This metadata describes the Corine Land Cover changes layer between 2018 and 2024 in raster format developed for different regions in four European Partnership countries (Armenia, Georgia, Republic of Moldova and Ukraine) under the ENI CLC (European Neighbourhood Initiative - Corine Land Cover) pilot project. This dataset was created following the methodology and rules of the European CLC project, namely computer assisted photointerpretation of satellite imagery, standard European level-3 nomenclature, 25 ha minimum mapping unit (MMU) for status layer, 5 ha MMU for change layer, minimum width of linear elements is 100 meters.

These CLC layers have been created in the context of the cooperation between the EEA and four Eastern Partnership countries (Armenia, Georgia, Republic of Moldova and Ukraine), which was implemented through the EU-funded programme "EU4Environment Water & Data". The period of implementation of the project was from 2021 to 2024.

Additional information about CLC product description including mapping guides as well as the corresponding CLC class descriptions can be found at the Copernicus Land Monitoring Service website and the metadata of the relevant Corine Land Cover layers.

This metadata refers to the 'Corine Land Cover Plus Backbone' (CLCplus Backbone), a spatially detailed, large-scale, Earth Observation-based land cover inventory which is produced by the Copernicus Land Monitoring Service (CLMS). The CLCplus Backbone vector is a land cover map that contains vector polygon geometries (minimum mapping unit: 0.5 ha; minimum mapping width: 20 m) and is based on Sentinel satellite time series and a combination of existing reference datasets for geometries containing transportation and hydrological networks. Each polygon represents aggregated landscape objects and contains their dominant land cover among the 18 basic land cover classes. See polygon class codes in the additional information section. In addition, polygons are enriched with land cover fractions from the CLCplus Backbone raster as well as aggregated attributes based on other CLMS and Copernicus products (e.g. topography).

CLCplus Backbone vector is an independent product and its thematic and geometric contents differ from CLCplus Backbone raster and Corine Land Cover.

The CLCplus Backbone vector is available for the 2018 reference year.

You can read more about the product here: https://land.copernicus.eu/en/products/clc-backbone

This metadata refers to the 'Corine Land Cover plus Backbone' (CLCplus Backbone), a spatially detailed, large-scale, Earth Observation-based land cover inventory which is produced by the Copernicus Land Monitoring Service (CLMS). The CLCplus Backbone is a 10m pixel-based land cover map based on Sentinel satellite time series. Each pixel contains the dominant land cover among the 11 basic land cover classes. See pixel class codes in the additional information section.

The product has an update cycle of three years and starting from the 2018 reference year. The update cycle for future products (from 2021 reference year onwards) will be 2 years.

You can read more about the product here: https://land.copernicus.eu/en/products/clc-backbone

This metadata describes the Corine Land Cover 2018 status layer dataset in raster format developed for different regions in four European Partnership countries (Armenia, Georgia, Republic of Moldova and Ukraine) under the ENI CLC (European Neighbourhood Initiative - Corine Land Cover) pilot project. This dataset was created following the methodology and rules of the European CLC project, namely computer assisted photointerpretation of satellite imagery, standard European level-3 nomenclature, 25 ha minimum mapping unit (MMU) for status layer, 5 ha MMU for change layer, minimum width of linear elements is 100 meters.

These CLC layers have been created in the context of the cooperation between the EEA and four Eastern Partnership countries (Armenia, Georgia, Republic of Moldova and Ukraine), which was implemented through the EU-funded programme "EU4Environment Water & Data". The period of implementation of the project was from 2021 to 2024.

Additional information about CLC product description including mapping guides as well as the corresponding CLC class descriptions can be found at the Copernicus Land Monitoring Service website and the metadata of the relevant Corine Land Cover layers.

Corine Land Cover Edition 2018 France Métropolitaine ainsi que la feuille de style .sld et .qml pour Qgis Réalisé par le PMIRG (SNUM du MTES)

The High Resolution Layer Forest Additional Support Layer (FADSL) provides information on trees under agricultural use or in urban context to be excluded from the Forest Type (FTY) product and at 10m spatial resolution. The derivation of Forest Additional Support Layer (FADSL) is based on the spatial intersection of the 10m DLT and TCD layers with CORINE Land Cover (CLC) 2018 and HRL Imperviousness Degree 2018 with 10 m spatial resolution; TCD range of ≥ 10-100%; with a MMW of 10m and no MMU (pixel base). This dataset is provided on a 3-yearly frequency in 10 meter rasters (fully conformant with the EEA reference grid) in 100 x 100 km tiles covering the EEA38 countries. High Resolution Layer Tree Cover and Forest product is part of the European Union’s Copernicus Land Monitoring Service. This dataset includes data from the French Overseas Territories (DOMs)

The High Resolution Layer Forest Additional Support Layer (FADSL) provides information on trees under agricultural use or in urban context to be excluded from the Forest Type (FTY) product and at 10m spatial resolution. The derivation of Forest Additional Support Layer (FADSL) is based on the spatial intersection of the 10m DLT and TCD layers with CORINE Land Cover (CLC) 2018 and HRL Imperviousness Degree 2018 with 10 m spatial resolution; TCD range of ≥ 10-100%; with a MMW of 10m and no MMU (pixel base).

This dataset is provided on a 3-yearly frequency in 10 meter rasters (fully conformant with the EEA reference grid) in 100 x 100 km tiles covering the EEA38 countries.

High Resolution Layer Tree Cover and Forest product is part of the European Union’s Copernicus Land Monitoring Service.

This dataset includes data from the French Overseas Territories (DOMs)

Descarga aquí el metadato:https://aplicaciones.siatac.co:8443/geonetwork/srv/spa/catalog.search#/metadata/13367922-7516-4ae5-ab0d-11792cf6a685El mapa de coberturas de la tierra escala 1:25.000, se realiza mediante la reinterpretación visual de imágenes de satélite Planet Scope de 3 m de resolución basándose en la metodología CORINE LAND COVER, propuesta de clasificación 25k desarrollada por el Instituto SINCHI; de esta manera, el procedimiento consiste en generar una primera capa de coberturas de la tierra como línea base, y luego se actualiza cada seis meses en donde se redelimitan únicamente aquellas unidades que cambiaron de cobertura. Adicionalmente, la estructuración de la información se hace de acuerdo las reglas de generalización para la escala 1:25.000 (área mínima cartografiable de 1,5 ha, reinterpretando cambios superiores a 0,3 ha respecto al mapa del periodo anterior, territorios artificializados con áreas mayores a 0,3 ha y coberturas tipo lineal con una ancho mínimo superior a 25 m). De igual manera, la información es sometida a estrictos procesos de control de calidad en cada una de las etapas de producción (descarga de imágenes planet scope, cubrimiento del área de estudio, calidad en la interpretación y reinterpretación, revisión topológica, empalmes y cruces espaciales.

Net ecosystem productivity (gross primary production minus respiration). Positive fluxes are emissions, negative mean uptake. These fluxes are the result of the SiB4 (Version 4.2-COS, hash 1e29b25, https://doi.org/10.1029/2018MS001540) biosphere model, driven by ERA5 reanalysis data at a 0.5x0.5 degree resolution. The NEP per plant functional type are distributed according to the high resolution CORINE land-use map (https://land.copernicus.eu/pan-european/corine-land-cover), and aggregated to CTE-HR resolution. For more information, see https://doi.org/10.5281/zenodo.6477331 van der Woude, A., 2022. Near real time fluxes. https://doi.org/10.18160/20Z1-AYJ2

Extended label set of UC Merced for Hierarchical Multi-Label Classification

This dataset contains an extended version of the original label set of UC Merced for Hierarchical Multi-Label Classification.

  Dataset creation

It was created based on the CORINE Land Cover database of the year 2018 (CLC 2018), which provides detailed information about the land cover classes at multiple levels of the hierarchy

  Loading the Dataset

To load the dataset into your project… See the full description on the dataset page: https://huggingface.co/datasets/marjandl/UCM-HMLC.

Extended label set of BigEarthNet-43 for Hierarchical Multi-Label Classification

This dataset contains an extended version of the original label set of BigEarthNet-43 for Hierarchical Multi-Label Classification.

  Dataset creation

It was created based on the CORINE Land Cover database of the year 2018 (CLC 2018), which provides detailed information about the land cover classes at multiple levels of the hierarchy

  Loading the Dataset

To load the dataset into your… See the full description on the dataset page: https://huggingface.co/datasets/marjandl/BigEarthNet-43-HMLC.

The European geodiversity data provides a novel perspective on the diversity of non-living nature over large spatial extents. These data describe geological, pedological, geomorphological, and hydrological diversity, including 78 different geofeatures. Geofeatures refer to individual features that each component of geodiversity (geology, pedology, geomorphology, and hydrology) consists of, such as soil types in the case of pedology. This standardized and accessible geodiversity dataset facilitates comparability for geodiversity research across Europe and can be used for multiple purposes, from studying geodiversity patterns to geodiversity–biodiversity relationship and more. Moreover, the methodology (described in Toivanen et al. 2024) establishes a grid-based approach for quantifying geodiversity, which is suitable for large extents and can be applied in other regions worldwide. This grid-based geodiversity dataset, available at resolutions of 1-km and 10-km, includes ready-to-use georichness variables (as GEOtiff files), and provides information on the presence and coverage of individual geofeatures that can be used to calculate different measures of geodiversity (as csv files). The data on georichness can be utilized in its entirety, representing the overall geodiversity, or with selected geodiversity components as individual richness layers describing geological, pedological, geomorphological or hydrological feature richness. One key objective of this geodiversity data is to provide complimentary environmental variables for biodiversity modelling and conservation studies. However, the choice of geodiversity data (richness or other index), the scale of analysis (1-km or 10-km), and the specific variables (overall geodiversity or individual components) should be determined by the research question and context. This is a dataset from: Toivanen, M. et al. (2024). Geodiversity data for Europe. Philosophical Transactions of the Royal Society A. https://dx.doi.org/10.1098/rsta.2023.0173 (accepted for publication 2023-10-19) Methods We used global and continental open-access data as the basis of our European geodiversity data to describe geological (IHME1500 Lithology), pedological (SoilGrids 2.0), geomorphological (Geomorpho90m), and hydrological (EU-Hydro, Corine Land Cover 2018, IHME1500 Aquifer-type) diversity. EEA Reference Grids were used as the basis of our calculations to produce the raster layers of terrestrial geodiversity at two resolutions (1-km and 10-km) through zonal calculations. All analyses were done with ESRI ArcGIS Pro version 2.8. The spatial extent of the data follows Corine Land Cover 2018 landcover data produced by the European Environment Agency (EEA). Please see the related manuscript (Toivanen et al. 2024) for detailed description of the methodology.

To improve the sustainability of the European livestock sector we need improved knowledge on livestock density, and also on the grazing patterns. Here we provide spatially explicit data on the distribution of cattle, sheep and goats, developed by combining agricultural and veterinary statistics, in-situ data, expert surveys and machine learning. The data allow for the differentiation between livestock that are grazing on semi-natural areas and managed grasslands, versus those that do not graze and are kept indoors.

This dataset covers all European Union Member States and the United Kingdom, and presents the spatial distribution of cattle, sheep and goat density for approximately the year 2020. Livestock density was allocated on the Corine Land Cover data, resulting in a data-set with a 100 m resolution (EPSG: 3035 - ETRS89-extended / LAEA Europe).

Together with the livestock density maps, we also provide spatial data on the probability for grazing, and allocated grazed and non grazed areas.

File description:

The data-set consists of the following files:

• clc_forage_mask.tif , forage areas mask for EU, based on selected Corine Land Cover classes (not including seminatural land cover areas such as natural grasslands...). This was developed by surveying grazing, grassland and livestock experts from all EU Member States and the United Kingdom. More info in the upcoming paper and in the linked paper below (Malek et al. 2024). Values are the same as in the Corine Land Cover data.
• grazing_probability.tif , grazing probability map, indicating how likely each location in the EU+UK is grazed
• allocated_grazing.tif , allocated grazing map, indicating which areas are grazed and which are not

• cattle density maps:
  • cattle_grazing.tif , cattle grazing on managed forage areas
  • cattle_other.tif , cattle kept indoors, receiving feed from managed forage areas
  • cattle_seminatural.tif , cattle grazing in semi-natural areas
  • cattle_mosaic_categorical.tif (with a legend file) , combined categorical map for all cattle types.

• sheep and goat density maps:
  • sheep_goat_other.tif , sheep and goat density
  • sheep_goat_seminatural.tif , sheep and goat grazing in seminatural areas

Descarga aquí el metadato:https://aplicaciones.siatac.co:8443/geonetwork/srv/spa/catalog.search#/metadata/eb685422-4858-41c2-9f0f-15e4806877cbCapa de Coberturas de la Tierra del año 2024 de la Región de la Amazonia escala 1:100.000, con base en la interpretación de imágenes satelitales para el periodo 2024 del programa Landsat 8 (OLI), de la selección Path-Row (4-57, 4-58, 4-59, 4-60, 4-61, 4-62, 4-63, 9-59, 9-60, 7-58, 7-59, 7-60, 7-61, 5-57, 5-58, 5-59, 5-60, 5-61, 5-62, 3-57, 3-58, 3-59, 8-58, 8-59, 8-60, 6-57, 6-58, 6-59, 6-60, 6-61, 6-62), e implementación de la metodología CORINE Land Cover adaptada para Colombia. Esta clasificación de coberturas se hizo a partir de la interpretación visual de las imágenes, aplicando la leyenda del mapa de coberturas a escala 1:100.000 y la metodología PIAO, que permite interpretar, digitalizar y capturar las coberturas de forma visual, utilizando la combinación de las bandas 4, 5, 3, (NIR, SWIR1, R). La estructuración de la información se hizo según las reglas de generalización para escala 1:100.000 y siguiendo la codificación de cobertura y diligenciando los campos de la tabla de atributos. A partir de estos campos, se calculó el atributo de agrupación con el que se realizan los análisis estadísticos por grandes grupos de coberturas. Igualmente, se realiza una clasificación de las coberturas de acuerdo a la condición que presenta: natural, seminatural o transformada. Finalmente, esta capa pasó por un proceso de control de calidad, empalme e interventoría, en el que se evaluó la calidad temática, topológica, de empalmes y de mosaico final. La actualización de la información para el mapa de los periodos 2002, 2007 y 2012, se realizó con una temporalidad de 5 años. A partir del 2012, la actualización se realizó cada dos años y a partir del año 2021 se realiza una actualización en cada año impar para 17 municipios de la Amazonia los cuales tienen alta dinámica de transformación.Diccionario de datos:objectid: Corresponde al identificador propio de cada registro dentro de la capa de informaciónarea_ha: Corresponde al área en hectáreasarea_km2: Corresponde al área en kilómetros cuadradoscodigo: Corresponde al código de la leyenda de CORINE Land Cover a escala 1:100.000cobertura: Corresponde al nombre y tipo de coberturacondicion: Corresponde a la condición "natural, seminatural y transformada"cob_agrup: Corresponde a la cobertura agrupada dentro de la leyenda de CORINE Land Cover a escala 1:100.000shape: Corresponde a geometría del elementost_area(shape): Corresponde al área del elementost_length(shape): Corresponde al perímetro del elementoFuente:Modelos de Funcionamiento y Sostenibilidad del Laboratorio SIG y SRBogotá D.C., Colombia siatac.coCalle 20 # 5 - 44Código Postal: 110311 Teléfono: +57 (1) 4442060Horario de atención: 8:00 am - 5:00 pm de Lunes a Viernes Información de contacto:Establecer previo contacto telefónico o a través de correo electrónico, para realizar la solicitud o fijar una cita en el horario de atención.

Descarga aquí el metadato:https://aplicaciones.siatac.co:8443/geonetwork/srv/spa/catalog.search#/metadata/eb685422-4858-41c2-9f0f-15e4806877cbCapa de Coberturas de la Tierra del año 2024 de la Región de la Amazonia escala 1:100.000, con base en la interpretación de imágenes satelitales para el periodo 2024 del programa Landsat 8 (OLI), de la selección Path-Row (4-57, 4-58, 4-59, 4-60, 4-61, 4-62, 4-63, 9-59, 9-60, 7-58, 7-59, 7-60, 7-61, 5-57, 5-58, 5-59, 5-60, 5-61, 5-62, 3-57, 3-58, 3-59, 8-58, 8-59, 8-60, 6-57, 6-58, 6-59, 6-60, 6-61, 6-62), e implementación de la metodología CORINE Land Cover adaptada para Colombia. Esta clasificación de coberturas se hizo a partir de la interpretación visual de las imágenes, aplicando la leyenda del mapa de coberturas a escala 1:100.000 y la metodología PIAO, que permite interpretar, digitalizar y capturar las coberturas de forma visual, utilizando la combinación de las bandas 4, 5, 3, (NIR, SWIR1, R). La estructuración de la información se hizo según las reglas de generalización para escala 1:100.000 y siguiendo la codificación de cobertura y diligenciando los campos de la tabla de atributos. A partir de estos campos, se calculó el atributo de agrupación con el que se realizan los análisis estadísticos por grandes grupos de coberturas. Igualmente, se realiza una clasificación de las coberturas de acuerdo a la condición que presenta: natural, seminatural o transformada. Finalmente, esta capa pasó por un proceso de control de calidad, empalme e interventoría, en el que se evaluó la calidad temática, topológica, de empalmes y de mosaico final. La actualización de la información para el mapa de los periodos 2002, 2007 y 2012, se realizó con una temporalidad de 5 años. A partir del 2012, la actualización se realizó cada dos años y a partir del año 2021 se realiza una actualización en cada año impar para 17 municipios de la Amazonia los cuales tienen alta dinámica de transformación.Diccionario de datos:objectid: Corresponde al identificador propio de cada registro dentro de la capa de informaciónarea_ha: Corresponde al área en hectáreasarea_km2: Corresponde al área en kilómetros cuadradoscodigo: Corresponde al código de la leyenda de CORINE Land Cover a escala 1:100.000cobertura: Corresponde al nombre y tipo de coberturacondicion: Corresponde a la condición "natural, seminatural y transformada"cob_agrup: Corresponde a la cobertura agrupada dentro de la leyenda de CORINE Land Cover a escala 1:100.000shape: Corresponde a geometría del elementost_area(shape): Corresponde al área del elementost_length(shape): Corresponde al perímetro del elementoFuente:Modelos de Funcionamiento y Sostenibilidad del Laboratorio SIG y SRBogotá D.C., Colombia siatac.coCalle 20 # 5 - 44Código Postal: 110311 Teléfono: +57 (1) 4442060Horario de atención: 8:00 am - 5:00 pm de Lunes a Viernes Información de contacto:Establecer previo contacto telefónico o a través de correo electrónico, para realizar la solicitud o fijar una cita en el horario de atención.

Podrobná bezešvá vrstva krajinného pokryvu dělící území ČR do 40 kategorií. Sestaveno v rámci Integrovaného projektu LIFE Jedna příroda (LIFE17 IPE/CZ/000005). Copyright: © AOPK ČR 2024 © CzechGlobe 2021, s využitím vlastních dat a dat ZABAGED (© ČÚZK 2023), Corine Land Cover 2018 (© EEA 2023), Urban Atlas 2018 (© EEA 2023), LPIS (© SZIF 2023), ÚHÚL (© ÚHÚL 2023). Tato vrstva navazuje na předchozí verze KVES 2013, 2021 a 2022. Hlavní rozdíly mezi KVES 2022 a KVES 2023: aktualizace dat. Obalová zóna na kolem Souvislé a Nesouvislé zástavby větší o 15 m. Verze 2023 nezahrnuje žádná data RUIAN, pro odstranění mezer ve vrstvě byla použita data ZABAGED, Urban Atlas, vrstva mapování biotopů, Corine Land Cover.