The dataset shows larger expanses of bare peat across Scotland from Sentinel 2 imagery taken in summer 2018. Resolution of 10m x 10m Sentinel 2 pixels. Produced by GIG Earth Observation team for the Peatland Action project to be used at a regional scale to identify those parts of Scotland with the most exposed peat.

The Standing Waters Sample Points dataset is a GIS dataset of survey sample locations used during the course of the Scottish Loch Survey Project. The statutory nature conservation agencies in Scotland, England and Wales have a long history of carrying out routine aquatic plant (macrophyte) surveys of lakes. This involves identifying and estimating the abundance of emergent, submerged, floating leaved, and free-floating macrophytes that grow in or near the water. The results of these surveys are held in the Standing Waters Database which is available to view on the SNH website. (http://gateway.snh.gov.uk/pls/apex_cagdb2/f?p=111:1000:1289803086875801).

The data contains boundaries of Wild Land Areas in Scotland as determined by their level of naturalness, remoteness, ruggedness and lack of built modern artefacts. Boundaries should be considered as ‘fuzzy’ rather than definitive to reflect the transitional nature of wild land. It is an updateand replacementto the previously published Core Areas of Wild Land(CAWL)produced in 2013. Note that the areas have been renumbered sequentially and differ from those on the CAWL map.

Landscape Character Assessment (LCA) is a recognised technique which identifies areas with a distinct composition of inter-related natural, physical, cultural and historical characteristics. A National Programme of LCAs was initiated by SNH in 1994 covering 29 regional studies carried out with local authorities and other organisations. Although the broad methodology is similar for each study (i.e. carried out in accordance with published guidance), there is not complete consistency in the naming and describing of LCTs. The 2010 Loch Lomond and the Trossachs (LLTT) LCA dataset sits alongside the National dataset, and is captured at a higher resolution. This dataset should be used in conjuction with the LLTT LCA 2010 Report.