cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/bqf-ler-gxf
title: Lomelosia palaestina (L.) Raf.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/ehl-rbg-748
title: Lomelosia palaestina (L.) Raf.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.15468/dl.pxdaee
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ctenopharyngodon idella (Valenciennes, 1844)",
 "Country is Mauritius",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0111676-250525065834625/datasets/export for details.
DOI: 10.3535/16h-4tz-yt0
title: Lomelosia palaestina (L.) Raf.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/ts6-66d-3hd
title: Lomelosia palaestina (L.) Raf.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/bmn-wl9-5pr
title: Lomelosia palaestina (L.) Raf.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/f4g-p1s-16r
title: Tribulus terrestris L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/r3b-kgl-hxx
title: Lomelosia palaestina (L.) Raf.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/327-yxv-d2s
title: Tragopogon pratensis L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/ktp-2az-ycr
title: Tragopogon pratensis L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/gh4-np0-2c8
title: Tragopogon pratensis L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/hl5-qlj-nq8
title: Tragopogon pratensis L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/lb3-3gw-byh
title: Tragopogon pratensis L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.15468/dl.ket28a
title: Occurrence Download

description: A dataset containing 6065 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Umbra limi",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6065 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000431-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0162630.10fu
title: SH0162630.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/7115bc48-3ab0-475d-84ae-fd3126c20984
title: Land Cover Map 2015 (1km percentage aggregate class, GB)

description: This dataset consists of the 1km raster, percentage aggregate class version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 1km percentage product provides the percentage cover for each of 10 aggregated land cover classes for 1km x 1km pixels. This product contains one band per aggregated habitat class (producing a 10 band image).   The 10 aggregate classes are groupings of 21 target classes, which are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats.  The aggregate classes group some of the more specialised classes into more general categories. For example, the five coastal classes in the target class are grouped into a single aggregate coastal class.   This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. 

LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. 

LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990.  They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.
description: The percentage aggregate class is produced from the 25m raster product (which is derived from the vector product) by:
1.	Using gdal_calc to split the 10 target classes into 10 individual images for each class where the presence of the class in question is recorded as 100 and absence is assigned 0.
2.	Gdal_warp is then applied to each of the 10 presence/absence images to resample to 1km, using the 'average' option under resample. This produces images of percentage cover for each class.
3.	Gdal_merge is then used to create a single file with 10 bands, where each band provides the percentage cover for the class i.e. band 1 provides percentage cover for class 1 etc.
DOI: 10.5285/f15289da-6424-4a5e-bd92-48c4d9c830cc
title: Land Cover Map 2019 (25m rasterised land parcels, GB)

description: This is the 25m rasterised land parcels dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Great Britain. It describes Great Britain's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats.  This dataset was derived by rasterising the corresponding LCM2019 land parcels dataset into 25m pixels.  It is provided as a 3-band, 8-bit integer raster.  The first band is the UKCEH Land Cover Class identifier.  Bands 2 and 3 are indicators of classification confidence.  For a fuller description please refer to the product documentation.

LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019.  These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018.  These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015.

This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.
description: The 25m Rasterised Land Parcels datasets of the LCM2017, LCM2018 and LCM2019 product range were derived by rasterising the corresponding Land Parcels datasets. They give land cover information in 21 classes based on UK Biodiversity Action Plan broad habitats. They are provided as 3-band 8-bit integer 25m pixel rasters. Band-1 is the modal land cover from the Land Parcels dataset, band-2 and band-3 are indicators of classification confidence. The Land Parcels datasets are maintained in a PostGIS database. Gdal tools were used to rasterise the land parcels, giving the 25m Rasterised Landparcels dataset in GeoTiff format. GeoTiff is open standard format for raster data and GeoTiff files can be read by most GIS software.
DOI: 10.15156/bio/sh0162631.10fu
title: SH0162631.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/0e3ab6f8-4a20-4a60-a804-e144fb0bde39
title: Land Cover Map 2024 (25m rasterised land parcels, GB)

description: This is a 25m pixel data set representing the land surface of Great Britain, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band raster in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty.  A full description of this and all UKCEH LCM2024 products are available from the LCM2024 product documentation.
description: UKCEH’s automated land cover algorithms classify 10 m pixels across the whole of UK. A Random Forest classifier is used to classify four composite satellite images representing per season median surface reflectance, based on training data comprising locations of known land cover for 21 land cover classes. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra. 

Land cover was validated by organising the 10 m pixel classification into a land parcel framework (the LCM2024 classified land parcels product). The classified land parcels were compared to known land cover producing a confusion matrix to determine overall and per class accuracy. Details are available from the product documentation.

The 25 m rasterised land parcels product is created by rasterising the corresponding land parcel product.
DOI: 10.5285/35c7d0e5-1121-4381-9940-75f7673c98f7
title: Land Cover Map 2020 (10m classified pixels, GB)

description: This is a 10-metre pixel data set representing the land surface, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. 

The pixel product is given as a two-band raster in geoTiff format. The first band gives the most likely land cover type; the second band gives the probability associated with this land cover. The probability layer is an indicator of uncertainty (0 to 100). Low values correspond to low certainty (higher uncertainty). 

This is the first 10m resolution land cover map produced by UKCEH. It succeeds 20m resolution classified pixel products from 2017, 2018 and 2019.

A full description of this and all UKCEH LCM2020 products are available from the product documentation accompanying this data.
description: UKCEH's automated land cover classification algorithms generated the 10m classified pixels. Training data were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.

Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2020 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy. Details are available from the product documentation.

Prior to 2017 classified pixels are not available as part of the UKCEH LCM product suite. The classified pixels represent the core dataset from which the remaining products in the LCM2020 suite are derived. These include LCM2020 classified land parcels and the LCM2020 25m rasterised land parcels product.
DOI: 10.5285/d33593d7-5c4d-419e-924c-b341847fd6ae
title: Land Cover Map 1990 (1km dominant target class, N. Ireland)

description: This dataset consists of the 1km raster, dominant target class version of the Land Cover Map 1990 (LCM1990) for Northern Ireland. The 1km dominant coverage product is based on the 1km percentage product and reports the habitat class with the highest percentage cover for each 1km pixel. The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution.
 
LCM1990 is a land cover map of the UK which was produced at the UK Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019.  

LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the UKCEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs.

This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.
description: The 1km dominant cover target class is produced from the 1km percentage cover target class product. The 1km percentage cover data is used to identify the highest percentage cover across the 21 bands and a script is used to identify which band the maximum value coincides with.
DOI: 10.15156/bio/sh0162632.10fu
title: SH0162632.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/8eed6d77-714a-438a-aa65-887b1ef62378
title: Land Cover Map 2000 (1km percentage target class, N.Ireland)

description: This dataset consists of a 1km resolution raster version of the Land Cover Map 2000 for Northern Ireland. The raster consists of 27 bands. Within each band, each 1km pixel represents a percentage cover value for one of 27 target (or 'sub') classes, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. Note that the Band numberings in the dataset run from 1-27 rather than 0-26 and therefore each band relates to the one below it in the subclass code list (i.e. 1 = Unclassified, labelled as 0 in the list).
description: LCM2000 used image segmentation to identify land parcels in the pixel-based images. An automated procedure grouped the image pixels into spectrally 'uniform' segments. These were built around 'seedpoints' selected to avoid parcel boundaries. The segmentation recorded a field-by-field pattern, also separating land use zones within urban and suburban areas, and subdividing mosaics of semi-natural vegetation. Generalisation gave minimum mappable units of a half hectare. A 'vector' version was then created in the geographical information system (GIS), where the boundaries between the pixel-based segments were represented by digital linework. The resultant land parcels were treated as GIS objects to which attribute data could then be attached covering such topics as land cover class, parcel area, length of boundary, processing history, knowledge-based correction and identification of the original satellite scene. The raster products have been derived from the vector dataset. LCM2000 was produced at CEH Monks Wood. For further information on the methodology developed and used to create Land Cover Map 2000, see on-line supporting information.
DOI: 10.5285/f6f86b1a-af6d-4ed8-85af-21ee97ec5333
title: Land Cover Map 2017 (20m classified pixels, GB)

description: This is the 20m classified pixels dataset for the UKCEH Land Cover Map of 2017 (LCM2017) representing Great Britain. It describes Great Britain's land cover in 2017 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset is the Random Forest classification result from classifying a 20m pixel raster containing multi-season spectral information combined with context layers, which help to resolve spectral confusion.  It is provided as a 2-band, 8-bit integer raster.  The band-1 is the UKCEH Land Cover Class identifier, band-2 is an indicator of classification confidence.  For a fuller description please refer to the product documentation. 

LCM2017 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2017.  These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2017. LCM2017 was simultaneously released with LCM2018 and LCM2019.  These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015.

This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.
description: The 20m Classified Pixels datasets are the most spatially detailed in LCM2017, LCM2018 and LCM2019 product range. All other datasets were derived from these. They give land cover information in 21 classes based on UK Biodiversity Action Plan broad habitats. They result from automatic Random Forest classifications of partially overlapping, rectangular classification scenes and are given as 8-bit, 2-band integer 20m pixel rasters. Band-1 is the most likely land cover class, band-2 is the classification probability associated with this class, rescaled over the interval 0 to 100. Classification scenes comprised per-season Sentinel-2 median top of atmosphere reflectance values resampled to 20m pixel resolution, derived using the Google Earth Engine, combined with regional context layers (for example: terrain, coastal proximity). Overlapping classification results were visually ranked to determine precedence. The best classifications were compiled to form seamless national products for Great Britain and Northern Ireland. Classification used bespoke software integrated with a PostGis spatial database. The 20m rasters were exported from PostGIS using open source gdal tools to give the final product in GeoTiff format. GeoTiff is open standard format for raster data and GeoTiff files can be read by most GIS software.
DOI: 10.15156/bio/sh0162633.10fu
title: SH0162633.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162634.10fu
title: SH0162634.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.