EYWA System Winner of the 1st EIC Horizon Prize on Early Warning for Epidemics

EYWA banner winner long

EYWA, Prize Winner Press Release EN

EYWA, Prize Winner Press Release GR

EYWA, Prize winner (video)

Factsheet

Official Announcement of the EIC

 

In a nutshell

EYWA (EarlY WArning System for Mosquito borne diseases) is a prototype system addressing the critical public health need for prevention and protection against the Mosquito-Borne Diseases (MBDs) and lies under the umbrella of EuroGEO Action Group "Earth Observation for Epidemics of Vector-borne Diseases" which is led by the National Observatory of Athens / BEYOND Centre of Earth Observation Research and Satellite Remote Sensing.enter the platform

The system combines interdisciplinary scientific fields (entomology, epidemiology, ecology, EO, Big Data Analytics, AI/ML, Ensemble Dynamic/Hybrid vs Data Driven models, Data Fusion and Citizen sciences) towards building new directions in applied research and innovative services for public health, such as outbreak forecasting and decision support modeling for vector control applications and other mitigation actions.

EYWA system is the outcome of the co-development conducted by the BEYOND Centre of EO Research and Satellite Remote Sensing of the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS) of the National Observatory of Athens, in collaboration with key core partners, the Ecodevelopment S.A. company specialized in mosquito control and data analytics, and the Laboratory of Atmospheric Physics of the University of Patras - Physics Department specialized in mathematical modelling, and along with important European organisations from Italy, France, Germany and Serbia, that serve research purposes, perform mosquito control activities, belong to health and decision making sectors. The partnership scheme is open to include new partners from other European countries. For the time being it is comprising of the following partners:

  EYWA leaflet in GR & EN

greeceGreece

National Observatory of Athens (NOA) – BEYOND Centre of EO Research & Satellite Remote Sensing,

Ecodevelopment S.A

Dimitrios Vallianatos (I.D.Com)

University of Patras – Physics Department - Laboratory of Atmospheric Physics (LapUP)

Aristotle University of Thessaloniki

University of Thessaly, Medical School. Laboratory of Hygiene and Epidemiology

greeceSerbia

University of “Novi Sad” Faculty of Agriculture

University of Novi Sad, Faculty of Medicine

Scientific Veterinary Institute "Novi Sad" (NIV)

 
greeceGermany

German Mosquito Control Association (KABS)

Bernhard Nocht Institute for Tropical Medicine

greeceFrance

EID Méditerranée

greeceItaly

Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe)

Edmund Mach Foundation

University of Trento

 

 

 

 

 

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BEYOND Centre of Earth Observation Research and Satellite Remote Sensing, of the National Observatory of Athens, has launched an online Web GIS platform that is closely monitoring the global spread of COVID-19, aiming to actively provide robust and accurate information about the pandemic.

The live dashboard pulls data from official sources, specifically, the ECDC (European Centre for Disease Prevention and Control- https://www.ecdc.europa.eu/en) as well as the HNPHO (Hellenic National Public Health Organization-https://eody.gov.gr/) and the media.

This is part of the Center’s wider initiative to deliver reliable and timely reporting to the general public at this critical time.

Track the coronavirus on http://webgiscovid19.beyond-eocenter.eu/

Το Κέντρο Κέντρο Επιστημών Παρατήρησης της Γης και Δορυφορικής Τηλεπισκόπησης BEYOND του ΕΑΑ, λειτουργεί από σήμερα μια Web GIS πλατφόρμα μέσω της οποίας ενημερώνουμε καθημερινά με την παγκόσμια εικόνα εξάπλωσης του COVID-19.

Η πλατφόρμα ενημερώνεται μέσω δεδομένων που παίρνουμε από ECDC (European Centre for Disease Prevention and Control- https://www.ecdc.europa.eu/en), ΕΟΔΥ
(Εθνικός Οργανισμός Δημόσιας Υγείας - https://eody.gov.gr/), και τις σχετικές
ανακοινώσεις που δίνονται στα MME.

Η πλατφόρμα είναι προσβάσιμη στον σύνδεσμο http://webgiscovid19.beyond-eocenter.eu/


satellite access v1 Click the Button to visit the Ground Segment DataHub Website

 

The Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens has been operating since 2014 and on a 24/7/365 basis a X/L Band acquisition antenna to receive EO data from eight different polar orbit satellites namely EOS/Terra, EOS/Aqua, SUOMI NPP, NOAA-20, FengYun-3B, NOAA-19, Metop-A, Metop-B. The raw satellite data are undergone a routine processing in real time so as to generate HDF products of higher level that are L1A, L1B and L2. The Ground Segment architecture is presented herein.

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MAIN OBJECTIVES & OUTCOMES

The EO Data Access Gateway is an application through which, the end user can search for and download satellite images from the aforementioned polar orbit satellites. The user is enabled to get access to L1 e.g. raw radiances of an instrument’s channel or L2 data such as predefined masks (eg. MODIS NDVI&EVI, VIIRS Active Fires, etc). The application is user friendly, providing the proper GUIs to perform data search and preview as well as downloading. It offers many different options for searching the data based on criteria such as acquisition time/period, satellite, sensor, and product type.

The application has been developed using Django and provides its own REST Application Programming Interface (API) based on the Django REST Framework.

The metadata are referring to a rolling archive of about 200.000 satellite images and higher-level products that have been acquired and stored during the last year. Images and products older that one year are not available on the rolling archive and could be potentially retrieved after direct communication with the Ground Segment at This email address is being protected from spambots. You need JavaScript enabled to view it.

CONTACT PERSONS

Application Development: This email address is being protected from spambots. You need JavaScript enabled to view it.
System Administrator: This email address is being protected from spambots. You need JavaScript enabled to view it.

The BEYOND Center is a living entity that constantly evolves its services through the development new scientific methods, and the exploitation of emerging technologies and state-of-the-art infrastructure for the extraction of higher level information and knowledge for the benefit of the citizen and the environment.

It is a key objective of the BEYOND Center to follow the Big Data paradigm shift and the ICT penetration into the Earth Observation domain. We have been actively participating into flagship European projects, conducting research and developing services in new domains other than natural disasters, which demand or benefit from the exploitation of enabling technologies; such as Machine Learning (ML), Artificial Intelligence (AI) and Distributed Computing.

Over that last years the team has conducted advanced research and had developed mature services, through the combination of mature Remote Sensing technologies and state-of-the-art ICT and AI solutions, in the domains of sustainable agriculture, food security, geohazards and energy.

Alternative application domains / Big Earth Data Analytics

The Big Earth Data that we continuously receive from multiple sources, such as satellites, in situ sensors is multi-dimensional by nature. In order to effectively exploit these data, we need to efficiently combine information of different spatial, temporal and spectral characteristics.

Therefore, we need to efficiently organize this kind of datasets, into structures that will in turn feed complex AI algorithms. The Data Cube structure constitutes a scalable solution of multi-dimensional databases proposed and adapted the last years for the Big Earth Data domain. Data Cubes gain more and more popularity in the EO sector and evolve rapidly towards solving issues, such as the multiple data sources fusion, centralized access, analysis ready data presentation, storage etc.

Below follow some indicative success stories of utilizing advance AI and ICT technologies for the thematic areas of Agriculture, Geo-hazards and Energy.

  • Earth Observation, Machine Learning and Distributed Computing at the service of Food Security monitoring (EOPEN H2020 project)

Food security requires the large-scale monitoring of agricultural land and the extraction of quality knowledge from EO data at the national level. It becomes apparent that certain Big Data considerations come into play, including the effective storage and processing of an immense volume of data (tens of TBs). For this reason, we have utilized High Performance Data Analytics environments to store our data, using the Hadoop Distributed File System (HDFS) and to employ distributed implementations of supervised (Random Forest) and unsupervised learning (K-Means), using the analytics engine Apache Spark. More information can be found in this link.

  • Earth Observation (EO), Machine Learning (ML) and High Performance Computing (HPC) at the service of Solar energy monitoring and short-term forecasting (EuroGEO e-shape project)

The continuous monitoring and short-term forecasting of solar energy potential at continental level require ultra fast radiative transfer models (RTM), high resolution EO data and sophisticated prediction algorithms. To this direction we exploit ML and distributed computing architectures for instantaneous RTM simulations (i.e. 25 million/min), motion flow techniques for cloud microphysics forecasting (up to 6 hours ahead at 15-min intervals) as well as Copernicus Atmosphere Monitoring Service (CAMS) and EUMETSAT's Nowcasting Satellite Application Facilities (SAFNWC) for realistic aerosols and clouds impact on solar power. The use of HPC provides operationally and in real-time a tremendous solar data production flow (i.e. 550 Gb/day), forming the nextSENSE energy management system for the European and North African region. More information can be found here.

  • Earth Observation (EO), Machine Learning (ML) and Distributed Computing Computing (HPC) for landslide susceptibility mapping (NextGEOSS project)

Systematic ground deformation mapping is critical for a number of applications that model the impact of geophysical (e.g. earthquakes, volcanoes, landslides) and manmade (water extraction, mining, underground works, dams construction) activities, and assess geohazard risk. We have re-engineered a Persistent Scatterer Interferometry processing chain for distributed execution on a cloud environment. We have used this chain to exploit the frequent Sentinel-1 acquisitions and enrich a landslides inventory for a large area in Greece. Using this inventory as input data we have trained a statistical model that maps landslide driving factors (topography, climate/meteorology, geology, etc.) to the observations, creating a landslides susceptibility product. More information can be found here.


satellite access v1 Click the Button to visit the Sentinel Access Point

 

Searching for Sentinel data is often a complicated process due to the different missions available, the different Copernicus Sentinel Hubs that host data and geographic restrictions, but also the different performances of the Hubs in terms of download speed and latency (at both the inter and intra level). Thus, at BEYOND Center of EO Research and Satellite Remote Sensing we developed a service,  the Umbrella Sentinel Access Point, that brings the various Sentinel Access Points all together in a one stop shop (the so called federated access) offering uniform access to Sentinel 1, Sentinel 2, Sentinel 3, and Sentinel 5p metadata. This is done via connecting at the back end to a number of the available Copernicus Sentinel Data Sources and serving the data search results via a front end catalogue and an Application Programming Interface (API).

On the plus side the applications we have developed will be a solution for RO that will be the cheapest, has the best availability in terms of data access, matches the timeliness performance of the best performing Hub, and also secures downloading from the Hub with the highest, at the time, download capacity if the same product exists in more than one Hub.

On the cons side, our application will have to use as many accounts, as the number of Hubs it connects to. If we connect to 10 different Hubs then we will need 10 different accounts to be created once following the ESA policy on data download and user tracking.

Umbrella Sentinel Access Point

  • Independent of the API’s architecture; It can connect to any API under certain prerequisites.
  • Provision of the download link from the most appropriate hub for any requested product at a particular instance.
  • Scoring process for identifying the most appropriate Sentinel Access Point takes places every 15 minutes
  • API Offer, no GUI.
  • Ten connected hubs

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RELATED SERVICES & PLATFORMS

The Sentinel data federated gateway is accessed through the Application Programming Interface (API) directly from the Hellenic Mirror Site :https://sentinels.space.noa.gr/dhus/#/home

CONTACT PERSONS

Application Development of Umbrella Sentinel Access Point: Athanasios Drivas, tdrivas[at]noa.gr

General Contact Person: Vassileios Sitokonstantinou, vsito[at]noa.gr

  1. European Forest Fire Information System (EFFIS)
  2. SolarHub
  3. FloodHub
  4. ClimaHub