Simone Sabbatini
Simone Sabbatini has a PhD in Forest Ecology, obtained in 2014 at the DIBAF department of the University of Tuscia, Viterbo, Italy. His background consists in a BSC in Forestry and Environmental Science, and a MSC in Management of Forestry Systems, both held at the University of Florence, Italy. Currently he is a Junior Researcher at the Euri-Mediterranean Center on Climate Change (CMCC), where he is involved in the activities of the Ecosystem Thematic Center (ETC), a facility of the Integrated Carbon Observatory System Research Infrastructure (ICOS-RI). At the ETC he deals with giving support to the ICOS stations concerning eddy covariance (EC), air meteorological measurements, and file submission. He is also in charge of running quality routines on EC data during the labelling time, and of caring the correct metadata ingestion of sensors by the processing routines.
Sessions
The collection of representative observational datasets in environmental sciences is crucial for advancing the understanding of the phenomena under consideration. The integration between in-situ datasets with remote sensing and machine learning techniques makes possible reliable predictions and analyses with enhanced precision and resolution. The OEMC project aims at supporting informed decision making on environmental policies for the benefit of the whole society, by combining in-situ measurements and remote sensing datasets. Here we investigate the impacts of some of the OEMC in-situ datasets on society and policymakers: how are the in-situ datasets supporting the use-cases of the project? What is their combined potential in terms of technological advancement and knowledge boost? The following categories of OEMC in-situ data, their benefits, and relation to sustainable development goals (SDGs) are scrutinised.
GHG fluxes: GHG fluxes ground observations, combined with satellite data, can be proficiently used for calibration and validation of models, with benefits in terms of better predictions, development of early warning systems, better understanding of climate change impacts, ecosystem services, etc. Current and potential stakeholders are the Intergovernmental Panel on Climate Change (IPCC) and international projects such as the Global Carbon Project (GCP) and FluxCom initiative. UNFCCC is also using GHG flux data. Related SDGs include 11, 12, 13 and 15.
Forest biomass: in-situ observations of forest biomass are fundamental in refining the assessment of global forest carbon stocks and their change under natural and anthropogenic drivers. These data serve the needs of a wide range of stakeholders, from both the scientific and the policy making sectors, interested in quantifying the actual carbon sequestration capacity of forests and refining estimates of forest inventories. Policies such as the European Forest strategy and monitoring of SDG 15 will benefit from such datasets.
Marine and terrestrial biodiversity: these datasets support projects and activities of biodiversity conservation, a fundamental branch of Earth science and a crucial aspect for the survival of humanity. Potential stakeholders include the European Environmental Agency (EEA) and the Joint Research Centre of the European Commission (JRC), and policies such as the European Biodiversity strategy and SDGs 14 and 15.
Ocean and coastal datasets: the importance of ocean and coastal organisms for the balance of the biosphere becomes more and more evident, but scientific knowledge is still limited in comparison with the terrestrial counterpart. Increasing the monitoring of these ecosystems is crucial, in particular for human communities living in coastal areas. EEA and JRC are included in the stakeholders interested. Related SDG: 14
LCLU: in-situ land use and land cover information derived from processing land surveys data and satellite imagery support land degradation alert systems and EO mapping. Potentially supported SDGs are 11, 12, 13, 14 and 15.
Automated ground observations: automated measurements of biological processes support the validation of EO products and provide input for ecological modelling. Data consistency is enhanced by the availability of a continuous dataflow from field sites where sampling is logistically or financially constrained. Possible applications include early warning systems in agricultural, forestry, and urban greening sectors, improved agronomic and silvicultural practices, monitoring ecosystems productivity and biodiversity levels. Potential stakeholders are the EEA, the JRC, entities involved in mandatory and voluntary carbon markets (UNFCCC, UNDP, private companies), national governments and local administrations. Related SDGs are 11, 12, 13 and 15.
Citizen science: citizen science in-situ data for training and validation of EO mapping models can play a fundamental part in supporting environmental policies, covering a wide range of topics, from deforestation to aboveground biomass assessment, from crop type to land use and land cover distributions. The European Green Deal is expected to greatly benefit from this type of in-situ datasets, and SDGs 13, 14 and 15 will potentially be supported.
In-situ and gridded integration: although the combination of in-situ and gridded datasets is common, their spatial resolution often differs. A case study focusing on eddy covariance data tries to shed light on the overlapping degree of ground and satellite footprints, with benefits for society in terms of technological advancements and a deeper understanding of how ecosystems react to climate change, with potential benefits for SDGs 13 and 15.
Among the many services in-situ datasets can provide to society, one of the more pressing interests currently active in the Earth Observation (EO) sector is the integration of in-situ and satellite datasets. The remote sensing community is actively using ICOS (Integrated Carbon Observation System) outputs for calibration and validation activities of satellite products. However, there are additional measurements currently excluded from the ICOS portfolio that could be beneficial for calibration and validation opportunities: for example, fraction of absorbed photosynthetic active radiation (fAPAR) and land surface temperature (LST) from thermal cameras.
An experimental setup was implemented on a subset of ICOS stations for estimating leaf area index (LAI), strictly related to fAPAR, from above- and below-canopy measurements of photosynthetic active radiation (PAR). The first longer-than-1-year datasets being available, we present some relevant preliminary results and the future direction of this activity.
NASA recently published some best practices on LST measurements for validation of satellite products. At this scope, a single thermal camera of high accuracy is deployed on a network of measuring stations. We intend to check how this setup relates to different configurations, such as different camera models, or the deployment of 3-4 lower-standard sensors looking at different angles, thus increasing the spatial resolution.
Additional points under scrutiny are: what is the heterogeneity of these variables in the eddy covariance footprint, and how can these measurements add value to the net ecosystem exchange (NEE) and its derived products? And how can the integration between satellite imagery and ground observations benefit from them?