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.

Seedlings were grown in soil collected from an experiment at Hambleton Forest, North Yorkshire. Soils originated from plots containing either Scots pine or birch monocultures, or a mixture of both species. In the lab, pairs of seedlings of birch and Scots pine were grown as monocultures and mixtures from each of the three plot treatments. The data represent the biomass, leaf C:N ratio and mycorrhizal status determined after 20 weeks. Full details about this dataset can be found at https://doi.org/10.5285/7991871e-382f-422f-b5b2-91b4f6d8598f

This dataset consists of an ecology-focused survey of stillwaters along the rivers Yure and Swale and sediment flux measurements recorded at sites along the river Esk. The dataset results from a study which was part of the Rural Economy and Land Use (RELU) programme. The project analysed the complex network of natural and socio-economic relationships around angling in the river environment, including institutions of governance and land use practices at a range of interconnected scales. The sustainability, integrity and ecological value of river catchments are currently major issues for science. The management of freshwaters and their ecologies requires addressing processes that work across the boundaries between the natural environment, economy and society. This research focused upon these cross-cutting processes in an interdisciplinary, holistic assessment of river environments through the case of angling. Angling benefits from and influences river quality, design and management. It also links urban and rural environments and is an economic driver for the rural economy, involving about 4 million people in England and Wales and contributing 6 billion pounds to the economy through freshwater angling alone. This research aimed to provide insights into how environmental and socio-economic drivers for rural change work. This project therefore aimed to identify and analyse the complex network of influences and feedbacks around angling in the rural environment. These include natural and socio-economic influences, interdisciplinary research from both natural and social science disciplines (aquatic ecology, geomorphology, anthropology, sociology, human geography), as well as stakeholders from government, NGOs and the local community. This project focused upon three rivers in northern England - the Esk, Ure and Swale - in the course of an integrated and fine-grained study. The postal survey and business interviews from this study are available at the UK Data Archive under study number 6580 (see Supplemental). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see Supplemental).

The Land Cover Map 2024 (UK Land Cover Statistics) dataset summarises the coverage of different land cover types across Great Britain and Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. This data is provided in both .csv and geopackage (vector) formats. Statistics are calculated at country, county, and regional (England only) levels from the Land Cover Map 2024 (10 m classified pixels) datasets for Great Britain and Northern Ireland. A full description of this and all UKCEH LCM2024 products are available from the LCM2024 product documentation. In addition to UKCEH as copyright holders, the Land Cover Map 2024 (UK Land Cover Statistics) products use digital boundary products and reference maps. The source of the data is the Office for National Statistics and they are licensed under the Open Government Licence v.3.0. They contain OS data © Crown copyright and database right [2024]. Full details about this dataset can be found at https://doi.org/10.5285/0171ccb2-1c0c-404f-b782-e7204a86a92f