Biography

My publications

Publications

ANA MONICA ANDRIES, STEPHEN MORSE, RICHARD JAMES MURPHY, Jim Lynch, Bernardo Mota, Emma Woolliams (2021)Can Current Earth Observation Technologies Provide Useful Information on Soil Organic Carbon Stocks for Environmental Land Management Policy?, In: Sustainability (Basel, Switzerland)13(21)12074 MDPI

Earth Observation (EO) techniques could offer a more cost-effective and rapid approach for reliable monitoring, reporting, and verification (MRV) of soil organic carbon (SOC). Here, we analyse the available published literature to assess whether it may be possible to estimate SOC using data from sensors mounted on satellites and airborne systems. This is complemented with research using a series of semi-structured interviews with experts in soil health and policy areas to understand the level of accuracy that is acceptable for MRV approaches for SOC. We also perform a cost-accuracy analysis of the approaches, including the use of EO techniques, for SOC assessment in the context of the new UK Environmental Land Management scheme. We summarise the state-of-the-art EO techniques for SOC assessment and identify 3 themes and 25 key suggestions and concerns for the MRV of SOC from the expert interviews. Notably, over three-quarters of the respondents considered that a ‘validation accuracy’ of 90% or better would be required from EO-based techniques to be acceptable as an effective system for the monitoring and reporting of SOC stocks. The cost-accuracy analysis revealed that a combination of EO technology and in situ sampling has the potential to offer a reliable, cost-effective approach to estimating SOC at a local scale (4 ha), although several challenges remain. We conclude by proposing an MRV framework for SOC that collates and integrates seven criteria for multiple data sources at the appropriate scales.

Ana Andries, Stephen Morse, Richard J. Murphy, Jim Lynch, Emma R. Woolliams (2019)Seeing Sustainability from Space: Using Earth Observation Data to Populate the UN Sustainable Development Goal Indicators, In: Sustainability11(18) MDPI

In 2015, member countries of the United Nations adopted the 17 Sustainable Development Goals (SDGs) at the Sustainable Development Summit in New York. These global goals have 169 targets and 232 indicators based on the three pillars of sustainable development: economic, social, and environmental. However, substantial challenges remain in obtaining data of the required quality and quantity to populate these indicators efficiently. One promising and innovative way of addressing this issue is to use Earth observation (EO). The research reported here updates our original work to develop a Maturity Matrix Framework (MMF) for assessing the suitability of EO-derived data for populating the SDG indicators, with a special focus on those indicators covering the more social and economic dimensions of sustainable development, as these have been under-explored in terms of the contribution that can be made by EO. The advanced MMF 2.0 framework set out in this paper is based on a wide consultation with EO and indicator experts (semi-structured interviews with 38 respondents). This paper provides detail of the evolved structure of MMF 2.0 and illustrates its use for one of the SDG indicators (Indicator 11.1.1). The revised MMF is then applied to published work covering the full suite of SDG indicators and demonstrates that EO can make an important contribution to providing data relevant to a substantial number of the SDG indicators.

Ana Andries, Stephen Morse, James Lynch, E Woolliams, J Fonweban, Richard Murphy (2018)Translation of Remote Sensing data into Sustainable Development Indicators, In: Proceedings of ISDRS24 ISDR

In 2015, member countries of the United Nations adopted the 17 Sustainable Development Goals (SDGs) at the Sustainable Development Summit in New York. These global goals have 169 targets and 232 indicators which are based on the three pillars of sustainable development: economic, social and environmental. Substantial challenges remain in obtaining data of the required quality, especially in developing countries, given the limited resources involved. One promising and innovative way of addressing this issue of data availability is to use Earth Observation (EO). This paper presents the results of research to analyse and optimise the potential of EO approaches to populate the SDG indicators and targets. We present a matrix of EO technologies with respect to the full set of current SDG indicators which shows the potential for direct or proxy calibrations across the span of the social, economic and environmental SDG indicators. We have focussed particularly on those SDG indicators covering the social and economic dimensions of sustainable development as these are relatively unexplored from an EO context. Results suggest that EO can make an important contribution towards populating the SDG indicators, but there is a spectrum from at one end the sole use of EO to the other end where the EO derived data have to be used in concert with data collected via non-EO means (surveys etc.). Complicating factors also include the lack of driving force and pressure indicators in the SDG framework and the use of ‘proxy’ indicators not part of the SDG framework but more amenable to EO-derived assessment. The next phase of the research will involve the presenting of these ideas to experts in the EO and indicator arenas for their assessment.

Ana Andries, Stephen Morse, Richard Murphy, James Lynch, Emma Woolliams, John Fonweban (2019)Translation of Earth Observation data into Sustainable Development Indicators: an analytical framework., In: Sustainable Development27(3)pp. 366-376 Wiley

In 2015, member countries of the United Nations adopted the 17 Sustainable Development Goals (SDGs) at the Sustainable Development Summit in New York. These global goals have 169 targets and 232 indicators which are based on the three pillars of sustainable development: economic, social and environmental. Substantial challenges remain in obtaining data of the required quality, especially in developing countries, given the often limited resources available. One promising and innovative way of addressing this issue of data availability is to use Earth Observation (EO). This paper presents the results of research to develop a novel analytical framework for assessing the potential of EO approaches to populate the SDG indicators. We present a Maturity Matrix Framework (MMF) and apply it to all of the 232 SDG indicators. The results demonstrate that while the applicability of EO-derived data does vary between the SDG indicators, overall, EO has an important contribution to make towards populating a wide diversity of the SDG indicators.