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10 results for “RPAS”
Orthophotos and DSMs derived from RPAS flights over the nature reserve Zwin in Flanders, Belgium
<p><strong>Study area</strong></p> <p>The Zwin is a nature reserve situated along the Belgian North Sea coast, northeast of Knokke, in the province of West-Flanders, Flanders, Belgium. The area is managed by the Flemish Agency for Nature and Forest and consists of a tidal marsh, coastal dunes with <em>Ammophila arenaria</em>, dune grasslands and/or shrub (<em>Hippophae rhamnoides</em>, <em>Salix repens</em>), and a transitional grassland zone that stretches from the inner edge of the coastal dunes into the polders.</p> <p><strong>Data collection</strong></p> <p>Data were collected by the <a href="http://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a> with a fixed wing drone Gatewing X100 in 2014 and 2015 (15 flights). RGB data were acquired using an off-the-shelf Ricoh GR Digital IV camera, with the following image bands: 1: red, 2: green, 3: blue, 4: alpha channel. CIR (color-infrared) data were acquired using a NIR-enabled Ricoh GR Digital IV camera, with the following info bands: 1: NIR, 2: red, 3: green, 4: alpha channel.</p> <p><strong>Data processing</strong></p> <p>The raw data were processed to Digital Surface Models and orthophotos by the <a href="https://vito.be/en">Flemish Institute for Technological Research (VITO)</a> in 2017. Images with coarse GPS coordinates were imported and processed in Agisoft PhotoScan Pro 1.4.x, a structure-from-motion (SfM) based photogrammetry software program. After extraction and matching of tie points, a bundle adjustment leads to a sparse point cloud and a refined set of camera position and orientation values. Ground control points (either artificially installed markers on the terrain, or other photo-identifiable points, measured on the ground with RTK GNSS) were used to further refine the camera calibration and obtain a pixel-level georeferencing accuracy. From there, a point cloud densification and classification into ground and non-ground points was performed, leading to a rasterized digital surface model (DSM) and digital terrain model (DTM). Finally, a true orthomosaic was projected onto the DTM.</p> <p><strong>Coordinate reference system</strong></p> <p>All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>.</p> <p><strong>Files</strong></p> <ul> <li><strong>Raw flight data</strong>: images and logs collected by the drone during flight. These files are zipped per flight, with the date (<code>yyyymmdd</code>) and flight number (<code>x</code>) indicated in the file name (<code>flight_yyyymmdd_Zwin_x.zip</code>).</li> <li><strong>Processed data</strong>: Digital Surface Models (<code>filename_DSM.tif</code>) and orthophotos (<code>filename_Ortho.tif</code>) stitched together from the raw data. The included flights are indicated in the file name (e.g. 6 flights for <code>20150709_Zwin_1-3_20150710_Zwin_1-3_DSM.tif</code>).</li> <li><strong>Ground control points</strong>: fixed ground control points (GCP) were placed on 2014-04-07, coordinates of which are available in <code>GCP_20140407_Zwin_fixed.tsv</code>. These GCPs are visible (but fading over time) in all orthophotos except <code>20151012_Zwin_1-4_Ortho.tif</code> which covers a different area. Additional temporary GCPs were placed on 2014-04-07, 2014-04-10 and 2015-07-09 (visible in orthophotos of those dates), coordinates of which are available in the respective <code>GCP_yyyymmdd_Zwin.tsv</code> file.</li> </ul> <p><strong>Cloud Optimized GeoTIFF</strong></p> <p>The most efficient way to explore the processed data is by loading the <a href="https://www.cogeo.org/">Cloud Optimized GeoTIFFs</a> we created for each processed file. Copy one of the file URLs below and follow e.g. the <a href="https://www.cogeo.org/qgis-tutorial.html">QGIS tutorial</a> to load this type of file.</p> <ul> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20140407_Zwin_1-2_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20140407_Zwin_1-2_Ortho.tif</code> CIR</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20140410_Zwin_1-3_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20140410_Zwin_1-3_Ortho.tif</code> CIR</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150709_Zwin_1-3_20150710_Zwin_1-3_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150709_Zwin_1-3_20150710_Zwin_1-3_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151012_Zwin_1-4_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151012_Zwin_1-4_Ortho.tif</code> RGB</li> </ul> <p>See <a href="https://s3-eu-west-1.amazonaws.com/lw-remote-sensing/index.html">this page</a> for an overview of public INBO RPAS data.</p>
Orthophotos and DSMs/DTM derived from RPAS flights over the nature reserve Landschap De Liereman in Flanders, Belgium
<p><strong>Study area</strong></p> <p>Landschap De Liereman is a nature reserve situated in Oud-Turnhout, in the province of Antwerp, Flanders, Belgium. The area is managed by the nature conservation NGO Natuurpunt and consists of a diverse landscape of wet and dry heathlands, <em>Nardus</em> grasslands on siliceous soils, forests and transition mires, as well as some remaining arable fields and high-intensity agricultural grasslands.</p> <p><strong>Data collection</strong></p> <p>Data were collected by the <a href="http://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a> with a fixed wing drone Gatewing X100 in 2015 (7 flights). RGB data were acquired using an off-the-shelf Ricoh GR Digital IV camera, with the following image bands: 1: red, 2: green, 3: blue, 4: alpha channel.</p> <p>An additional flight campaign was commissioned by INBO and carried out by the <a href="https://vito.be/en">Flemish Institute for Technological Research (VITO)</a> in 2017 with a fixed wing drone SenseFly eBee. Multispectral data were acquired using a Parrot Sequoia camera, with the following image bands: 1: green, 2: red, 3: red edge, 4: NIR, 5: alpha channel. with a Parrot Sequoia camera. Raw data for this flight campaign are not available.</p> <p><strong>Data processing</strong></p> <p>The raw data were processed to Digital Surface Models and orthophotos by VITO in 2017. For the 2017 campaign by VITO, the outputs also include a Digital Terrain Model (DTM). Images with coarse GPS coordinates were imported and processed in Agisoft PhotoScan Pro 1.4.x, a structure-from-motion (SfM) based photogrammetry software program. After extraction and matching of tie points, a bundle adjustment leads to a sparse point cloud and a refined set of camera position and orientation values. From there, a point cloud densification and classification into ground and non-ground points was performed, leading to a rasterized digital surface model (DSM) and digital terrain model (DTM). Finally, a true orthomosaic was projected onto the DTM.</p> <p><strong>Coordinate reference system</strong></p> <p>All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>.</p> <p><strong>Files</strong></p> <ul> <li><strong>Raw flight data</strong>: images and logs collected by the drone during flight. These files are zipped per flight, with the date (<code>yyyymmdd</code>) and flight number (<code>x</code>) indicated in the file name (<code>flight_yyyymmdd_Liereman_x.zip</code>). Raw data for the eBee flights are not available.</li> <li><strong>Processed data</strong>: Digital Surface Models (<code>filename_DSM.tif</code>) and orthophotos (<code>filename_Ortho.tif</code>) stitched together from the raw data. The included flights are indicated in the file name (7 flights for <code>20151008_Liereman_1-4_20151009_Liereman_1-3_DSM.tif)</code>.</li> <li><strong>Ground control points</strong>: not applicable for this dataset.</li> </ul> <p><strong>Cloud Optimized GeoTIFF</strong></p> <p>The most efficient way to explore the processed data is by loading the <a href="https://www.cogeo.org/">Cloud Optimized GeoTIFFs</a> we created for each processed file. Copy one of the file URLs below and follow e.g. the <a href="https://www.cogeo.org/qgis-tutorial.html">QGIS tutorial</a> to load this type of file.</p> <ul> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151008_Liereman_1-4_20151009_Liereman_1-3_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151008_Liereman_1-4_20151009_Liereman_1-3_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20170718_Liereman_eBee_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20170718_Liereman_eBee_DTM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20170718_Liereman_eBee_Ortho.tif</code> multispec</li> </ul> <p>See <a href="https://s3-eu-west-1.amazonaws.com/lw-remote-sensing/index.html">this page</a> for an overview of public INBO RPAS data.</p>
Orthophotos and DSMs derived from RPAS flights over wild boar damaged fields in Eigenbilzen in Flanders, Belgium
<p><strong>Study area</strong></p> <p>The study area in Eigenbilzen is situated in the agricultural zone east of the locality of Eigenbilzen, in the province of Limburg, Flanders, Belgium. The flights picture a wheat field where damage by wild boar is apparent.</p> <p><strong>Data collection</strong></p> <p>Data were collected by the <a href="https://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a> with a fixed wing drone Gatewing X100 in 2015 (2 flights). RGB data were acquired using an off-the-shelf Ricoh GR Digital IV camera, with the following image bands: 1: red, 2: green, 3: blue, 4: alpha channel. CIR (color-infrared) data were acquired using a NIR-enabled Ricoh GR Digital IV camera, with the following info bands: 1: NIR, 2: red, 3: green, 4: alpha channel.</p> <p><strong>Data processing</strong></p> <p>The raw data were processed to Digital Surface Models and orthophotos by INBO in 2015 using Agisoft PhotoScan Pro 1.0.4, a structure-from-motion (SfM) based photogrammetry software program.</p> <p><strong>Coordinate reference system</strong></p> <p>All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>.</p> <p><strong>Files</strong></p> <ul> <li><strong>Raw flight data</strong>: images and logs collected by the drone during flight. These files are zipped per flight, with the date (<code>yyyymmdd</code>) and flight number (<code>x</code>) indicated in the file name (<code>flight_yyyymmdd_Bilzen_x.zip</code>).</li> <li><strong>Processed data</strong>: Digital Surface Models (<code>filename_DSM.tif</code>) and orthophotos (<code>filename_Ortho.tif</code>) stitched together from the raw data. The included flight is indicated in the file name (e.g. <code>20150728_Bilzen_1_DSM.tif</code>).</li> <li><strong>Ground control points</strong>: not applicable for this dataset.</li> </ul> <p><strong>Cloud Optimized GeoTIFF</strong></p> <p>The most efficient way to explore the processed data is by loading the <a href="https://www.cogeo.org/">Cloud Optimized GeoTIFFs</a> we created for each processed file. Copy one of the file URLs below and follow e.g. the <a href="https://www.cogeo.org/qgis-tutorial.html">QGIS tutorial</a> to load this type of file.</p> <ul> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_1_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_2_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_2_Ortho.tif</code> CIR</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_1_DSM.tif</code></li> </ul> <p>See <a href="https://s3-eu-west-1.amazonaws.com/lw-remote-sensing/index.html">this page</a> for an overview of public INBO RPAS data.</p>
Orthophotos and DSMs derived from RPAS flights over the nature reserve Averbode Bos & Heide in Flanders, Belgium
<p><strong>Study area</strong></p> <p>Averbode Bos & Heide is a nature reserve situated near the locality of Averbode, in the province of Flemish-Brabant, Flanders, Belgium. The area is managed by the nature conservation NGO Natuurpunt and consists of wet and dry heathlands, inland dunes, forests and moorland pools. In the years prior to the drone flights, large stands of mostly coniferous trees were cut to enable ecological restoration of heathlands and moorland pools. The drone flight was triggered by a particular interest to monitor the effects of this restoration.</p> <p><strong>Data collection</strong></p> <p>Data were collected by the <a href="https://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a> with a fixed wing drone Gatewing X100 in 2015 and 2016 (6 flights). RGB data were acquired using an off-the-shelf Ricoh GR Digital IV camera, with the following image bands: 1: red, 2: green, 3: blue, 4: alpha channel. CIR (color-infrared) data were acquired using a NIR-enabled Ricoh GR Digital IV camera, with the following info bands: 1: NIR, 2: red, 3: green, 4: alpha channel.</p> <p><strong>Data processing</strong></p> <p>The raw data were processed to Digital Surface Models and orthophotos by the <a href="https://vito.be/en">Flemish Institute for Technological Research (VITO)</a> in 2017. Images with coarse GPS coordinates were imported and processed in Agisoft PhotoScan Pro 1.4.x, a structure-from-motion (SfM) based photogrammetry software program. After extraction and matching of tie points, a bundle adjustment leads to a sparse point cloud and a refined set of camera position and orientation values. From there, a point cloud densification and classification into ground and non-ground points was performed, leading to a rasterized digital surface model (DSM) and digital terrain model (DTM). Finally, a true orthomosaic was projected onto the DTM.</p> <p><strong>Coordinate reference system</strong></p> <p>All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>.</p> <p><strong>Files</strong></p> <ul> <li><strong>Raw flight data</strong>: images and logs collected by the drone during flight. These files are zipped per flight, with the date (<code>yyyymmdd</code>) and flight number (<code>x</code>) indicated in the file name (<code>flight_yyyymmdd_ABH_x.zip</code>).</li> <li><strong>Processed data</strong>: Digital Surface Models (<code>filename_DSM.tif</code>) and orthophotos (<code>filename_Ortho.tif</code>) stitched together from the raw data. The included flights are indicated in the file name (e.g. 3 flights for <code>20150928_ABH_1-2_20151001_ABH_1_DSM.tif</code>).</li> <li><strong>Ground control points</strong>: not applicable for this dataset.</li> </ul> <p><strong>Cloud Optimized GeoTIFF</strong></p> <p>The most efficient way to explore the processed data is by loading the <a href="https://www.cogeo.org/">Cloud Optimized GeoTIFFs</a> we created for each processed file. Copy one of the file URLs below and follow e.g. the <a href="https://www.cogeo.org/qgis-tutorial.html">QGIS tutorial</a> to load this type of file.</p> <ul> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150928_ABH_1-2_20151001_ABH_1_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150928_ABH_1-2_20151001_ABH_1_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151001_ABH_2_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151001_ABH_2_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_1_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_1_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_2_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_2_Ortho.tif</code> CIR</li> </ul> <p>See <a href="https://s3-eu-west-1.amazonaws.com/lw-remote-sensing/index.html">this page</a> for an overview of public INBO RPAS data.</p>
Orthophotos and DSMs derived from RPAS flights over the nature reserve Kalmthoutse Heide in Flanders, Belgium
<p><strong>Study area</strong></p> <p>The Kalmthoutse Heide is a nature reserve situated north of Kalmthout, in the province of Antwerp, Flanders, Belgium. It is part of the Cross-Border Nature Park De Zoom - Kalmthoutse Heide in the Netherlands and Belgium. The Kalmthoutse Heide is managed by the Flemish Agency for Nature and Forest and consists of wet and dry heathlands, inland dunes, forests and moorland pools. In this area, there is particular interest in monitoring the encroachment of the heathlands by <em>Molinia caerulea</em> and <em>Campylopus introflexus</em>.</p> <p><strong>Data collection</strong></p> <p>Data were collected by the <a href="http://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a> with a fixed wing drone Gatewing X100 in 2015 and 2016 (8 flights). RGB data were acquired using an off-the-shelf Ricoh GR Digital IV camera, with the following image bands: 1: red, 2: green, 3: blue, 4: alpha channel.</p> <p><strong>Data processing</strong></p> <p>The raw data were processed to Digital Surface Models and orthophotos by the <a href="https://vito.be/en">Flemish Institute for Technological Research (VITO)</a> in 2017. Images with coarse GPS coordinates were imported and processed in Agisoft PhotoScan Pro 1.4.x, a structure-from-motion (SfM) based photogrammetry software program. After extraction and matching of tie points, a bundle adjustment leads to a sparse point cloud and a refined set of camera position and orientation values. Ground control points (either artificially installed markers on the terrain, or other photo-identifiable points, measured on the ground with RTK GNSS) were used to further refine the camera calibration and obtain a pixel-level georeferencing accuracy. From there, a point cloud densification and classification into ground and non-ground points was performed, leading to a rasterized digital surface model (DSM) and digital terrain model (DTM). Finally, a true orthomosaic was projected onto the DTM.</p> <p><strong>Coordinate reference system</strong></p> <p>All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>.</p> <p><strong>Files</strong></p> <ul> <li><strong>Raw flight data</strong>: images and logs collected by the drone during flight. These files are zipped per flight, with the date (<code>yyyymmdd</code>) and flight number (<code>x</code>) indicated in the file name (<code>flight_yyyymmdd_KH_x.zip</code>).</li> <li><strong>Processed data</strong>: Digital Surface Models (<code>filename_DSM.tif</code>) and orthophotos (<code>filename_Ortho.tif</code>) stitched together from the raw data. The included flights are indicated in the file name (e.g. 3 flights for <code>20150717_KH_1-3_DSM.tif</code>).</li> <li><strong>Ground control points</strong>: temporary ground control points were placed for the first flights on 2015-07-17 (visible in <code>20150717_KH_1-3_Ortho.tif</code>). Coordinates for these are available in <code>GCP_20150717_KH.tsv</code>.</li> </ul> <p><strong>Cloud Optimized GeoTIFF</strong></p> <p>The most efficient way to explore the processed data is by loading the <a href="https://www.cogeo.org/">Cloud Optimized GeoTIFFs</a> we created for each processed file. Copy one of the file URLs below and follow e.g. the <a href="https://www.cogeo.org/qgis-tutorial.html">QGIS tutorial</a> to load this type of file.</p> <ul> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150717_KH_1-3_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150717_KH_1-3_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_1-2_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_1-2_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_3_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_3_Ortho.tif</code> RGB</li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160205_KH_1-2_DSM.tif</code></li> <li><code>http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160205_KH_1-2_Ortho.tif</code> RGB</li> </ul> <p>See <a href="https://s3-eu-west-1.amazonaws.com/lw-remote-sensing/index.html">this page</a> for an overview of public INBO RPAS data.</p>
EuroSDR RPAS benchmark datasets
<p><strong>Overview</strong></p> <p>The <a href="https://www.eurosdr.net/">EuroSDR</a> RPAS benchmark datasets were aqcuired in August 2021 as part of the EuroSDR benchmark initiative. This aims to evaluate the true geometric quality of real-world survey data generated from Remotely Piloted Aircraft System (RPAS) photogrammetry and lidar under different control configurations, focussing primarily on the geometric quality of data generated in the absence of ground control and local GNSS base station information.</p> <p>Guided by a task force of National Mapping and Cadastral Agencies (NMCAs) experts and academics, in August 2021 Newcastle Geospatial Engineering team have established and surveyed a coordinated test field of independent checkpoints (CPs), test surfaces and profiles at the disused Wards Hill Quarry near Morpeth, Northumberland, UK. The 350 x 250 m study area was simultaneously surveyed using the following RPAS mounted instruments, each limited to a single flight to represent “real-world” operation:</p> <ul> <li>DJI Phantom 4 RTK </li> <li>DJI ZENMUSE P1 </li> <li>DJI ZENMUSE L1 </li> <li>Routescene LidarPod </li> <li>Riegl MiniVUX</li> </ul> <p>More information can be found <a href="https://geospatialncl.github.io/eurosdr-rpas-benchmark/">here</a>.</p> <p>To facilitate and encourage wider use of the EuroSDR RPAS dataset, it has been made open access.</p> <p><strong>About us</strong></p> <p>We are the <a href="https://www.ncl.ac.uk/engineering/research/civil-engineering/geospatial-engineering/">Geospatial Engineering</a> research group in the <a href="https://www.ncl.ac.uk/engineering/">School of Engineering</a> at <a href="https://www.ncl.ac.uk/">Newcastle University</a> with a long history of research and teaching across geospatial disciplines. <a href="https://www.eurosdr.net/">EuroSDR</a> is a not-for-profit organisation linking National Mapping and Cadastral Agencies with Research Institutes and Universities in Europe for the purpose of applied research in spatial data provision, management and delivery.</p> <p> </p>
Mapping Areas Invaded by Pinus sp. from Geographic Object-Based Image Analysis (GEOBIA) Applied on RPAS (Drone) Color Images
<p><strong>Abstract: </strong>Invasive alien species reduce biodiversity. In southern Brazil, the genus <em>Pinus</em> is considered invasive, and its dispersal by humans has resulted in this species reaching ecosystems that are more sensitive and less suitable for cultivation, as it was the case for the restingas on the island of Santa Catarina. Invasion control requires persistent efforts to identify and treat each new invasion case as a priority. In this study, areas invaded by <em>Pinus</em> sp. in restingas were mapped using images taken by a remotely piloted aircraft system (RPAS, or drone) to identify the invasion areas in great detail, enabling management to be planned for the most recently invaded areas, where management is simpler, more effective, and less costly. Geographic object-based image analysis (GEOBIA) was applied on images taken from a conventional RGB camera embedded in a RPAS, which resulted in a global accuracy of 89.56%, a mean kappa index of 0.86, and an F-score of 0.90 for the <em>Pinus</em> sp. Processing was conducted with open source software to reduce operational costs.</p>
Raw data used in the paper User involvement before the development of an indoor RPAS for the creative industries
<p>This file includes the data used in the paper: de-Miguel-Molina, B., de-Miguel-Molina, M., Santamarina-Campos, V., & Segarra-Oña, M. (2021). User involvement before the development of an indoor RPAS for the creative industries. <em>International Journal of Micro Air Vehicles</em>, <em>13</em>, 1756829321992140.</p> <p>Please, cite the paper if you use the data.</p> <p> </p>
RPAS thermal infrared data for Nicola River - 2016/2017
<p>In this study, we used remotely piloted aircraft system (RPAS)-based thermal infrared (TIR) imaging to study fine-scale thermal heterogeneity in a temperature-sensitive salmon stream in the Southern Interior region of British Columbia. We were able to identify cool-water zones at the site level that may provide important thermal refugia for salmonids during periods of high summer stream temperatures. Repeat imaging of our study reach following a major flood event in 2017 found that the abundance of cold alcoves, a type of thermal refuge habitat, increased significantly. Our results highlight the importance of maintaining the fluvial processes that create new habitat, in-keeping with the concept of Shifting Habitat Mosaics. As part of this work, we also provide some best practices for rapid, RPAS-based TIR surveys of stream thermal refugia – expecting that this type of survey will become an increasingly common addition to fish habitat inventories.</p>
RPAS thermal infrared data for Nicola River - 2016/2017
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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.