Pilots

Our Expertise

The project will promote the development and uptake of 5 pilot applications from different geographic areas and climate regions, addressing the UN Sustainable Development Goals, The Paris Agreement and the Sendaï Framework for Disaster Risk Reduction and aligned with GEO Societal Benefit Areas:

→ Water and Land Use Management

→ Sustainable Agriculture

→ Transport Management

→ Sustainable Urban Development

→ Disaster Resilience

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Pilot 1: Water & Land-Use Management Regional Scale & Cross-border

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Development of a framework, models and DSS for embedding co-design into spatial water and land management strategies to enhance climate resilience, focusing on water shortage, droughts and soil carbon sequestration. Regional stakeholders use climate impact atlases for testing adaptation measures; these need enhancement using data of high spatiotemporal resolution. The Province of NB is leading the co-design process.

Pilot Description & Climate Change application

Pilot Description & Climate Change application: Stakeholders need easily accessible climate effect applications and atlases of the Aa of Weerijs catchment. These are preferably built on spatial and temporal high-resolution data on climate and for relevant effects of Climate Change. There are some existing national and regional climate atlases, but they are not built on high-resolution data, and, secondly, they provide few, generic climate effect analyses. The proposed applications built with the support of GEOSS data will enhance stakeholder knowledge for designing climate adaptation measures and analyse these on their effects and degree of reducing/managing water shortages in drought conditions, and of GHGs mitigation (denitrification and carbon sequestration). Applications are as follows:
1. Hydrological / Water management model: Using combinations of data available locally and in GEOSS, comprehensive model(s) representing the hydrology in the catchment will be developed such that the adaptation measures can be represented and their effects analysed. These models need to provide results easily translated into potential actions by stakeholders on the ground, a task that will need to continue for a longer period. A mix of process-based models and AI-based models will be built, including sensitivity and uncertainty assessments. A hydrological and hydraulic model of the Aa of Weerijs catchment will be designed (including the subsurface), capable of representing adaptation measures (water storage, effective use, etc.) preferably at level of farm or property, under different climate scenarios. The value of GEOSS data will be tested also to assess conditions in the upstream part of the catchment in Belgium. Although the catchment is small (about 190 km2, of which 120 km2 is in Belgium), such analysis is valuable for replication / upscaling in other cross (trans) border catchments.
2. Soil carbon model: An integrated model of the catchment as a socio-ecological system will be built, representing the impact of adaptation measures on carbon sequestration. The model will be used to analyse some representative chrono-sequences of land use change (space‐for‐time substitution sites). To assess the impact of nature based solutions as adaptation measures on soil carbon storage, the application will model these impacts on processes, combining EO and in-situ data (from NB/waterboard), on changes in Soil Organic Matter (SOM), Soil Quality (topsoil depth, earthworms, drainage, retention etc.), Land Use Change (SDG 15.3). In addition to testing the effect on soil carbon sequestration locally, this application will enable assessing the impact on soil carbon at European Scale (EU Green Deal). This will be enabled using sub-basin spatial variability in drivers and retention processes of the Global News model (Global Nutrient Export from WaterSheds) with EU basins data.
3. Decision Support Application (web-based) that will allow presentation and testing of the adaptation measures in the Aa of Weerijs catchment by different stakeholders of the Pilot 1 Communities of Practice in a user-friendly manner. The effect of all proposed adaptation measures will be tested under Climate Change impact scenarios already developed in the climate impact atlases in NL11. Where needed, these atlases will be enhanced to assess impacts on local scales.

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Pilot 2: Sustainable Agriculture National scale

This pilot will develop a consistent land representation system for efficient estimation of carbon stock changes and measures that influence emissions of GHGs. This will be used by farmers and policymakers to manage local and national microclimate effects more efficiently in support of a shift towards a low carbon and climate resilient economy in the agriculture.

Pilot Description & Climate Change application

EIFFEL, in a co-design process led by NPA, envisions to achieve short and long-term adaptation to Climate Change (e.g. carbon sequestration) and address environmental priorities of post-CAP 2020. This will be achieved thought A) the enhancement of EO services by leveraging on GEOSS and Copernicus data/products, as well as the distinct advantages of IACS/LPIS over other potential LULUCF data sources. The co-designing approach aims to B) enhance the reporting/monitoring of agricultural carbon emissions data by reaching Tier 3 modelling methodologies (IPCC guidelines), and C) assess recognized good practices (e.g. crop diversification) to the advent of Climate Change for current and future climatic conditions.
A) Enhanced spatial explicit agri-indicators: The aim is to provide detailed, next generation agricultural products for a robust assessment at micro-scales (i.e. field level based on IACS). The estimation of spatially distributed vegetative characteristics will be done leveraging GEOSS data (DEM, CLMS) and assimilating EO, in-situ and auxiliary spatial databases (LPIS). In this context, a monitoring tool will integrate both indirect predictions of Soil Organic Carbon (SOC) for grasslands through digital soil mapping techniques, and direct prediction for exposed soils (e.g. croplands), through imaging spectroscopy techniques. The accuracy of SOC prediction should meet the needs of users responsible for reporting on soils, and of policy makers designing and evaluating policies to increase SOC stocks. Given the rapid sensor developments (e.g. hyper-spectral PRISMA), the approach should evolve in the quality of SOC predictions and accommodate other soil properties (NO3-N). Existing EO data will be studied for their features, regulation needs and applicability in EIFFEL, while prominent integration strategies will be proposed assisted by XAI models, including uncertainty assessments.
B) Agricultural Carbon Hybrid model: With the need to move to higher tier methodologies, we will evaluate ensemble DL for building agricultural carbon meta-models and improve existing agricultural C storage and flux estimates in terms of spatiotemporal scale and completeness. The enhanced spatial explicit agri-indicators will be combined with global gridded crop models (GGCMs, e.g. EPIC), supporting scenario based calculations of crop biomass, soil C storage and C fluxes. The declaration of agricultural lands will be extended to provide additional information related to farm management practices (e.g. tillage). Then, spatiotemporal downscaling of GGCMs outputs will be performed by applying ensemble modelling on the large scale agronomic simulations as derived from the various GGCMs and applied to the region of interest at a finer spatial resolution. The approach will enable a meta-model training in a systematic way in order to simulate artificial combinations of atmospheric, soil, cultivar, and management conditions and the corresponding reporting of them.
C) Crop diversification (CropDiv): CropDiv will answer where suitable areas are located, taking into account climate shifts from one area to another. Research will be conducted to build data driven algorithms to model the suitability of specific crops (e.g. maize, cotton) using yield data and EO variables (agriculture, environmental and weather). Then, specific IPCC climate scenarios will be used (e.g. RCP 2.6, 4.5, 8x.5) for the 2050s and 2100s, providing important agro-climatic indicators e.g. precipitation, air temperature, frost days, max consecutive dry/frost days etc. to assess the suitability of specific crops. The influence of climatic conditions and land changes (e.g crop mixes and extent of diversification) will be evaluated, using geospatial land suitability models for selected crops. A suitability analysis will be performed clustering land suitability parameters using XAI models.
On top of these, an in-depth validation exercise will be executed in the Lithuania (~400 farmers) stratified into landscapes unit based on the following criteria: agricultural land use (incl. nitrate vulnerable areas) and soil type. Additionally, socio-economic impacts will be roughly estimated taking into account the variability of farm income/subsidies% per region, as well as gender-age information.

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Pilot 3: Infrastructure & Transport Management Regional Scale

Development, following a co-design approach, driven by the Port Authority of the Balearic Islands (BPA), of an XAI-based atmospheric pollution monitoring and predicting application. The application will use data mining techniques to minimize the carbon footprint of the port activity and its impact on the city, dominated by high seasonal cruise-ships traffic and help them adopt good environmental practices.

Pilot Description & Climate Change application

BPA is gathering real time surface pollution data through a set of 25 in-situ stations distributed in the 5 ports area, that measure atmosphere parameters every 10 minutes, such as SO2, NO2, O3, CO, PM10, PM2.5 and weather observations (temperature, pressure and wind direction). Yet, this amount of data is not enough to build pollution patterns to produce reliable historical episodes of pollution or anomaly pollution predictions outside the port area, neither in the city nearby, where local and regional variability should be considered. This pilot will develop, through a co-design process, a port-oriented, atmospheric pollution monitoring web application addressed to port operators, cruise companies, city and other stakeholders for decision making and awareness. This application benefits from XAI, DL, data mining and geospatial techniques and is facilitated by EIFFEL tools. Real time in-situ observations will be combined with historical GEOSS data as well as external sources. The application will allow (i) integration with the cognitive search tool for data exploration, (ii) the calibration of EO surface pollution data in the port area, where land pollution stations data is available, (iii) the upscaling of pollution data in a regional level taking into account GEOSS and other open data sources, (iv) the real-time monitoring of abnormal pollution events detection, through the correlation of vessel activity (cargo and cruise ships), pollution, wind, and land traffic data in port area, city area and sea nearby, identifying the pollution origin and impact, (v) the temporal analysis of pollution indicators, in areas affected by navigation routes, (vi) the prediction of pollution patterns for supporting decision makers in optimising vessel traffic routes from/to the port area. The application will also provide a map viewer with temporal air quality maps (following OGC standards, INSPIRE), profile-tailored dashboards with pollution KPIs, notifications and reports for BPA, cruise companies and city authorities/citizens. This pilot will leverage datasets, results and collaboration with ongoing projects that share complementary objectives, e.g. PIXEL (H2020) and I2panema (ITEA3).

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Pilot 4: Sustainable Urban Development Local | Regional Scale

Development of an application to enable inspection of GHG mitigation scenarios, in three urban critical sectors: building energy efficiency, photovoltaic penetration in urban environments, vehicle fleet emissions, in support of carbon neutrality in a metropolis, specifically the Greek capital city of Athens.

Pilot Description & Climate Change application

The Region of Attica (approx. 3.8M population) is the key stakeholder that will drive the co-design of a Climate Change application with other partners (NOA, Draxis). The application will enable the inspection of different GHG emissions' mitigation scenarios in three critical sectors:

(i) Building energy efficiency: Google Earth imagery classification and object features including buildings and shadows geometry integrated, with Eumetsat’s SAFNWC and Copernicus products (e.g. Urban Atlas 2012; Building Height 2012) will be used to map the footprint of buildings and their main geometry (e.g. height, roof-top area), in a selected Local Administrative Unit (LAU). In addition, the QGIS package with the LU/LC from the Greek Land Registry will help identify the potential areas for PV penetration. This data will be combined with national statistical data to compile a building stock model (BSM), leveraging EO and AI driven classification to map the building stock to specific building typologies. The concept from the EPISCOPE project along the lines of the TABULA Hellenic building typology and the updated version will enable scenario based calculation of GHG emission reduction. Further BSM improvement will be done by evaluating the above free data with Very High Resolution data for the building footprint (e.g. IKONOS), thermal envelope properties and local or central heat pumps (e.g. Sentinel-3 TIR). Complementary data through Cadastral and the energy performance certificate central registry will be used. BSM will allow assessing various renovation measures, modernization rates of the envelopes, technical installations, renewables etc. for the typical buildings and then projected to the region’s building stock. The vision is a systematic process for assessing energy savings and emissions abatement.

(ii) Photovoltaic penetration in urban areas: The solar energy system SENSE, developed through national (Aristotelis-Solar) and EU projects (GEO-CRADLE, e-shape) and applied at high resolution for the Attica region in SMURBS, will be used for assessing Rooftop PV (photovoltaic) systems penetration in urban areas. SENSE combines AI and high performance computing with CAMS solar and aerosol products and PV characteristics, to derive the energy potential of the region. Cadastral archives, inclination and orientation aspects and shadowing effects, will be used to calculate the solar energy availability at a building and neighbourhood level. A pilot study will be performed for the LAU of interest. Results will include assessing the carbon footprint reduction potential and estimating GHG emission abatement. The final product will be a detailed solar database and an interactive interface including: a) solar availability for a choice of PV orientations, available surface areas and PV materials b) a building scale database and interactive map of the LAU, providing the energy potential of the specific area.

(iii) Urban transport emissions and electromobility penetration: To calculate road transport emissions, the COPERT methodology, part of the EMEP/EEA air pollutant emission inventory guidebook, consistent with the 2006 IPCC Guidelines for calculating GHG emissions, will be deployed. Simulating from a single street to a full urban network, and selecting various fleet compositions (electric, LPG, CNG, hybrids), realistic scenarios will be studied to support policy decisions for achieving the desirable GHG emission reduction. The scenarios will be combined with the energy provided/saved by buildings, to infer on the feasibility of electric cars’ recharging. A city scale AQ model (e.g. EPISODE-Citychem) developed in SMURBS, will be used to study the effects of the scenarios in residential- and traffic-related emissions on the intra-urban concentration fields of basic air pollutants. The workflow will be fed with CLMS (Urban Atlas 2012 for proxies) and CAMS (emission inventory and regional reanalysis for boundary conditions) data. It will be assessed with AQ data from in-situ platforms and Sentinel-5p. Given the relation between climate forcing and air pollution emitters, the knowledge gained, not least with respect to black carbon, a critical climate forcer, will aim at developing sustainable and resilient cities, with citizens well-being the priority. The selected LAU is initially in Athens’ northern suburbs (e.g. municipalities of Penteli, Vrillisia, Kifissia), further refined upon co-design with Attica region and the availability of supplementary data.

Decision Support Application (DSA) for urban Climate Change mitigation measures: All the above will be combined into an interactive application comprising a user-friendly UI/UX, with the following features: capacity to use heterogeneous available data as input; visualization of different layers of the three components described above; simulation of policy scenarios and assessment of their effectiveness; support of the implementation of Climate Change policies.

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Pilot 5: Disaster Resilience > Drought, forest fire & pest risk assessment Regional | National Scale

Development of a framework for the risk assessment for: (i) drought, (ii) forest fires, (iii) forest pests. This will support monitoring, seasonal forecasts and long-term projections at regional and national scale and the development of adaptation and mitigation measures. Partner SYKE will drive the co-design approach.

Pilot Description & Climate Change application

The pilot will focus on the mapping of risks of droughts, forest fires and forest pests at regional and national scale in Finland. EIFFEL will integrate multiple data sources from GEOSS with national databases into a modelling framework to enhance existing drought and forest fire risk assessments and develop a new mapping tool for the risks of forest pests. The modelling framework will be applied to seasonal weather forecasts and climate projections up to 2050 and beyond. The pilot will bring together regional and national stakeholders to co-interpret the intermediate and final mapping of risks, followed by deliberation of alternative adaptation and mitigation measures. The WSFS model will be utilized to identify drought prone areas and to make seasonal and long-term drought forecasts. The potential improvement of drought forecast capabilities, based on satellite-observed soil moisture and vegetation characteristics as well as new drought indices, will be investigated. Forest fire indices calculated from meteorological variables, operationally in use in Finland to issues fire warnings, have also been applied to climate scenarios. WFSF and fire indices will be applied to construct impact response functions in a probabilistic framework to quantify the risk of drought and forest fire occurrences using similar approaches as in the Europe-wide analysis. Additionally, the benefit of satellite-observed soil moisture and vegetation condition and their integration in the assessment of forest fire risks will be evaluated. Building on previous work, predictive models that integrate in-situ observations from the Finnish moth monitoring scheme, climate variables and satellite-derived information from GEOSS and Copernicus will be used to forecast the occurrence and abundance of forest pest species. To this aim, GEOSS data will be investigated that can describe the phenological development of the host plants, drought effects on vegetation and forest damages. Stakeholders will be engaged in developing scenarios, data interpretation and utilization of the results. This will provide the project with empirical material and the stakeholders with support to their governance and decision-making processes. National scale risk assessments will be integrated as additional web-service based applications to national portals, such as the climate guide and the national portal for water resources information.