The RPA CROME GOP is a simple point dataset, that marks the location of observations made by surveyors in a sample of parcels and records the land cover according to set criteria. It has been maintained by RPA Geospatial Services since 2015. RPA currently collects ground observation data from the following source: • Agricultural parcels eligible for the Control with Remote Sensing (CwRS) element of the Basic Payment Scheme (BPS), and that fall within zones selected for monitoring claims. The locations and size of these zones vary from year to year. The field surveys for are carried out on RPA’s behalf by Cyient Europe Ltd. They have been acquired for both Control with Remote Sensing (CwRS) and for Commons Eligibility Mapping programmes that have been completed during the year. The points are attributed with: • Parcel reference ID (as with RPA Parcel Points) • Crop or land cover observed to be / have been growing at that location • Date of observation • Whether observations were made by RPA or an external surveyor • Any additional comments Two versions will be made available: one with photos of the land cover attached (RPA_CROME_GOP_2023_FULL) and the other with them removed (RPA_CROME_GOP_2023_Basic).
The data for the CwRS programme is used in the production of the Crop Map of England (CROME) which is publicly available and has historically been used as part of CwRS for the Basic Payment Scheme (BPS). It is intended that releasing the ground observations would benefit research in automation, machine learning, and our national food production. RPA’s GOP use the Open Government Licence v3.0 as used by other publicly accessible data on the Defra Data Services Platform and will be updated approximately every year, subject to the continuation of current policies.

The RPA Ground Observation Points (GOP) is a point dataset, that represents the location of observations made by surveyors in a sample of parcels and records the land cover according to set criteria. Over 11,000 locations were visited to assess the accuracy and maintain the quality of features in Crop map of England (CROME). In 2024, observations contain evidence of mowing and harvest events on grassland and arable lands respectively. The GOP dataset has been maintained by RPA Geospatial Services since 2015. Ground observation points are randomly distributed within 32 zones across England. RPA's GOP data collection policies now enables annual visit to the same locations and as such GOPs are mostly fixed with yearly updates to capture the operational needs of RPA. This could enable long-term monitoring of land use and help with training deep learning models. The field surveys are carried out on RPA’s behalf by a contractor Cyient Europe Ltd. In previous years they have been acquired for both Control with Remote Sensing (CwRS) and for Commons Eligibility Mapping programmes that have been completed during the year. The points are attributed with: i) Parcel reference ID (as with RPA Parcel Points) ii) Crop or land cover observed to be / have been growing at that location iii) Farm / land management practices (Events) at that location iv) Date of observation v) Description of observation vi) Confirmation technique in current year vii) Confidence of observation and viii) Whether observations were made by RPA or an external client. There are no publicly available supporting photographs in this version. The Crop Map of England (CROME) is publicly available and has historically been used as part of CwRS for BPS. It is intended that releasing the ground observations would benefit research in automation, machine learning, and national food production system. RPA’s GOP use the Open Government Licence v3.0 as used by other publicly accessible data on the Defra Data Services Platform and would be updated approximately every year. Attribution statement: © Rural Payments Agency copyright and/or database right 2024. All rights reserved.

The VDEQ provided grant funds to Charles City to support the development of improved Chesapeake Bay Preservation District Area maps ( Resource Protection Area and Resource Management Area) GIS map overlays and digital datasets including analysis to generate a new RPA map and meta data using off-site publicly available mapping (soils, wetlands, USGS streams, floodplains, topography and other environmental constraints).

There are approximately 2.6 million agricultural land parcels in England, and the Parcel Points (England) point dataset represents the approximate centres, or centroids of these parcels. The number of agricultural parcels varies over time as fields are split or joined consequently creating new fields with new centroids. Some parcels may be sold for development and are no longer available for agricultural use, occasionally land that was previously developed may return to agriculture, e.g. disused airfields.

Parcel Points is a simple point dataset that uses the centres of agricultural parcels attributed only with the parcel reference ID. Parcel points are categorised according to county and are available as England-wide coverage too.

Users can use the data as supplied or attach their own attributes. When viewed overlying other publicly available data, e.g. satellite imagery (Google earth), OS open data, OpenStreetMap, etc. that may feature agricultural land, the points provide a useful reference point to identify the approximate centre of agricultural parcels.

Parcel Points uses the Open Government Licence v3.0 as used by other publicly accessible data on the Defra Data Services Platform and will be updated every 6 months.

Coverage will be for agricultural land parcels in England only.

Users should be aware that client-side constraints associated WFS and OGC API, such as maximum feature limits, may affect the loading and display of parcel points. Parcel Points WMS are not affected to the same extent.

The Chesapeake Bay Preservation Ordinance was adopted to protect our local streams and one of the world's most productive estuaries, the Chesapeake Bay, from pollution due to land use and development. All of Fairfax County drains into the Potomac River and ultimately the Chesapeake Bay. In an effort to protect and improve the quality of these waterways, sensitive areas along streams throughout Fairfax County have been designated as Resource Protection Areas.State regulations require that Resource Protection Areas (RPAs) be designated around all water bodies with perennial flow. Perennial flow means that water always flows in the stream or other water body except during periods of drought. The Department of Public Works and Environmental Services conducted field studies to identify all perennial streams throughout the county and used this information to prepare a set of maps showing the location of RPAs as defined under the revised Ordinance. The maps were adopted by the Board on November 17, 2003. The data include the boundaries of the RPAs adopted by the Board in 1993 and the additional RPAs adopted by the Board in 2003. These are general locations of RPA boundaries for planning purposes and the actual limits may be further refined by detailed field studies conducted at the time a plan is submitted to obtain a permit to develop a property.Any areas within Fairfax County not contained within the RPAs are Resource Management Areas (RMAs). Together, the RPAs and RMAs comprise the Chesapeake Bay Preservation Areas.

This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries.

Regional Planning Association (RPA) in the State of Iowa with Iowa's Transportation Alternatives Program (TAP) data.

This datalayer represents the boundaries of the 13 regional planning agencies (RPAs) in Massachusetts. Each RPA serves as a forum for state and local officials to address issues of regional importance, including the development of comprehensive plans and recommendations in areas of population and employment, transportation, economic development, regional growth and the environment.More details...Map service also available.

The RPA Commons GOP is a simple point dataset, that marks the location of observations made by surveyors in a sample of parcels and records the land cover according to set criteria. It has been maintained by RPA Geospatial Services since 2015. RPA currently collects ground observation data from the following source: • Common land parcels eligible for the Control with Remote Sensing (CwRS) element of the Basic Payment Scheme (BPS), and that fall within zones selected for monitoring claims. The locations and size of these zones vary from year to year. The field surveys for are carried out on RPA’s behalf by Cyient Europe Ltd. They have been acquired for both Control with Remote Sensing (CwRS) and for Commons Eligibility Mapping programmes that have been completed during the year. The points are attributed with: • Parcel reference ID (as with RPA Parcel Points) • Crop or land cover observed to be / have been growing at that location • Date of observation • Whether observations were made by RPA or an external surveyor • Any additional comments Two versions will be made available: one with photos of the land cover attached (RPA_Commons_GOP_2023_FULL) and the other with them removed (RPA_Commons_GOP_2023_Basic). The data for the Commons Eligibility Mapping programmes is part of CwRS programme. It is intended that releasing the ground observations would benefit research in automation, machine learning, and our national food production. RPA’s GOP use the Open Government Licence v3.0 as used by other publicly accessible data on the Defra Data Services Platform and will be updated approximately every year, subject to the continuation of current policies. Attribution statement: © Rural Payments Agency copyright and/or database right 2023. All rights reserved.

This layer depicts the Chesapeake Bay Preservation Act (CBPA) areas in Hampton Roads, Virginia, categorized into three delineations:

James City County - Resource Protection Area

The James City County Community Development Dept. provided criteria for this layer.Please refer to the JCC web site below.JCC Stormwater

Michigan's Planning and Development Regions

List of bacteria species and strains used for determining the cross reactivity of the RPA assay.

Production data were generated using the Normalized Difference Vegetation Index (NDVI) from the Thematic Mapper Suite from 1984 to 2021 at 250 m resolution. The NDVI is converted to production estimates using two regression formulas depending on the level of the NDVI; there is one equation for lower values (and thus lower production values) and one for higher values.This raster dataset yields estimates of annual production of rangeland vegetation and should be useful for understanding trends and variability in forage resources.The Rangeland Productivity data can be downloaded here:https://data.fs.usda.gov/geodata/rastergateway/rangelands/index.phpThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

RPA primers and exo-probe combination, yielding the highest analytical sensitivity in the MAP-RPA assay.

The Registered Common Land (RCL) Layer is an Administrative Boundary dataset which shows Rural Payments Agency land mapped as Registered Common Land. The RCL layer defines the extent of all registered common boundaries within England that are claimed on for subsidies and is better aligned to Ordnance Survey MasterMap and RPA parcel boundaries.

RPA's implementation of the RCL layer has been used from 2015 onwards to support the payment of subsidies associated with commons and commons grazing rights; it is derived from the CRoW Registered Common Land dataset, and is continually updated to support payments.

Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed on data.gov.uk.

The Crop Map of England (CROME) is a polygon vector dataset mainly containing the crop types of England. The dataset contains approximately 32 million hexagonal cells classifying England into over 50 main crop types, grassland, and non-agricultural land covers, such as Trees, Water Bodies, Fallow Land and other non-agricultural land covers. The classification was created automatically using supervised classification (Random Forest Classification) from the combination of Sentinel-1 and Sentinel-2 images during the period late January 2017 – August 2017. The dataset was created to aid the classification of crop types from optical imagery, which can be affected by cloud cover. The results were checked against survey data collected by field inspectors and visually validated. Refer to the CROME specification document. Attribution statement: © Rural Payments Agency

The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods. The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used: Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate Data Attribution statement: "Contains data supplied by ©Natural England ©Centre for Ecology and Hydrology, Natural England Licence No. 2011/052 British Geological Survey © NERC. All rights reserved., © Environment Agency copyright and/or database right 2015. All rights reserved. ©Natural England © Crown copyright and database right [2014], © Rural Payments Agency, © Natural England © 1995–2020 Esri, Contains Environment Agency information © Environment Agency and/or database rights. Some information used in this product is © Bluesky International Ltd/Getmapping PLC. Contains freely available data supplied by Natural Environment Research Council (Centre for Ecology & Hydrology; British Antarctic Survey; British Geological Survey). Contains OS data © Crown copyright and database right, © Environment Agency copyright and/or database right 2015. All rights reserved., Esri, Maxar, Earthstar Geographics, USDA FSA, USGS, Aerogrid, IGN, IGP, and the GIS User Community, Contains Ordnance Survey data © Crown copyright and database right 2021., EODS / CEDA ARD: ESA Copernicus: 'Contains modified Copernicus Sentinel data [2021]', © Carlos Bedson Manchester Metropolitan University, © Copyright 2020, worldclim.org" Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315. Pescott, O.L.; Walker, K.J.; Day, J.; Harris, F.; Roy, D.B. (2020). National Plant Monitoring Scheme survey data (2015-2019). NERC Environmental Information Data Centre. https://doi.org/10.5285/cdb8707c-eed7-4da7-8fa3-299c65124ef2 © UK Centre for Ecology & Hydrology © Joint Nature Conservation Committee © Plantlife © Botanical Society of Britain and Ireland The following acknowledgement is required for use of this dataset: The National Plant Monitoring Scheme (NPMS) is organised and funded by the UK Centre for Ecology & Hydrology, Botanical Society of Britain and Ireland, Plantlife and the Joint Nature Conservation Committee. The NPMS is indebted to all volunteers who contribute data to the scheme.

The Crop Map of England (CROME) South West is a polygon vector dataset mainly containing the crop types of England. The dataset contains approximately 32 million hexagonal cells classifying England into over 20 main crop types, grassland, and non-agricultural land covers, such as Woodland, Water Bodies, Fallow Land and other non-agricultural land covers. The classification was created automatically using supervised classification (Random Forest Classification) from the combination of Sentinel-1 and Sentinel-2 images during the period late January 2016 – August 2016. The dataset was created to aid the classification of crop types from optical imagery, which can be affected by cloud cover. The results were checked against survey data collected by field inspectors and visually validated. refer to the CROME specification document Attribution statement: © Rural Payments Agency