cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.f2u9ze
title: Occurrence Download

description: A dataset containing 158 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudaphya ferreri (de Buen & Fage, 1908)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen, Material sample)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 158 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004727-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sepqg5
title: Occurrence Download

description: A dataset containing 125 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pristimantis relictus Roberto, Loebmann, Lyra & Ávila, 2022"
 ]
}

 The dataset includes 125 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005654-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3nj3vm
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pristimantis rupicola Taucce, Nascimento, Trevisan, Leite, Santana, Haddad & Napoli, 2020"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005656-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9na9z2
title: Occurrence Download

description: A dataset containing 4105 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-10000.0",
 "Geometry POLYGON((-124.97844 23.70333,-70.34438 23.70333,-70.34438 44.77297,-124.97844 44.77297,-124.97844 23.70333))",
 "TaxonKey is Bromus tectorum L."
 ]
}

 The dataset includes 4105 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005657-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ruv64
title: Occurrence Download

description: A dataset containing 92 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pristimantis vinhai (Bokermann, 1975)"
 ]
}

 The dataset includes 92 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005658-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zhn8w7
title: Occurrence Download

description: A dataset containing 92 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "TaxonKey is Clarias gariepinus (Burchell, 1822)"
 ]
}

 The dataset includes 92 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005659-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/5e78ff91e9cd4143bfa3b7358efd2607
title: ForestScan: Tree census data (diameter and species name) of FBRMS-01: Paracou, French Guiana 1ha plot IRD-CNES, October 2021

description: This dataset consists of data collected during the October 2021 census. A few trees were also measured in January 2022 as they could not be accessed in 2021. The data collection includes treeID, position, DBH_cm (girth in cm), observations, POM_cm (Point of measurement) status, census, date, family, genus and species. Botanical identification was done by Julien Engel (IRD). Trees were positioned using TLS scan by Olivier Martin. This tree census was funded by CNES (France).
DOI: 10.5285/b1cd34f6af7941a3b1429ac52a3f6b28
title: ForestScan: Terrestrial Laser Scanning (TLS) of FBRMS-01: Paracou, French Guiana 1ha plot IRD-CNES, October 2021

description: Terrestrial laser scanning (TLS) was conducted in October 2021 by G. Vincent and J-L Smock (IRD) using a Riegl VZ-400. Scans were acquired at locations on a 10 m Cartesian grid. Capturing a complete sample of the scene at each location requires two scans (upright and tilted), owing to a 100° field of view. 249 scans in total were collected. The angular resolution between sequentially fired pulses was 0.04°, resulting in approximately 22.4 million emitted pulses per scan (i.e., 5.42 billion per ha). Up to four targets can be resolved per pulse, with a nominal ranging accuracy of 5 mm. The laser itself is characterised by a beam divergence of 0.35 mrad, and the diameter of the beam at emission is 7 mm (e.g., the diameter of the beam at a range of 50 m, would be 21 mm). The pulse repetition rate was 300 kHz, therefore, each scan took approximately 3 minutes to complete. To generate a plot-level point cloud from individual scans, all scans were co-registered and projected to a standard geographical coordinate system (epsg 2972). To this end, 5 identifiable targets with known X,Y,Z coordinates (plot corners + plot centre) were positioned using a total station.

Once co-registered using RiScanPro software, individual scans were exported in las extrabyte format (including deviation) using LidarFomartConverter v.1.2.(AMAP code based on RivLib). Reflectance range was set to -30dB to +5dB and stored in the Intensity field as a long integer. Echoes outside this reflectance range were discarded. Coordinate precisions were set to 0.001 m. The full point cloud (all 249 scans) was then cropped to 1.4 ha plot (+10m buffer around 100x100m plot), and tiled per 20 x 20m (no buffer). Cropping and tiling were done with LAStools software. Scan position number was stored as flight line to allow selection of scans if needed. In particular, distant scans which contribute little more than noise could be deleted. LiDAR data were acquired without the “reflectance optimization filter”. In order to keep only returns with reflectance above -20dB (equivalent to setting reflectance optimization filter) all returns with Intensity below 18724 were dropped.
DOI: 10.15139/s3/jt3csv
title: Monmouth University Pennsylvania Poll, Number 265

description: This survey was conducted among Pennsylvania voters and addresses the 2022 election for US Senate and governor as well as issues facing the state.
DOI: 10.25446/oxford.28684766
title: Kähler 1955

description: Transcription, translation and analysis of Kähler (1955), Afrika und Übersee 39, 89--94.
DOI: 10.25446/oxford.28684766.v1
title: Kähler 1955

description: Transcription, translation and analysis of Kähler (1955), Afrika und Übersee 39, 89--94.
DOI: 10.5285/7bef89a9dc404683a46642625a024a4b
title: ForestScan: Aerial Laser Scanning (ALS) of FBRMS-01: Paracou, French Guiana, November 2022

description: This Aerial Laser Scanning (ALS) campaign was conducted in November 2022. The ALS data corresponding to plots FG5c1, FG6c2, FG8c4 and IRD-CNES also scanned by Terrestrial LiDAR Scanning (TLS) in October or November 2022 as part of the ForestScan Project are provided in four separate laz files.

The covered area: 3*2.16 ha + 1*1.44 ha; Pulse density: ~200 m2; Scanner type: VQ 780II RIEGL; Scanner wavelength: 1064 nm; Beam divergence: &lt;=0.25 mrad (1/e2); Vehicle: Airplane BN2; Operator: Altoa. Acquisition parameters: swath angle: +/-20 degrees; PRR (channel type): ~ 1000 kHz; Ground footprint size of pulse: ~0.16 m; Flight height: 650m terrain follow mode (AGL); Acquisition mode: Full waveform, RGB camera on board but no orthomosaïc made.
DOI: 10.5285/325a4dde60d142049339e0c84816aac1
title: ForestScan Project: Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS) and Terrestrial Laser Scanning (TLS) data of FBRMS-01: Paracou, French Guiana plot 6, 10th October to 15th November 2019

description: This dataset contains LiDAR scanning derived products (raw scanner data, geo-located point clouds, individual 3D tree models) collected over the north-eastern part (200 m x 200 m) of FBRMS-01: Paracou, French Guiana plot 6. The campaign took place from the 10th of October to the 15th of November 2019. Terrestrial LiDAR Scanning (TLS) was conducted on a regular grid with spacing of 10 m with a RIEGL VZ-400 scanner and retro-reflective targets for scan registration. Unpiloted Aerial Vehicle Laser Scanning (UAV-LS) was conducted with a RIEGL Ricopter with VUX-SYS VUX-1UAV system with varying flight heights and flight directions.

The TLS point clouds were collected to produce explicit 3D models of individual trees and subsequently estimate their above-ground biomass (AGB). The UAV-LS point clouds were collected to test scanner settings and inspect point clouds properties, in particular with regard to their suitability to model individual trees and their AGB.

The campaign was conducted by researchers Benjamin Brede, Harm Bartholomeus and Alvaro Lau of the Laboratory of Geo-Information Science and Remote Sensing of Wageningen University & Research (The Netherlands) with support from Nicolas Barbier of AMAP Lab (Botany and Modeling of Plant Architecture and Vegetation).
DOI: 10.5285/7a4649cabd3e4afb8cd31cfd7d95ac8e
title: ForestScan project: Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS) data of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon, June 2022

description: This dataset contains point cloud data (a set of data points in a 3D coordinate system) which were collected using a RIEGL miniVUX1-DL LiDAR scanner mounted on a DELAIR DT26X Unpiloted Aerial Vehicle (UAV). The data was collected in June 2022 as part of the ForestScan project. The person responsible for the data collection was Dr. Iain McNicol from the University of Edinburgh, who collected and processed the data.
DOI: 10.5285/ff217c783e3f4c66a4891d2b5807ee6e
title: ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-03: Kabili-Sepilok, Malaysian Borneo 1ha plot SEP-30, March 2017

description: Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Malaysia during March 2017 by Mathias Disney using a Riegl VZ-400 scanner. Data collection assistance was provided by postdocs Dr Phil Wilkes, Dr Andy Burt and Dr Toby Jackson and a local team of field assistants. Data processing was performed by Dr Cecilia Chavana-Bryant with assistance provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.

Scans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.

The Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2). 

Data for each of the three FBRMS plots is found within plot directories: SEP-11, SEP-12 and SEP-30. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2017-03-20.001.riproject) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/malaysia/SEP-30/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets.
DOI: 10.15468/dl.u7sugm
title: Occurrence Download

description: A dataset containing 9866 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Material sample, Specimen)",
 "TaxonKey is Ameiva ameiva (Linnaeus, 1758)",
 "Year 1970-2025"
 ]
}

 The dataset includes 9866 records from 167 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005660-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/bb81c82352524df99ddd411f6ca2ec81
title: ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-03: Kabili-Sepilok, Malaysian Borneo 1ha plot SEP-12, March 2017

description: Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Malaysia during March 2017 by Mathias Disney using a Riegl VZ-400 scanner. Data collection assistance was provided by postdocs Dr Phil Wilkes, Dr Andy Burt and Dr Toby Jackson and a local team of field assistants. Data processing was performed by Dr Cecilia Chavana-Bryant with assistance provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates. 

Scans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.

The Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).

Data for each of the three FBRMS plots is found within plot directories: SEP-11, SEP-12 and SEP-30. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2017-03-02.001.riproject) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/malaysia/SEP-12/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets.
DOI: 10.5285/37b039605e9b4bb5a89371fd7f5b7ba1
title: ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-03: Kabili-Sepilok, Malaysian Borneo 1ha plot SEP-11, March 2017

description: Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Malaysia during March 2017 by Mathias Disney using a Riegl VZ-400 scanner. Data collection assistance was provided by postdocs Dr Phil Wilkes, Dr Andy Burt and Dr Toby Jackson and a local team of field assistants. Data processing was performed by Dr Cecilia Chavana-Bryant with assistance provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates
.
Scans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.

The Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).

Data for each of the three FBRMS plots is found within plot directories: SEP-11, SEP-12 and SEP-30. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2017-03-14.001.riproject) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/malaysia/SEP-11/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets.
DOI: 10.5285/8ed3ddec76b8470285bdb2ea643f54bc
title: ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon 1ha plot OKO-03, June to July 2022

description: Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Gabon from June to July 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by Heddy O. Milamizokou Napo, Luna Soenens and Virginie Daelemans, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.

Scans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.

The Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).

Data for each of the four FBRMS plots is found within plot directories: LPG-01, OKO-01, OKO-02 and OKO-03. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-07-04_OKO-03.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-03/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets.