the global localization of UAVs."</p>
ADM3_UAV
<p>This dataset contains five sets (each set from a different spectra) of images taken by an UAV equipped with a downward looking multispectral camera (Parrot Sequoia), in one flight. The region in which the UAV flyed was Arroio do Meio, a city from Rio Grande do Sul, Brazil. In addition to the sets of images, there are also a folder with five satellite images from Arroio do Meio, a README file, a .kml and a .DAT file.</p> <p>This dataset was used in the experiments of: </p> <p>R. Westhauser, M. Mantelli, D. Pittol, R. Maffei, E. Prestes, M. Kolberg, "λ-BRIEF: a new binary descriptor for multispectral images applied to the global localization of UAVs."</p>
Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at July 11, 2017, Rio Grande do Sul, Brazil
<p>Title:</p> <p>Unmanned Aerial Vehicle (UAV) data acquired over a subtropical forest area of the UFSM campus Frederico Westphalen, at July 11, 2017, Rio Grande do Sul, Brazil</p> <p> </p> <p>Data description:</p> <p> </p> <p>The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) covering an 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 (<a href="https://www.sciencedirect.com/science/article/pii/S0303243419309481#bib0015">Alvares et al., 2013</a>). The rainfall is well distributed throughout the year.</p> <p> </p> <p>Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.</p> <p> </p> <p>UAV and camera settings for the acquisition (Specifications Table):</p> <p> </p> <p><strong>Parameters</strong></p> <p><strong>Specification/value</strong></p> <p>Date (YYYYMMDD):</p> <p>20170711</p> <p>Time of day (BRT = -3)</p> <p>10h a.m.</p> <p>UAV – Drone - Camera</p> <p>Phantom 4.</p> <p>Fly high (meters above ground)</p> <p>250 m</p> <p>View angle</p> <p>90° automatic mode.</p> <p>Sky conditions</p> <p>( x ) Clear sky</p> <p>( ) Low cloud coverage (some clouds)</p> <p>( ) Completely cloudy</p> <p>Wind condition</p> <p>( x ) no wind</p> <p>( ) Low speed</p> <p>( ) High speed wind</p> <p>Approximate data acquisition duration</p> <p>16 minutes</p> <p>Total of photographs acquired</p> <p>143</p> <p>Across track coverage</p> <p>80%</p> <p>Cross-track coverage</p> <p>80%</p> <p>Fly planning software</p> <p>Pix4D Capture</p> <p> </p> <p>For more information contact: Fábio Marcelo Breunig, <a href="mailto:breunig@ufsm.br">breunig@ufsm.br</a></p> <p>An example of the mosaic is showed (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.</p> <p> </p> <p>Figure 2. The capture of an orthomosaic and processing workflow</p> <p> </p> <p> </p> <p>References to the main project/publications:</p> <p> </p> <p>Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: <https://www.researchgate.net/project/CONESAT-Monitoring-the-CONESUL-using-remote-sensing-data>.</p> <p>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</p> <p>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</p> <p> </p> <p>Acknowledgments:</p> <p>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).</p> <p> </p> <p>Other considerations</p> <p> </p> <p>PS. A pdf file is also attached with this description</p> <p> </p> <p>Declaration of Competing Interest</p> <p>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.</p> <p> </p> <p>References associated:</p> <p>Breunig, Fábio Marcelo (2017, July 7). Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil. Zenodo. http://doi.org/10.5281/zenodo.4327943</p> <p>Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, <em>Meteorologische Zeitschrift</em>, 22 (2013), 711–28 <https://doi.org/10.1127/0941-2948/2013/0507></p> <p>Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897548</p> <p>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,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897909</p> <p>Sestari, Geovane (2019): RPAS orthomosaic over the remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil.<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.910114</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil
<p>Title:Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil</p> <p> </p> <p>Data description:</p> <p> </p> <p>The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) covering an 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 (<a href="https://www.sciencedirect.com/science/article/pii/S0303243419309481#bib0015">Alvares et al., 2013</a>). The rainfall is well distributed throughout the year.</p> <p> </p> <p>Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.</p> <p> </p> <p>UAV and camera settings for the acquisition (Specifications Table):</p> <p> </p> <p><strong>Parameters</strong></p> <p><strong>Specification/value</strong></p> <p>Date (YYYYMMDD):</p> <p>20170707</p> <p>Time of day (BRT = -3)</p> <p>14h a.m.</p> <p>UAV – Drone - Camera</p> <p>Phantom 4.</p> <p>Fly high (meters above ground)</p> <p>250 m</p> <p>View angle</p> <p>90° automatic mode.</p> <p>Sky conditions</p> <p>( x ) Clear sky</p> <p>( ) Low cloud coverage (some clouds)</p> <p>( ) Completely cloudy</p> <p>Wind condition</p> <p>( x ) no wind</p> <p>( ) Low speed</p> <p>( ) High-speed wind</p> <p>Approximate data acquisition duration</p> <p>16 minutes</p> <p>Total of photographs acquired</p> <p>143</p> <p>Across track coverage</p> <p>80%</p> <p>Cross-track coverage</p> <p>80%</p> <p>Fly planning software</p> <p>Pix4D Capture</p> <p> </p> <p>For more information contact: Fábio Marcelo Breunig, <a href="mailto:breunig@ufsm.br">breunig@ufsm.br</a></p> <p>An example of the mosaic is showed (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.</p> <p> </p> <p>Figure 2. The capture of an orthomosaic and processing workflow</p> <p> </p> <p> </p> <p>References to the main project/publications:</p> <p> </p> <p>Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: <https://www.researchgate.net/project/CONESAT-Monitoring-the-CONESUL-using-remote-sensing-data>.</p> <p>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</p> <p>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</p> <p> </p> <p>Acknowledgments:</p> <p>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).</p> <p> </p> <p>Other considerations</p> <p> </p> <p>PS. A pdf file is also attached with this description</p> <p> </p> <p>Declaration of Competing Interest</p> <p>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.</p> <p> </p> <p>References associated:</p> <p> </p> <p>Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, <em>Meteorologische Zeitschrift</em>, 22 (2013), 711–28 <https://doi.org/10.1127/0941-2948/2013/0507></p> <p>Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897548</p> <p>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,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897909</p> <p>Sestari, Geovane (2019): RPAS orthomosaic over the remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil.<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.910114</p> <p>Title:</p> <p> </p> <p>Unmanned Aerial Vehicle (UAV) data acquired over an subtropical forest area of the UFSM campus Frederico Westphalen, at July 7, 2017, Rio Grande do Sul, Brazil</p> <p> </p> <p>Data description:</p> <p> </p> <p>The data were acquired from an aerial survey conducted with an Unmanned Aerial Vehicle (UAV, also <em>Drone</em>) covering an 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 (<a href="https://www.sciencedirect.com/science/article/pii/S0303243419309481#bib0015">Alvares et al., 2013</a>). The rainfall is well distributed throughout the year.</p> <p> </p> <p>Figure 1. Location of the site of data acquisition. Based on Google Earth Pro scenes. The KML and KMZ are appended to the files.</p> <p> </p> <p>UAV and camera settings for the acquisition (Specifications Table):</p> <p> </p> <p><strong>Parameters</strong></p> <p><strong>Specification/value</strong></p> <p>Date (YYYYMMDD):</p> <p>20170707</p> <p>Time of day (BRT = -3)</p> <p>14h a.m.</p> <p>UAV – Drone - Camera</p> <p>Phantom 4.</p> <p>Fly high (meters above ground)</p> <p>250 m</p> <p>View angle</p> <p>90° automatic mode.</p> <p>Sky conditions</p> <p>( x ) Clear sky</p> <p>( ) Low cloud coverage (some clouds)</p> <p>( ) Completely cloudy</p> <p>Wind condition</p> <p>( x ) no wind</p> <p>( ) Low speed</p> <p>( ) High speed wind</p> <p>Approximate data acquisition duration</p> <p>16 minutes</p> <p>Total of photographs acquired</p> <p>143</p> <p>Across track coverage</p> <p>80%</p> <p>Cross-track coverage</p> <p>80%</p> <p>Fly planning software</p> <p>Pix4D Capture</p> <p> </p> <p>For more information contact: Fábio Marcelo Breunig, <a href="mailto:breunig@ufsm.br">breunig@ufsm.br</a></p> <p>An example of the mosaic is showed (Figure 2), referring to a screen capture of Agisoft Metashape (Agisoft LLC, 11 Degtyarniy per., St. Petersburg, Russia, 191144) and, the workflow adopted.</p> <p> </p> <p>Figure 2. The capture of an orthomosaic and processing workflow</p> <p> </p> <p> </p> <p>References to the main project/publications:</p> <p> </p> <p>Breunig, Fabio Marcelo. CONESAT – Monitoring the CONESUL using remote sensing data. Project. Federal University of Santa Maria, Campus of Frederico Westphalen. Brazil. Available at: <https://www.researchgate.net/project/CONESAT-Monitoring-the-CONESUL-using-remote-sensing-data>.</p> <p>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</p> <p>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</p> <p> </p> <p>Acknowledgments:</p> <p>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).</p> <p> </p> <p>Other considerations</p> <p> </p> <p>PS. A pdf file is also attached with this description</p> <p> </p> <p>Declaration of Competing Interest</p> <p>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.</p> <p> </p> <p>References associated:</p> <p> </p> <p>Alvares, Clayton Alcarde, José Luiz Stape, Paulo Cesar Sentelhas, José Leonardo De Moraes Gonçalves, and Gerd Sparovek, ‘Köppen’s Climate Classification Map for Brazil’, <em>Meteorologische Zeitschrift</em>, 22 (2013), 711–28 <https://doi.org/10.1127/0941-2948/2013/0507></p> <p>Breunig, Fábio Marcelo (2019): UAV images acquired over the UFSM campus in Frederico Westphalen, RS, Brazil. Universidade Federal de Santa Maria,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897548</p> <p>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,<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.897909</p> <p>Sestari, Geovane (2019): RPAS orthomosaic over the remnant of rainforest on UFSM/IFFar campus in the municipality of Frederico Westphalen, Rio Grande do Sul, Brazil.<em> PANGAEA</em>, https://doi.org/10.1594/PANGAEA.910114</p>
UAV RGB and TIR images in the Qinghai-Tibet Engineering Corridor
<p>Two permafrost slopes were conducted four flight experiments with UAV-mounted RGB and TIR sensors in 2016 and 2017.</p>
Ortophotos and DSMs UAV
<p>Ortophoto and DSMs from UAV.</p><p> </p><p>(The presented dataset is the result of the multidisciplinary work of the cc-glacier-lab of the Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino.</p><p>The Italian Ministry for Education and Research (MIUR), Dipartimento di Eccellenza, funded this research.)</p>
Vertical profiles of air temperature, relative humidity, wind speed and direction observed using UAV over the Mukhrino peatland in June 2022
<p>Vertical profiles of air temperature and relative humidity were measured using the iMetXQ2 sensor onboard DJI Phantom 4 quad-copter; vertical profiles of wind speed and direction were obtained from the Phantom 4 flight logs as produced by the DJI proprietary algorithm. </p>
EV UAV
<p>Event Videos of Unmanned Aerial Vehicles (UAVs) with RGB camera recording.</p><p>Recordings of Quadcopter drones using a Dynamic Vision Sensor camera with 1280x720p resolution.</p><p> </p><p> </p>
UAV Map of Isimila, Tanzania
<p>UAV-based mapping data set for the Middle Pleistocene archaeological site of Isimila, Tanzania. Includes full-resolution orthomosaic, digital elevation model, flight data, and video data.</p>
mDRONES4rivers-project: UAV-imagery of the project area Nonnenwerth at the Rhine River, Germany
<p>Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. <br> Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. <br> In this dataset, the following UAS data and metadata of the project site ‘Nonnenwerth’ (center coordinates [WGS84]: 50.637541°N, 7.208834°E; area: 8 ha) at the Rhine River in Germany is available for download:<br> • Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW)<br> • RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO)<br> • Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM)<br> • associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model)<br> The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_UAV_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder: <br> • Overview table and metadata of the above-mentioned data (xlsx)<br> • Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models)<br> Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.</p>
mDRONES4rivers-project: UAV-imagery of the project area Emmericher Ward at the Rhine River, Germany
<p>Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. <br> Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. <br> In this dataset, the following UAS data and metadata of the project site ‘Emmericher Ward’ (center coordinates [WGS84]: 50.385264°N, 6.198692°E; area: 53ha) at the Rhine River in Germany is available for download:<br> • Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW)<br> • RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO)<br> • Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM)<br> • associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model)<br> The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_EW_UAV_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder: <br> • Overview table and metadata of the above-mentioned data (xlsx)<br> • Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models)</p> <p><br> Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail. </p>
mDRONES4rivers-project: UAV-imagery of the project area Reitwein at the River Oder, Germany
<p>Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. <br> Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. <br> In this dataset, the following UAS data and metadata of the project site ‘Reitwein’ (center coordinates [WGS84]: 52.500961°N, 14.629186 °E; area: 60 ha) at the River Oder in Germany is available for download:<br> • Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW)<br> • RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO)<br> • Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM)<br> • associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model)<br> The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition and flight altitude, as the data was collected here from two different flight altitudes (e.g. mDRONES4rivers_RW_UAV_2020_03_summer_70m.zip = projectname_projectsite_platform_year_no.season_name.season_flightaltitude.zip). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder: <br> • Overview table and metadata of the above-mentioned data (xlsx)<br> • Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models)</p> <p>Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.</p>
mDRONES4rivers-project: UAV-imagery of the project area Niederwerth at the Rhine River, Germany
<p>Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. <br> Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. <br> In this dataset, the following UAS data and metadata of the project site ‘Niederwerth’ (center coordinates [WGS84]: 50.386326°N, 7.613847°E; area: 27 ha) at the Rhine River in Germany is available for download:<br> • Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW)<br> • RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO)<br> • Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation : PH_DEM)<br> • associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model)<br> The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_2019_01_Winter.zip = projectname_projectsite_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are additionally provided: <br> • Overview table and metadata of the above-mentioned data (xlsx)<br> • Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models)</p> <p><br> Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail. </p>
mDRONES4rivers-project: UAV-imagery of the project area Kuehkopf Knoblochsaue at the Rhine River, Germany
<p>Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. <br> Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. <br> In this dataset, the following UAS data and metadata of the project site ‘Kuehkopf Knoblochsaue’ (center coordinates [WGS84]: 49.830564°N, 8.383341°E; area: 48 ha) at the Rhine River in Germany is available for download:<br> • Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW)<br> • RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO)<br> • Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation : PH_DEM)<br> • associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model)<br> The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_2019_01_Winter.zip = projectname_projectsite_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder: <br> • Overview table and metadata of the above-mentioned data (xlsx)<br> • Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models)<br> Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail. </p>
mDRONES4rivers-project: UAV-imagery of the project area Laubenheim at the Rhine River, Germany
<p>Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. <br> Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. <br> In this dataset, the following UAS data and metadata of the project site ‘Laubenheim’ (center coordinates [WGS84]: 49.960007°N, 8.331229°E; area: 11 ha) at the Rhine River in Germany is available for download:<br> • Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW)<br> • RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO)<br> • Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM)<br> • associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model)<br> The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_UAV_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder: <br> • Overview table and metadata of the above-mentioned data (xlsx)<br> • Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models)<br> Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.