Remote sensing for essential biodiversity variables (RS4EBV)

Brian O'Connor, Andrew Skidmore, Roshanak Darvishzadeh, Tiejun Wang, Chris McOwen, Anton Vrieling, Mike Harfoot, Marc Paganini

Research output: Contribution to conferenceAbstract


Paper 900 - Session title: Essential Biodiversity Variables.

Plants underpin food chains in nearly all ecosystems and play a vital role in the provisioning of ecosystem goods and services to society. However human pressures are causing rapid and widespread decline in the world’s plant diversity with consequent influence on the capacity of ecosystems to provide the goods and services on which humanity ultimately depends. Monitoring and reporting on changes in ecosystem function and health is essential for evaluating and prioritising global biodiversity conservation efforts.

The Group on Earth Observation Biodiversity Observation Network (GEO BON) is in the process of reforming the acquisition, coordination and delivery of biodiversity information and services to end users, in particular to decision-makers. Underpinning this initiative is the GEO BON’s effort to develop a candidate set of Essential Biodiversity Variables (EBVs), which provide guidance to observation systems as to what and how to measure key aspects of biodiversity status and trends.

The RS4EBV project is a wholly novel project that aims to advance the conceptual development of EBVs concerning ecosystem structure and function. It is mapping a suite of plant functional traits over three pilot sites in Europe, representing three very different habitats – managed to natural grasslands, temperate forest and coastal saltmarsh- directly from Sentinel-2 imagery and transforming these variables into a higher-level, ecologically- meaningful estimate of Functional Diversity (FD); the value, range and relative abundance of plant traits in an ecosystem. The first phase of the project has relied on Sentinel-2 surrogate datasets, namely RapidEye for leaf chlorophyll retrieval and SPOT-5 for phenological metrics, owing to the presence of the red edge band and the 5-day revisit time of each sensor respectively. The second phase of the project will apply the algorithms and methods developed in phase 1 to Sentinel-2 imagery. The plant traits that can be directly retrieved from imagery are the so-called ‘direct’ EBVs while the FD, requiring a predictive model supported by in-situ and other trait data, is referred to as the ‘indirect’ EBV. In order to build the phenomenological relationships which drive this predictive model, a series of correlation tests are being carried out in order to characterise the relationship between the direct, satellite-derived EBVs and FD calculated from ground data alone.

The vision of this project is to initially pilot the methodology to model FD for a set of controlled study sites while exploring the possibility to up-scale the method to monitor FD on a continental to global scale. In future, spatiotemporally consistent observations of FD will provide a ready indicator of ecosystem status and trends and greatly assist in global conservation efforts in support of the Convention on Biological Diversity.
Original languageEnglish
Publication statusPublished - 2016
Externally publishedYes
EventLiving Planet Symposium 2016 - Prague, Czech Republic
Duration: 9 May 201613 May 2016


ConferenceLiving Planet Symposium 2016
Country/TerritoryCzech Republic


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