Agrimetrics Developer Portal - Data Sources
Agrimetrics Developer Portal - Data Sources
Data Sources
Agrimetrics combines data from various open and licensed data sources, including proprietary datasets created by Agrimetrics or our partners to address gaps in the agri-food data landscape. We collect data, but also connect it by using pioneering digital technologies that enable individual pieces of data to be linked to each other, across sources in a highly flexible and adaptable way. Traditional tabular databases are not able to do this, which has dramatically curtailed the sector's ability to exploit diverse sources of information.
Agrimetrics' current products include data from the following sources.
Field Boundaries
| Source | Agrimetrics | 
| Reference | https://developer.agrimetrics.co.uk/products/field-boundaries | 
| Coverage | UK | 
| Time | 2019 | 
Historical weather
| Source | UK Met Office - UKCP09 datasets | 
| Reference | https://www.metoffice.gov.uk/climate/uk/data/ukcp09 | 
| Coverage | UK | 
| Resolution | 5km grid | 
| Time | Daily data, aggregated by Agrimetrics in some products to monthly averages. | 
Recent weather
| Source | UK Met Office - DataPoint datasets | 
| Reference | https://www.metoffice.gov.uk/datapoint/product/uk-hourly-site-specific-observations | 
| Coverage | UK | 
| Resolution | ~140 point locations | 
| Time | Hourly data, aggregated by Agrimetrics in some products to daily values (mean, min and max). | 
Recent rainfall
| Source | Environment Agency | 
| Reference | https://environment.data.gov.uk/flood-monitoring/doc/rainfall | 
| Coverage | England | 
| Resolution | ~1000 point locations | 
| Time | Quarter-hourly data, aggregated by Agrimetrics in some products to daily totals. | 
Solar Radiation
| Source | NASA | 
| Reference | https://power.larc.nasa.gov/ | 
| Coverage | England | 
| Resolution | 0.5 degree grid | 
| Time | Daily | 
Short-term forecast
| Source | MET Norway - Weather API | 
| Reference | https://api.met.no/ | 
| Coverage | UK | 
| Resolution | 5km grid | 
| Time | Hourly and three-hourly data (depending on length of range) aggregated by Agrimetrics to daily values. | 
Soil Texture
| Source | SoilGrids | 
| Reference | ftp://ftp.soilgrids.org | 
| Coverage | UK | 
| Resolution | 250m grid | 
| Time | Modelled in 2017 using available physical sample points. | 
Soil Carbon
| Source | UKRI Centre for Ecology & Hydrology | 
| Reference | https://catalogue.ceh.ac.uk/download?fileIdentifier=d44373e1-23ac-4730-b6db-76c701a9426d_carbon | 
| Coverage | England | 
| Resolution | 1km grid | 
| Time | Modelled across England based on samples taken nationally in 2007. | 
Soil Nitrogen
| Source | UKRI Centre for Ecology & Hydrology | 
| Reference | https://catalogue.ceh.ac.uk/download?fileIdentifier=d44373e1-23ac-4730-b6db-76c701a9426d_nitrogen | 
| Coverage | England | 
| Resolution | 1km grid | 
| Time | Modelled across England based on samples taken nationally in 2007. | 
Soil pH
| Source | UKRI Centre for Ecology & Hydrology | 
| Reference | https://catalogue.ceh.ac.uk/download?fileIdentifier=d44373e1-23ac-4730-b6db-76c701a9426d_ph | 
| Coverage | England | 
| Resolution | 1km grid | 
| Time | Modelled across England based on samples taken nationally in 2007. | 
Soil Phosphorus
| Source | UKRI Centre for Ecology & Hydrology | 
| Reference | https://catalogue.ceh.ac.uk/download?fileIdentifier=d44373e1-23ac-4730-b6db-76c701a9426d_phosphorus | 
| Coverage | England | 
| Resolution | 1km grid | 
| Time | Modelled across England based on samples taken nationally in 2007. | 
Soil bacterial diversity
| Source | UKRI Centre for Ecology & Hydrology | 
| Reference | https://catalogue.ceh.ac.uk/download?fileIdentifier=d44373e1-23ac-4730-b6db-76c701a9426d_bacteria | 
| Coverage | England | 
| Resolution | 1km grid | 
| Time | Modelled across England based on samples taken nationally in 2007. | 
Soil invertebrate abundance
| Source | UKRI Centre for Ecology & Hydrology | 
| Reference | https://catalogue.ceh.ac.uk/download?fileIdentifier=d44373e1-23ac-4730-b6db-76c701a9426d_inverts | 
| Coverage | England | 
| Resolution | 1km grid | 
| Time | Modelled across England based on samples taken nationally in 2007. | 
Priority Habitats
| Source | Natural England | 
| Reference | https://data.gov.uk/dataset/4b6ddab7-6c0f-4407-946e-d6499f19fcde/priority-habitat-inventory-england | 
| Coverage | UK | 
| Resolution | Boundary polygons | 
| Time | 1999-2015 | 
Water Quality
| Source | Environment Agency | 
| Reference | https://data.gov.uk/dataset/298258ee-c4a0-4505-a3b5-0e6585ecfdb2/wfd-river-waterbody-catchments-cycle-2 | 
| Coverage | England | 
| Resolution | Boundary polygons and tabular data | 
| Time | 2014 | 
Historical Crops
| Source | Rural Payments Agency | 
| Reference | https://data.gov.uk/search?q=crome | 
| Coverage | England | 
| Resolution | 40m hex grid | 
| Time | 2016,2017,2018 | 
Altitude
| Source | EarthEnv | 
| Reference | http://www.earthenv.org/DEM | 
| Coverage | England | 
| Resolution | 90m grid | 
| Time | 2014 | 
Census
| Source | Office for National Statistics | 
| Reference | https://www.ons.gov.uk/census/2011census | 
| Coverage | England | 
| Resolution | UK Parish | 
| Time | March 2011 | 
Broad Habitat Classification
| Source | Land Cover Map (LCM), NERC (CEH) | 
| Reference | https://eip.ceh.ac.uk/lcm | 
| Coverage | England | 
| Resolution | UK Parish | 
| Time | 2015 | 
Crop Distribution
| Source | Land Cover plus: Crops, NERC (CEH) | 
| Reference | https://www.ceh.ac.uk/crops2016 | 
| Coverage | England | 
| Resolution | UK Parish | 
| Time | 2016 | 
The data as presented in our products may be the result of further aggregation or transformation by Agrimetrics, including deriving additional parameters from calculations or modelling using data from one or more source as input. Common transformations are described here.
Where the source has no data (for example, environmental sensor error at a location on a particular day, or limits to the geographic coverage), Agrimetrics will normally preserve this gap faithfully in the data we provide, rather than interpolating data ourselves to fill the gap. This is considered safer, in most cases, than adopting data interpolation methods that may be different to the original source's methods and may cause inconsistencies. It also ensures that users are clear about what data is real, rather than silently replacing missing actuals with synthetic values that may be less reliable.
Updated about 1 month ago
