GIS tool for urban areas to simulate variability in space and in time the electric energy load and the yield productions of rooftop PV systems to assess for planning phase

The pilot application is focusing on the sponge city concept and atmospheric phenomena concerning the safety in and around cities. The application focuses on Urban Heat Index, drought and precipitation and provides methods for impact studies and evaluation of different adaptation strategies. Post-processing models will be used for seasonal and shorter-term forecasts and all will be combined with in-situ observations. A seamless product portfolio will help road maintenance companies and city authorities in managing impacts of snowfall events.

In order for the world to meet the objectives of the Paris Agreement, the scientific community of earth observation and climate science has to come together and address the main identified research gaps. In particular, it is necessary to reduce the remaining uncertainties in the global carbon cycle. Special emphasis must be put on sources and sinks of oceans and terrestrial ecosystems, in order to fully integrate the budgets for the main greenhouse gases (GHG), CO2 and CH4.

Natural hazards such as droughts, flash floods, and natural and man-induced disasters e.g. forest fires, and floods, are affecting and have a dominant role in natural ecosystems and agriculture, and hence food, resiliency and sustainability. This pilot is being composed by 3 main pillars: i) Gathering and processing of raw EO and meteo data , leveraging on DIAS back-office cloud services and integrating with multiple other data sources (in-situ, crowd, modelled); ii) Risk disaster modelling derived by NOA (risk assessment on various phenomena fires, droughts, seismic, landslides, floods), meteo modelling, flash flooding targeting on timely and accurate information (e.g. warning, alerting), and timely delivery to relevant stakeholders (e.g. farmers, agriculture cooperatives); & iii) Crop type and natural ecosystems mapping leveraging on EO research capacities (TRL 5) relying on machine learning methods in the agriculture domain (e.g. vegetation indices, crop identification etc.), fused with meteo data and coupled with disaster assessments and forecasts , aiming to provide vital thematic information to support the involved user communities (e.g. agriculture agencies, farmers, farming cooperatives) and decision making for the benefit of the agriculture sector and food security. This pilot would integrate an advanced hazard forecasting system to explore the links between heatwaves, wildfires, and floods in synergy with the other pilots of the disaster showcase concerning the development of an innovative meteo modelling solution in higher grid resolution and with EO based assimilation process.

Aquafarmers faces new challenges due to the impact of extreme events mostly related to climate change, leading to changes in the sea temperature and phytoplankton, affecting growth rates and mortality of shellfishes and, therefore, the productivity of farms and the quality of products. As a consequence, aquafarmers can’t rely totally on well-known and established farming practices.

Using knowledge about how certain substances, such as one of the main pigments of the phytoplankton (Chlorophyll a - Chl a) alter the colour of the water, these parameters can be derived from optial Earth Observation (EO) satellite sensors. Water Insight provides monitoring services of Chl a based on EO data which is validated with in situmeasurements. Also the maps of WFD phytoplankton biomass status classes are created, by application of the WFD tresholds on Chl a as a proxy for phytoplankton biomass. The maps are made available in a portal, which allows to follow the lakes in time, zoom and download maps and time series.