Assessing soil data from sites in London to identify links to key indicators for characterising soils

By Aisha Gloudon: September 2009

Supervisors: Dr Nick Voulvoulis & Dr Martin Head
Collaborator: Ms Dee Flight (British Geological Survey)

Introduction

This project assessed soil data from sites in London generated through the OPAL soil and earthworm survey and compared it with the existing BGS soil observation dataset. Key indicators were identified which could enable the broad characterisation of soils using public participation surveys.

There is little previous quantitative work on the accuracy of public participation data in environmental surveying, particularly with regard to soil surveys. Consequently, this project was important in forming the basis for a quantitative comparison of the accuracy/reliability of the OPAL soil survey through the development of key indicators and comparison to the quality controlled BGS survey data.

Objectives

  1. Assess the robustness of the OPAL survey dataset generated in comparison with the BGS dataset (using directly and indirectly comparable observations from both surveys).
  2. Determine and evaluate the spatial distribution of OPAL and BGS datasets.
  3. Determine a methodology for comparative analysis of the OPAL results relative to the BGS dataset.
  4. Derive key indicators, through the collation of OPAL survey observations, to enable the broad characterisation of soils using multiple observations.
  5. Test the effectiveness of the key indicators by assessing the correlation of the grouped results with an existing pollution dataset (London Mercury concentration).
  6. Assess the ways in which the results from this project can optimize the design and structure of future OPAL environmental surveys for data quality and the effectiveness of public participation in soil surveying.

Method

The empirical data generated by the IC OPAL survey was analysed and represented spatially. The BGS and OPAL soil observational data was then collated and standardised in order to be comparable to each other. The OPAL data was compared against the BGS data and the results generated by the OPAL survey were evaluated in comparison to the well constrained BGS dataset.

Finally, the OPAL and BGS observations were grouped under the following three key soil indicators:

  • Ability to Support Life
  • Geography, Geology & Climate
  • Anthropogenic Impact/Pollution

Two areas of London were selected for sampling and analysis, and corresponding observational data from both the BGS and IC OPAL surveys was selected, collated and analysed using descriptive statistics, and some aspects of the data such as mercury concentrations were represented spatially using a Geographical Information System (GIS) software package (ArcGIS). The results were compared in three ways:

  • Direct comparison
  • Indirect comparison
  • Mercury comparison

Results and conclusion

This research was successful in assessing the functionality of the OPAL survey and demonstrated that in some aspects the results generated from a public participation survey of this nature can be of a similar standard to those generated by a high-quality comparator survey (eg BGS soil surveys). Overall the accuracy and reliability of soil characterisation from various sites in London using the OPAL survey was shown to be of a high quality when tested using direct comparators.

This reliability decreased with the use of indirect comparators, showing that further work needs to be done to combine IC OPAL categories into indicators so that indirect comparisons will be possible. The results of the IC OPAL survey were generally well correlated with Mercury levels but this was also less successful using indirect comparators.

This research also provides the methodology foundation for further work within this field including the grouping of OPAL observations to form soil character indicators and the reclassification of BGS observations for comparison with OPAL data. In this way it goes some way towards enabling the raw data submitted by the public to be quality controlled and better analysed in the future.

Download the full project summary (PDF, 556KB)

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