Virtual Survey Lab

Science challenge

The ability to efficiently access and analyse datasets from many sources is essential to gain an holistic understanding of environmental processes and change. The Virtual Survey Lab supports environmental research by bringing together data collected both within the UK-SCAPE programme and by external partners.

Objectives

To develop the components of a Data Science Framework (DSF) required to produce integrated data products utilising the data collected within the UK-SCAPE program and from external sources.
To develop statistical routines to analyse data across different spatial and temporal scales and from different sources to produce a series of highly resolved spatio-temporal data products.
To make these products discoverable and accessible to the wider scientific community and prioritised to address questions and fill gaps in other areas of the UK-SCAPE programme.
To test the efficiency of ongoing monitoring and, in the context of answering specific questions, highlight where we should direct monitoring campaigns and prioritise effort.
To provide a platform for the integration of monitoring data provided by a range of partners from across terrestrial, atmospheric and freshwater habitats.

Methodological Developments

Survey Design

Power analysis

Users can simulate data under different survey designs and expected change scenarios and then use this to calculate the expected power (probability of detecting an effect) of the specified survey design in detecting the specified change.

App: UK-SCAPE Power Analysis Tool
Paper:
- Boyd, R J, Powney, G D, Burns, F, Danet, A, Duchenne, F, Grainger, M J, Jarvis, S G, Martin, G, Nilsen, E B, Porcher, E, Stewart, G B, Wilson, O J, Pescott, O L. 2022. ROBITT : A tool for assessing the risk‐of‐bias in studies of temporal trends in ecology. Methods Ecol. Evol. 13, 1497–1507.

Data Quality Assurance (QA)

State tagging

State tagging is an unsupervised machine learning method to improve contextual understanding of environmental time series by segmenting it into arbitrary states, which can be used as a tool to QA variables whose typical range changes with environmental conditions.

Code: State tagging application for environmental data quality assurance
App: System state tagging (generic version)
Paper:
- Tso, C-H M, Henrys, P, Rennie, S, Watkins, J. 2020. State Tagging for Improved Earth and Environmental Data Quality Assurance. Front. Environ. Sci. 8.

Analysis Methods

Spatial Upscaling

Point data to maps

The EcoMAPS R library is a spatial statistical model to upscale point data to GB-wide mapped datasets using detailed covariate information.

Code: Spatial-Upscaling-model
Shiny App: EcoMAPS - GB Mapping of Environmental Indicators
Example output (EIDC dataset): Topsoil pH estimates from the Countryside Survey of Great Britain, 2007 using a generalized additive model

Integration

Joint species distribution modelling

This is an R package for running joint Species Distribution Models (jSDM) in Stan.

Code: jsdmstan: joint Species Distribution Models in Stan
Data: vegtaxon

Spatial integration

This work provides a detailed analysis and review of data integration, especially for species distribution models. The app allows users to compare two hypothetical sampling design as well as integrating them to show the benefits or disbenefits of each scheme.

Code: IOFFsimwork
Papers:
- Isaac, N J B, Jarzyna, M A, Keil, P, Dambly, L I, Boersch-Supan, P H, Browning, E, Freeman, S N, Golding, N, Guillera-Arroita, G, Henrys, P A, Jarvis, S, Lahoz-Monfort, J, Pagel, J, Pescott, O L, Schmucki, R, Simmonds, E G, O’Hara, R B. 2020. Data Integration for Large-Scale Models of Species Distributions. Trends Ecol. Evol. 35, 56–67.
- Simmonds, E G, Jarvis, S G, Henrys, P A, Isaac, N J B, O’Hara, R B. 2020. Is more data always better? A simulation study of benefits and limitations of integrated distribution models. Ecography (Cop.). 43, 1413–1422.
- Jarvis, S G, Mackay, E B, Risser, H A, Feuchtmayr, H, Fry, M, Isaac, N J B, Thackeray, S J, Henrys, P A. 2023. Integrating freshwater biodiversity data sources: Key challenges and opportunities. Freshw. Biol. 68, 1479–1488.
App: NCEA Data Integration Exploration Tool
Example output (EIDC dataset): Gridded estimates of Ellenberg N, R, F, and L indicators for Great Britain, 1990 and 2015–2019

Spatial-temporal integration

This exemplar provides examples of spatiotemporal integration of multiple data sources to predict insect populations using R-INLA.

Code and paper draft: Spatio-Temporal Data Integration in R-INLA Paper
App: gaussian_process_kernel_app

Process Model – Data Integration

This exemplar demonstrates how uncertainty in model discrepancy in UK maps with a spatial dependence can be modelled using a nearest-neighbour Gaussian Process methodology.

Code: ukMapsUncExemplar
Example output (EIDC dataset): UK maps representing baseline uncertainty in CO2 and CH4 fluxes

Application programming interface

The NRFA API

The NRFA API allows users to programmatically access river flow data from across the NRFA network.

Learn more about NRFA API

The COSMOS-UK API

The COSMOS-UK API allows users to programmatically access soil moisture data from across the 45+ sites in COSMOS-UK network.

Learn more about COSMOS-UK API

Data exploration portals

UK Water Resources Portal

The UK Water Resources Portal offers dynamic, interactive situation monitoring, mapping and plotting for rainfall, river flow, groundwater levels and soil moisture measurements.

Go to the UK Water Resources Portal

Hydrological data integration tool

This tool demonstrates the integration and visualisation of hydrological sensor data (often real-time) from diverse online sources, such as EA water quality and river flow.

Go to the hydrological data integration tool

Data portals

Our data portals enable you to visualise and interrogate some of the diverse environmental datasets held by UKCEH.

Browse our data portals

Data exploration and analysis

Screenshot of PBMS map showing data for 2021-22

PBMS Map of Bird Submissions

This app provides analytical tools for exploring submissions to the Predatory Bird Monitoring Scheme.

Go to the PBMS Map of Bird Submissions

BRC Indicator Builder

This app allows users to build custom biodiversity indicators from published data using their choice of taxa, region, filtering criteria and methods.

Go to the BRC Indicator Builder

Screenshot of plot in the NRFA Trend Explorer

NRFA Flow Trend Explorer

This app provides a way of exploring and evaluating trends in peak flow and daily flow data within the measuring stations with records in the National River Flow Archive.

Go to the NRFA Flow Trend Explorer

Web-based apps

Explore our range of web-based apps and tools which provide methods to search and evaluate different data or support decision-making relating to specific environmental challenges.

Browse our web-based apps

Data integration examples

NRFA

Find out how data from the NRFA is used across various other portals.

Read the NRFA story

Project Lead: Pete Henrys

Staff profile