Find research datasets worth reusing

Fig. 4 in The flight of the shrike. The ornithological representation in the Baptism of Christ (1470-1475 c.) by Andrea del Verrocchio and Leonardo da Vinci

Fig. 4 - Male redstart Phoenicurus phoenicurus flying among the fronds of a palm tree, in another detail of Verrocchio's Baptism of Christ. / Maschio di codirosso Phoenicurus phoenicurus in volo fra le fronde di una palma, in un altro particolare del Battesimo di Cristo. (Courtesy Galleria degli Uffizi, Firenze).

Fig. 5 in The flight of the shrike. The ornithological representation in the Baptism of Christ (1470-1475 c.) by Andrea del Verrocchio and Leonardo da Vinci

Fig. 5 - Portrait of an adult male redstart Phoenicurus phoenicurus. / Maschio adulto di codirosso Phoenicurus phoenicurus. (Drawing by: / Disegno di: Sandro Sacchetti).

Fig. 3 in The flight of the shrike. The ornithological representation in the Baptism of Christ (1470-1475 c.) by Andrea del Verrocchio and Leonardo da Vinci

Fig. 3 - Portrait of a female of red-backed shrike, Lanius collurio. / Femmina adulta di averla piccola, Lanius collurio. (Drawing by: / Disegno di: Sandro Sacchetti).

Fig. 2 in The flight of the shrike. The ornithological representation in the Baptism of Christ (1470-1475 c.) by Andrea del Verrocchio and Leonardo da Vinci

Fig. 2 - Detail of the Baptism of Christ. / Particolare del Battesimo di Cristo. (Courtesy Gallerie degli Uffizi, Firenze).

Fig. 1 in The flight of the shrike. The ornithological representation in the Baptism of Christ (1470-1475 c.) by Andrea del Verrocchio and Leonardo da Vinci

Fig. 1 - The Baptism of Christ (1470-1471), oil painting by Andrea del Verrocchio. / Battesimo di Cristo (1470-1471), olio su tavola di Andrea del Verrocchio. (Courtesy Gallerie degli Uffizi, Firenze).

Fig. 2 in Flight ability and dispersal of European grapevine moth gamma-irradiated males (Lepidoptera: Tortricidae)

Fig. 2. Schematic representation of the vineyard and the pheromone traps positions at the experimental plot where the marked male moths were released.

Fig 1 in Flight ability and dispersal of European grapevine moth gamma-irradiated males (Lepidoptera: Tortricidae)

Fig 1. Schematic representation of the flight assessment cage used to measure the flight responses of Lobesia botrana males to calling females. In the female compartment, 2-day-old virgin females were confined inside a small cylindrical plastic mesh box with a 5% sucrose-wetted wick. Males irradiated either with 150 Gy or with 350 Gy and untreated males differentially marked with variously colored fluorescent powders were introduced into the male compartment. The number of males of each of the 3 kinds that flew through the open slit at the 45 cm height [the 2 lower openings (slits) were sealed] into the female compartment were recorded at 24, 48, 72 and 96 h. Air was drawn into the female compartment and exhausted from the male compartment.

Fig. 2 in Influence of gamma-irradiation on flight ability and dispersal of Conopomorpha sinensis (Lepidoptera: Gracillariidae)

Fig. 2. Numbers of adult Conopomorpha sinensis males recaptured in traps deployed at various distances (m) from the release point in 2 release/recapture experiments in a litchi orchard of the South China Agricultural University, Guangzhou, China. The males were either non-irradiated or irradiated either with 150 or 200 Gy. A: First release, B: Second release.

Fig. 1 in Influence of gamma-irradiation on flight ability and dispersal of Conopomorpha sinensis (Lepidoptera: Gracillariidae)

Fig. 1. Survival (days) of non-irradiated Conopomorpha sinensis males either dyed with 1 of 3 different fluorescent colors or undyed (control) in the laboratory. Each treatment involved 30 males.

Fig. 3 in Influence of gamma-irradiation on flight ability and dispersal of Conopomorpha sinensis (Lepidoptera: Gracillariidae)

Fig. 3. Frequency distributions of the dispersal directions of adult Conopomorpha sinensis males in 2 release/recapture experiments in a litchi orchard of the South China Agricultural University, Guangzhou, China. The males were either non-irradiated or irradiated either with 150 or 200 Gy. A: First release, B: Second release.

opencc-by-4.0Dec 2016View details →

Fig. 2 in Monitoring the establishment and flight phenology of parasitoids of emerald ash borer (Coleoptera: Buprestidae) in Michigan by using sentinel eggs and larvae

Fig. 2. Percentage of parasitism by Tetrastichus planipennisi of emerald ash borer larvae in larval sentinel logs (pooled by sample date, i.e., the date that larval sentinel logs were collected) in Nancy Moore and Burchfield Parks, Michigan, in (A) 2011, (C) 2012, and (E) 2013, and by Atanycolus spp. in (B) 2011, (D) 2012, and (F) 2013. The secondary Y-axis is growing degree day base 10 °C (GDD10) using the Baskerville–Emin method.

opencc-by-4.0Mar 2017View details →

Fig. 1. The schematics for 4 in Circuitry and coding used in a flight mill system to study flight performance of Halyomorpha halys (Hemiptera: Pentatomidae)

Fig. 1. The schematics for 4 laser trip wire systems on a single breadboard and a single Arduino board. Lasers have been excluded. Note how the Arduino board allows for the hybrid use of both analog and digital circuitry systems.

opencc-by-4.0Dec 2016View details →

Fig. 1 in Monitoring the establishment and flight phenology of parasitoids of emerald ash borer (Coleoptera: Buprestidae) in Michigan by using sentinel eggs and larvae

Fig. 1. Percentage of parasitism by Oobius agrili of emerald ash borer eggs on all egg sentinel logs (pooled by sample date, i.e., the date that egg sentinel logs were collected) in Central Park, Michigan, in (A) 2011 and (C) 2012, and on individual egg sentinel logs pooled over all sample dates in (B) 2011 and (D) 2012. The secondary Y-axis is growing degree day base 10 °C (GDD10) using the Baskerville–Emin method.

opencc-by-4.0Apr 2018View details →

BirdVox-70k: a dataset for species-agnostic flight call detection in half-second clips

BirdVox-70k: a dataset for avian flight call detection in half-second clips ====================================================================================== Version 1.0, April 2018. Created By ---------- Vincent Lostanlen (1, 2, 3), Justin Salamon (2, 3), Andrew Farnsworth (1), Steve Kelling (1), and Juan Pablo Bello (2, 3). (1): Cornell Lab of Ornithology (CLO) (2): Center for Urban Science and Progress, New York University (3): Music and Audio Research Lab, New York University https://wp.nyu.edu/birdvox   Description ----------- The BirdVox-70k dataset contains 70k half-second clips from 6 audio recordings in the BirdVox-full-night dataset, each about ten hours in duration. These recordings come from ROBIN autonomous recording units, placed near Ithaca, NY, USA during the fall 2015. They were captured on the night of September 23rd, 2015, by six different sensors, originally numbered 1, 2, 3, 5, 7, and 10. Andrew Farnsworth used the Raven software to pinpoint every avian flight call in time and frequency. He found 35402 flight calls in total. He estimates that about 25 different species of passerines (thrushes, warblers, and sparrows) are present in this recording. Species are not labeled in BirdVox-70k, but it is possible to tell apart thrushes from warblers and sparrrows by looking at the center frequencies of their calls. The annotation process took 102 hours. The dataset can be used, among other things, for the research,development and testing of bioacoustic classification mode ls, including the reproduction of the results reported in [1]. For details on the hardware of ROBIN recording units, we refer the reader to [2]. [1] V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection. Proc. IEEE ICASSP, 2018. [2] J. Salamon, J. P. Bello, A. Farnsworth, M. Robbins, S. Keen, H. Klinck, and S. Kelling. Towards the Automatic Classification of Avian Flight Calls for Bioacoustic Monitoring. PLoS One, 2016. @inproceedings{lostanlen2018icassp,   title = {BirdVox-full-night: a dataset and benchmark for avian flight call detection},   author = {Lostanlen, Vincent and Salamon, Justin and Farnsworth, Andrew and Kelling, Steve and Bello, Juan Pablo},   booktitle = {Proc. IEEE ICASSP},   year = {2018},   published = {IEEE},   venue = {Calgary, Canada},   month = {April}, }   Data Files ------------ BirdVox-70k contains the recordings as HDF5 files, sampled at 24 kHz, with a single channel (mono). Each HDF5 file corresponds to a different sensor. The name of the HDF5 dataset in each file is "waveforms".   Metadata Files -------------- Contrary to BirdVox-full-night, BirdVox-70k is not shipped with a metadata file. Rather, the metadata is included in the keys of the elements in the HDF5 files themselves, whose values are the waveforms. An example of BirdVox-70k key is: <pre>unitID_TIMESTAMP_FREQ_LABEL </pre> where <ul> <li>ID is the identifier of the unit (01, 02, 03, 05, 07, or 10)</li> <li>TIMESTAMP is the timestamp of the center of the clip in the BirdVox-full-night recording. This timestamp is measured in samples at 24 kHz. It is accurate at about 10 ms.</li> <li>FREQ is the center frequency of the flight call, measured in Hertz. It is accurate at about 1 kHz. When the clip is negative, i.e. does not contain any flight call, it is set equal to zero by convention.</li> <li>LABEL is the label of the clip, positive (1) or negative (0).</li> </ul>   Example: <pre>unit01_085256784_03636_1</pre> is a positive clip in unit 01, with timestamp 085256784 (3552.37 seconds after dividing by the sample rate 24000), center frequency 3636 Hz.   Another example: <pre>unit05_284775340_00000_0</pre> is a negative clip in unit 05, with timestamp 284775340 (11865.64 seconds).   The approximate GPS coordinates of the sensors (latitudes and longitudes rounded to 2 decimal points) and UTC timestamps corresponding to the start of the recording for each sensor are included as CSV files in the main directory.   Please acknowledge BirdVox-70k in academic research ---------------------------------------------------------- When BirdVox-70k is used for academic research, we would highly appreciate it if  scientific publications of works partly based on this dataset cite the following publication: V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018. The creation of this dataset was supported by NSF grants 1125098 (BIRDCAST) and 1633259 (BIRDVOX), a Google Faculty Award, the Leon Levy Foundation, and two anonymous donors.   Conditions of Use ----------------- Dataset created by Vincent Lostanlen, Justin Salamon, Andrew Farnsworth, Steve Kelling, and Juan Pablo Bello. The BirdVox-70k dataset is offered free of charge under the terms of the Creative  Commons Attribution 4.0 International (CC BY 4.0) license: https://creativecommons.org/licenses/by/4.0/ The dataset and its contents are made available on an "as is" basis and without  warranties of any kind, including without limitation satisfactory quality and  conformity, merchantability, fitness for a particular purpose, accuracy or  completeness, or absence of errors. Subject to any liability that may not be excluded or limited by law, Cornell Lab of Ornithology is not liable for, and expressly excludes all liability for, loss or damage however and whenever caused to anyone by any use of the BirdVox-70k dataset or any part of it.   Feedback ----------- Please help us improve BirdVox-70k by sending your feedback to: vincent.lostanlen@gmail.com and af27@cornell.edu In case of a problem, please include as many details as possible.   Acknowledgements ---------------- Jessie Barry, Ian Davies, Tom Fredericks, Jeff Gerbracht, Sara Keen, Holger Klinck, Anne Klingensmith, Ray Mack, Peter Marchetto, Ed Moore, Matt Robbins, Ken Rosenberg, and Chris Tessaglia-Hymes. We acknowledge that the land on which the data was collected is the unceded territory of the Cayuga nation, which is part of the Haudenosaunee (Iroquois) confederacy.

Orthophotos and DSMs derived from RPAS flights over the nature reserve Zwin in Flanders, Belgium

Study area 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 Ammophila arenaria, dune grasslands and/or shrub (Hippophae rhamnoides, Salix repens), and a transitional grassland zone that stretches from the inner edge of the coastal dunes into the polders. Data collection 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. Data processing 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. Coordinate reference system All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>. Files <ul> <li>Raw flight data: 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>Processed data: 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>Ground control points: 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> Cloud Optimized GeoTIFF 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. <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> 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.

Orthophotos and DSMs/DTM derived from RPAS flights over the nature reserve Landschap De Liereman in Flanders, Belgium

Study area 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, Nardus grasslands on siliceous soils, forests and transition mires, as well as some remaining arable fields and high-intensity agricultural grasslands. Data collection 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. 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. Data processing 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. Coordinate reference system All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>. Files <ul> <li>Raw flight data: 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>Processed data: 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>Ground control points: not applicable for this dataset.</li> </ul> Cloud Optimized GeoTIFF 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. <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> 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.

Orthophotos and DSMs derived from RPAS flights over wild boar damaged fields in Eigenbilzen in Flanders, Belgium

Study area 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. Data collection 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. Data processing 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. Coordinate reference system All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>. Files <ul> <li>Raw flight data: 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>Processed data: 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>Ground control points: not applicable for this dataset.</li> </ul> Cloud Optimized GeoTIFF 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. <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> 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.

Orthophotos and DSMs derived from RPAS flights over the nature reserve Averbode Bos & Heide in Flanders, Belgium

Study area 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. Data collection 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. Data processing 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. Coordinate reference system All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>. Files <ul> <li>Raw flight data: 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>Processed data: 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>Ground control points: not applicable for this dataset.</li> </ul> Cloud Optimized GeoTIFF 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. <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> 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.

Orthophotos and DSMs derived from RPAS flights over the nature reserve Kalmthoutse Heide in Flanders, Belgium

Study area 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 Molinia caerulea and Campylopus introflexus. Data collection 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. Data processing 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. Coordinate reference system All geospatial data have the coordinate reference system <code>EPSG:31370 - Belgian Lambert 72</code>. Files <ul> <li>Raw flight data: 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>Processed data: 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>Ground control points: 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> Cloud Optimized GeoTIFF 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. <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> 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.