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). Full details about this dataset can be found at https://doi.org/10.5285/8eed6d77-714a-438a-aa65-887b1ef62378

The data describe vegetation outlines and tree tops above 1m in height as polylines and points. Data have been processed from a digital terrain model (DTM) and digital surface model (DSM), converted from raw LiDAR data. The LiDAR dataset was acquired for Cornwall and Devon (all the land west of Exmouth) during the months of July and August 2013. The data were created as part of the Tellus South West project. Full details about this dataset can be found at https://doi.org/10.5285/78dba959-989b-43d4-b4da-efd2506e0c8e

Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ValCalHyp- Validation of the "Smart Vicarious Calibration" (SVC) method and the Quality Indicators Protocol of Hyperspectral Data (EUFAR10_08) project (flight reference: 2010_301). Data were collected over the Toulouse, France area.

Grounding line locations (GLL) data for the Evans and Rutford Glaciers in Antarctica, produced by the ESA Antarctic Ice Sheet Climate Change Initiative (CCI) project. The grounding lines have been derived from satellite observations from the ERS-1/2 and Copernicus Sentinel-1 instruments, acquired between 1995 and 2016.

The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.

Cloud properties derived from the merged series of AVHRR instruments on the NOAA-15 to NOAA-18 satellites by the ESA Cloud CCI project. The L3S dataset consists of data combined (averaged) from into a global space-time grid, with a spatial resolution of 0.5 degrees lat/lon and a temporal resolution of 1 month. This dataset is version 1.0 data from Phase 1 of the CCI project.

The Cloud_cci AVHRR-PMv3 dataset (covering 1982-2016) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on measurements from AVHRR (onboard the NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19 satellites) and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci AVHRR-PMv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. The data in this dataset are a subset of the AVHRR-PM L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003. To cite the full dataset, please use the following citation: Stengel, Martin; Sus, Oliver; Stapelberg, Stefan; Finkensieper, Stephan; Würzler, Benjamin; Philipp, Daniel; Hollmann, Rainer; Poulsen, Caroline (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci AVHRR-PM L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD), DOI:10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003.

The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.

The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.

This dataset contains along-track sea level anomalies derived from satellite altimetry. Altimeter along-track sea level measurements from the RA2 instrument on ENVISAT and the Altika instrument on SARAL satellite missions have been processed to produce high resolution (20 Hz, corresponding to an along-track distance of ~300m) sea level anomalies, in order to provide long-term homogeneous sea level time series as close to the coast as possible in six different coastal regions (North-East Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, South-East Asia and Australia). The product benefits from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections. The main objective of this product is to provide accurate altimeter Sea Level Anomalies (SLA) time series as close to the coast as possible in order to assess whether the coastal sea level trends experienced at the coast are similar to the observed sea level trends in the open ocean and to determine the causes of the potential discrepancies. The Envisat and SARAL/AltiKa missions have the same ground track but the temporal gap between both missions prevents from computing reliable trends during the total period between both missions. This dataset has been produced by the Climate Change Initiative Coastal Sea Level team, within the extension phase of the European Sapce Agency (ESA) Climate Change Initiative.