3b44375a-cbe6-468c-9395-41471054d0f3 English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2025-11-13T16:17:10 UK GEMINI 2.3 OSGB 1936 / British National Grid Multi-tier archetypes to characterise British landscapes, farmland and farming practices 2022-07-11 publication https://catalogue.ceh.ac.uk/id/3b44375a-cbe6-468c-9395-41471054d0f3 10.5285/3b44375a-cbe6-468c-9395-41471054d0f3 doi: Goodwin, C.E.D., Bütikofer, L., Hatfield, J.H., Richter, G.M., Redhead, J.W. (2022). Multi-tier archetypes to characterise British landscapes, farmland and farming practices. NERC EDS Environmental Information Data Centre 10.5285/3b44375a-cbe6-468c-9395-41471054d0f3 This dataset consists of landscape and agricultural management archetypes (1 km resolution) at three levels, defined by different opportunities for adaptation. Tier 1 archetypes quantify broad differences in soil, land cover and population across Great Britain, which cannot be readily influenced by the actions of land managers; Tier 2 archetypes capture more nuanced variations within farmland-dominated landscapes of Great Britain, over which land managers may have some degree of influence. Tier 3 archetypes are built at national levels for England and Wales and focus on socioeconomic and agro-ecological characteristics within farmland-dominated landscapes, characterising differences in farm management. The unavailability of several input variables for agricultural management prevented the generation of Tier 3 archetypes for Scotland. The archetypes were derived by data-driven machine learning. The three tiers of archetypes were analysed separately and not as a nested structure (i.e. a single Tier 3 archetype can occur in more than one Tier 2 archetype), predominantly to ensure that archetype definitions were easily interpreted across tiers. Full details about this dataset can be found at https://doi.org/10.5285/3b44375a-cbe6-468c-9395-41471054d0f3 Goodwin, C. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0003-0093-9838 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information pointOfContact Goodwin, C.E.D. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0003-0093-9838 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Bütikofer, L. Rothamsted Research lucabutikofer@gmail.com https://orcid.org/0000-0001-8220-7520 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Hatfield, J.H. University of York jack.hatfield@york.ac.uk https://orcid.org/0000-0002-6361-0629 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Richter, G.M. Rothamsted Research goetz.richter@rothamsted.ac.uk https://orcid.org/0000-0003-2180-9514 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Redhead, J.W. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0002-2233-3848 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC EDS Environmental Information Data Centre info@eidc.ac.uk publisher UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk owner Rothamsted Research EMAIL NOT PROVIDED owner Agricultural and Aquaculture Facilities theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication AgLand Archetypes Land systems Great Britain Farming otherRestrictions no limitations otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions If you reuse this data, you should cite: Goodwin, C.E.D., Bütikofer, L., Hatfield, J.H., Richter, G.M., Redhead, J.W. (2022). Multi-tier archetypes to characterise British landscapes, farmland and farming practices. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/3b44375a-cbe6-468c-9395-41471054d0f3 grid 1000 English utf8 farming -8.648 1.768 49.864 60.861 TIFF NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://catalogue.ceh.ac.uk/datastore/eidchub/3b44375a-cbe6-468c-9395-41471054d0f3 Download the data Download a copy of this data fileAccess https://data-package.ceh.ac.uk/sd/3b44375a-cbe6-468c-9395-41471054d0f3.zip Supporting information Supporting information available to assist in re-use of this dataset information dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 Archetype data were generated from various spatial socioeconomic and bio-physical layers. These data were analysed using Self-Organising Maps (SOMs), which reduce the dimensions and cluster the data into similar groupings. This creates a pre-set number of Land System Archetypes, each associated with a group of representative 1km cells, at each tier. SOMs were run iteratively 1000 times to gain a measure of the consistency of the production of each set of Archetypes. Data are provided with a measure (Euclidean distance) of the accuracy of the assignment of archetypes for each 1km cell. Sensitivity analyses were conducted to test the inclusion of different data.