This dataset consists of a vector layer (based on 1 by 1° grid), of modelled daily surface nitrogen dioxide (NO2, ug m-3). A seasonal average value per grid cell was calculated for the grassland growing season (mid-April to mid-July), for the USA and UK, in 2018. Full details about this dataset can be found at https://doi.org/10.5285/d2524c77-c0b6-4228-a743-ec6f16623d80

This dataset contains the areas affected by landslides triggered by Typhoon Parma in the area of Itogon (Benguet, Philippines) between the 2nd and 5th October 2009. The polygons were mapped using Google Earth imagery dated 31 December 2003 for pre-event and images and 31 December 2009 for post-event images. The area has an extension of 150 km2. Full details about this dataset can be found at https://doi.org/10.5285/2e15dbd2-71c3-4e86-aa90-6029d37bd417

This dataset records the Saiga antelope die-off and calving sites in Kazakhstan. It represents the locations (and where available dates) of (i) die-offs and (ii) normal calving events in the Betpak-dala population of the saiga antelope, in which three major mass mortality events have been recorded since 1988. In total, the data contains 214 saiga die-off and calving sites obtained from field visits, aerial surveys, telemetry and literature. Locations derived from field data, aerial surveys or telemetry are polygons representing the actual size and shape of the die-off or calving sites; locations sourced from the literature are point data around which buffers of 6km were created, representing the average size of calving aggregations. Of the 214 locations listed, 135 sites for which environmental data were available were used to model the probability of a die-off event. The collection and use of these data are written up in more detail in papers which are currently under review (when published links will be added to this record). Saiga antelope are susceptible to mass mortality events, the most severe of which tend to be caused by haemorrhagic septicaemia following infection by the bacteria Pasteurella multocida. These die-off events tend to occur in May during calving, when saigas gather in dense aggregations which can be represented spatially as relatively small sites. The Betpak-dala population is one of three in Kazakhstan, located in the central provinces of the country (see map). Full details about this dataset can be found at https://doi.org/10.5285/8ad12782-e939-4834-830a-c89e503a298b

These data are GIS shapefiles which contain geospatial information describing the location and condition of bridges, buildings and roads in Chamoli District, Uttarakhand, India, following the 7th February 2021 avalanche and debris flow hazard cascade (the so-called ‘Chamoli event’). The dataset also contains a GIS shapefile which contains polygon outlines supporting geomorphological analysis of change in river valleys between the avalanche source and the town of Joshimath. The latter is designed to be used in conjunction with the other data resources contained in this data collection. Full details about this dataset can be found at https://doi.org/10.5285/a763e254-c249-4934-b0fb-c3b808b37db6

This dataset consists of a vector layer (based on 1 by 1degree grid), of modelled ozone flux (POD1IAM, mmol m-2), The values per grid cell are Phytotoxic Ozone Dose above a threshold of y (y=1 nmol m−2 sec−1 in this case) for use in large-scale Integrated Assessment Modelling (IAM). The accumulated flux value per 90-day grassland growing season (mid-April to mid-July) is provided per grid cell, for the year 2018, across the UK and USA. Full details about this dataset can be found at https://doi.org/10.5285/afadb068-7e35-4271-bf07-0227d0a7a10f

Erosion risk mapping showing soil erosion potential (tonnes/yr) using the Soil Water Assessment Tool (SWAT) for the Yorkshire River Derwent, UK. The modelled data includes 29 years of weather data (1990-2019). Outputs were validated using SUFI2. This dataset builds on previous modelling using SCIMAP. Full details about this dataset can be found at https://doi.org/10.5285/822646a9-6c20-4755-97af-eb22dd43fee3

This dataset is the 2012 revised Corine Land Cover (CLC) map, consisting of 44 classes in the hierarchical three level Corine nomenclature, produced during the CLC2018 production to improve the CLC2012 inventory. CLC 2018, CLC change 2012-2018 and CLC 2012 revised are three of the datasets produced within the frame of the Copernicus programme on land monitoring. Corine Land Cover (CLC) provides consistent information on land cover and land cover changes across Europe; these two maps are the UK component of Europe. This inventory was initiated in 1985 (reference year 1990) and established a time series of land cover information with updates in 2000, 2006 and 2012 being the last iteration. CLC products are based on photointerpretation of satellite images by national teams of participating countries – the EEA member and cooperating countries – following a standard methodology and nomenclature with the following base parameters: 44 classes in the hierarchical three level Corine nomenclature; minimum mapping unit (MMU) of status layers is 25 hectares; minimum width of linear elements is 100 metres; minimum mapping unit (MMU) for Land Cover Changes (LCC) for the change layers is 5 hectares. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. More information about the Corine Land Cover (CLC) and Copernicus land monitoring data in general can be found at http://land.copernicus.eu/. Full details about this dataset can be found at https://doi.org/10.5285/9bb7caab-764d-407b-9a81-0d758722d900

This dataset includes polygons representing ecosystem types (ET) and their respective ecosystem services (ES) and disservices (EDS) in the Luanhe River Basin, with attributes recording 14 ecosystem types (ET), 11 provisioning services (PS), ten regulating services (RS), five cultural services (CS), 7 Ecological integrity indicators (EI), and 11 ecosystem disservices (EDS). Full details about this dataset can be found at https://doi.org/10.5285/2252d8a4-0ef3-403f-b2c3-3f7acbcac1d5

These spatial layers contain the predicted occurrence and abundance of three heathland shrubs, Arctostaphylos uva-ursi, Vaccinium myrtillus and Vaccinium vitis-idaea identified as susceptible host species for Phytophthora ramorum and Phytophthora kernoviae in Scotland. The distribution models were developed from quadrat vegetation data kindly provided by Scottish Natural Heritage combined with data on climate and soil conditions as well as deer abundance and were fitted using a Bayesian Generalised Mixed Modelling approach adapted for input data on the DOMIN scale. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/5749df3d-000c-445e-a37f-dc0763b4d5ec

This dataset is the 2018 Corine Land Cover map, consisting of 44 classes in the hierarchical three level Corine nomenclature. Corine Land Cover (CLC) 2018, CLC change 2012-2018 and CLC 2012 revised are three of the datasets produced within the frame of the Copernicus programme on land monitoring. Corine Land Cover (CLC) provides consistent information on land cover and land cover changes across Europe; these two maps are the UK component of Europe. This inventory was initiated in 1985 (reference year 1990) and established a time series of land cover information with updates in 2000, 2006 and 2012 being the last iteration. CLC products are based on photointerpretation of satellite images by national teams of participating countries – the EEA member and cooperating countries – following a standard methodology and nomenclature with the following base parameters: 44 classes in the hierarchical three level Corine nomenclature; minimum mapping unit (MMU) of status layers is 25 hectares; minimum width of linear elements is 100 metres; minimum mapping unit (MMU) for Land Cover Changes (LCC) for the change layers is 5 hectares. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. More information about the Corine Land Cover (CLC) and Copernicus land monitoring data in general can be found at http://land.copernicus.eu/. Full details about this dataset can be found at https://doi.org/10.5285/084e0bc6-e67f-4dad-9de6-0c698f60e34d