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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 comprises bird abundance data collected using point count methods in Bedford, Luton and Milton Keynes in the summer of 2013. The purpose of the study was to characterise the variation in breeding bird fauna across a range of urban forms. As well as measuring the birds that were 'really' present, the survey aimed to investigate the birds detectable at times of day when people were more active and more likely to have casual encounters with them. These data were collected as part of the Fragments, Functions and Flows in Urban Ecosystem Services (F3UES) project, as part of the Biodiversity and Ecosystem Service Sustainability (BESS) framework. Full details about this dataset can be found at https://doi.org/10.5285/c4806e25-5325-4b01-8066-91a8fb55eb41
The data describe the ecological responses (invertebrate diversity and biomass, plant diversity, soil characteristics and microbial diversity) to experimental manipulation of floristic diversity and vegetation height in planted urban meadows. The experiment consisted of a replicated set of nine different perennial meadow treatments, sown in six public urban greenspaces in the towns of Bedford and Luton, in the UK. Full details about this dataset can be found at https://doi.org/10.5285/d0741544-cdf3-497d-996b-e30b4b7373c1