cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0162604.10fu
title: SH0162604.10FU

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/e5632f1b-040c-4c39-8721-4834ada6046a
title: Land Cover Map 2019 (1km summary rasters, GB and N. Ireland)

description: This 1 km summary pixel data set represents the land surface of Great Britain and Northern Ireland, classified using two classification schemas, target and aggregate classes. The target class schema comprise 21 UKCEH land cover classes based upon Biodiversity Action Plan broad habitats. The aggregate class schema comprises 10 aggregate classes that are groupings of the 21 target classes. The aggregate classes group some of the more specialised target classes into more general classes. For example, the five coastal classes in the target class are grouped into a single aggregate class.

The 1km percentage product provides the percentage cover for each of the 21 land cover classes for 1km x 1km pixels. This product contains one band per habitat class, producing 21 and 10 band images for the target and aggregate class products respectively. The 1km dominant coverage product is based on the 1km percentage product, and reports the land cover class with the highest percentage cover for each 1km pixel. A full description of this and all UKCEH LCM2019 products are available from the LCM2017-19 product documentation.
description: UKCEH's automated land cover algorithms classify 10m pixels across the whole of UK. 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 10 m pixel classification into a land parcel framework (the LCM2019 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 1 km percentage and dominant products are created by calculating the percentage cover for each land cover classes for every 1km x 1km pixel, then reporting the dominant land cover class with the highest percentage cover for each 1km pixel.
DOI: 10.5285/f2f646d3-cc5a-4676-8194-34dbfa1c2874
title: Land Cover Map 2000 (1km percentage aggregate class, GB)

description: This dataset consists of a 1km resolution raster version of the Land Cover Map 2000 for Great Britain. The raster consists of 10 bands. Within each band, each 1km pixel represents a percentage cover value for one of 10 aggregate classes. The aggregate classes are aggregations of the 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. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB). Like the earlier 1990 products, 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 1-11 rather than 0-10 and therefore each band relates to the one below it in the sub class code list.
description: In a major development of the 1990 methods, 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 the online supporting documentation.
DOI: 10.15156/bio/sh0162605.10fu
title: SH0162605.10FU

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/a1f88807-4826-44bc-994d-a902da5119c2
title: Land Cover Map 2007 (25m raster, GB) v1.2

description: This dataset consists of a 25m resolution raster version of the Land Cover Map 2007 for Great Britain. Each 25m pixel represents a 25m area of land cover target class, 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 LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 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. LCM2007 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 LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. 
description: LCM2007 uses a spatial framework based on OS MasterMap (R). MasterMap was generalised to remove unnecessary detail, then the framework was segmented according to the underlying satellite data to split areas of non-uniform landscape. The data was classified according to a parcel-based supervised maximum likelihood classification procedure. The raster products are derived from the vector products. See online supporting information for further details. Version 1.2 includes the addition of OS tiles HZ and NW.
DOI: 10.5285/becb5f16-948f-407b-8fa3-f7762ba6efb6
title: Land Cover Map 2023 (25m rasterised land parcels, N. Ireland)

description: This is a 25m pixel data set representing the land surface of Northern Ireland, 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 LCM2023 products are available from the LCM2023 product documentation.
description: UKCEH's automated land cover algorithms classify 10 m pixels across the whole of UK. Training data were automatically selected from stable land covers over the interval of 2020 to 2022. 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 10 m pixel classification into a land parcel framework (the LCM2023 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 pixelating the corresponding land parcel product.
DOI: 10.5285/e44ae9bd-fa32-4aab-9524-fbb11d34a20a
title: Land Cover Map 2021 (10m classified pixels, N. Ireland)

description: This is a 10m pixel data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a two-band raster in GeoTiff format. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover. A full description of this and all UKCEH LCM2021 products are available from the LCM2021 product documentation.
description: UKCEH's automated land cover algorithms classify 10 m pixels across the whole of UK. Training data were automatically selected from stable land covers over the interval of 2018 to 2020. 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 10 m pixel classification into a land parcel framework (the LCM2021 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 accompanying this dataset.

The 25 m rasterised land parcels product is created by pixelating the corresponding land parcel product.
DOI: 10.5285/6c22cf6e-b224-414e-aa85-900325baedbd
title: Land Cover Map 2020 (25m rasterised land parcels, GB) 

description: This is a 25m pixel data set representing the land surface, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats.  It is a three-band dataset 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 LCM2020 products are available from the LCM2020 product documentation.
description: UKCEH's automated land cover classification algorithms generated the 10m classified pixels, from which all remaining products were generated. Training data for classification 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.

This dataset represents LCM2020 25m rasterised land parcels.  It was produced by rasterising three properties of the LCM2020 Classified Land Parcels GB product (_mode, _conf and _purity).
DOI: 10.5285/cf5050d8-495d-45a6-9e2e-bba5239284c2
title: Land Cover Map 2018 (20m classified pixels, N. Ireland)

description: This is the 20m classified pixels dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Northern Ireland. It describes Northern Ireland's land cover in 2018 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.  

LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018.  These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019.  These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Northern Ireland (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/sh0162606.10fu
title: SH0162606.10FU

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: 10.5285/17223091-ca33-41f8-bd5b-bdd2a222cdae
title: Land Cover Map 2023 (10m classified pixels, N. Ireland)

description: This is a 10m pixel data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a two-band raster in GeoTiff format. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover. A full description of this and all UKCEH LCM2023 products are available from the LCM2023 product documentation.
description: UKCEH's automated land cover algorithms classify 10 m pixels across the whole of UK. Training data were automatically selected from stable land covers over the interval of 2020 to 2022. 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 10 m pixel classification into a land parcel framework (the LCM2023 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 25m rasterised land parcels product is created by pixelating the corresponding land parcel product.
DOI: 10.15156/bio/sh0162607.10fu
title: SH0162607.10FU

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/bb381b5b-d44e-4dbd-a9d1-efffd4c3e4a8
title: Land Cover Map 1990 (1km percentage target class, GB) v2

description: This dataset consists of the 1km raster, percentage target class version of the Land Cover Map 1990 (LCM1990) for Great Britain. The 1km percentage product provides the percentage cover for each of 21 land cover classes for 1km x 1km pixels. This product contains one band per target habitat class (producing a 21 band image). 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 percentage target class is produced from the 25m raster (which is derived from the vector product) by:
1. Using gdal_calc to split the 21 target classes into 21 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 21 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 21 bands, where each band provides the percentage cover for the class i.e. band 1 provides percentage cover for class 1 etc.