1. GNORASI vision and achievements, Future perspectives Panagiotis Symeonidis Environmental Physicist, M.Sc., Ph.D. Technical Director DRAXIS Environmental S.A.

2. The needs  To be able to easily handle remote sensing data  To help users into the interpretation of data  To automate specific user needs through customized workflows

3. The Vision  To develop an integrated information system, which will be:  Modular  Open structured  Adaptable  Extendable  User friendly

4. The Vision   Knowledge based image analysis methods   state of the art image processing algorithms   easy to use GUI   predefined workflows and knowledge bases for various remote sensing applications

5. The project  Partners: 4  Research: CERTH, NTUA  Companies: DRAXIS, ALTEC  Duration: 36 months  Effort: Over 180 MM

6. The GNORASI platform  GNORASI is a modular platform that consists of:  GNORASI API: for the development of new modules  GNORASI GUI: Graphical User Interface for the development / customization of remote sensing workflows

7. GNORASI is OPEN SOURCE   Free software (available in a aiolos source repository)   Released under GPL v2   Cross platform (Linux, Windows, OSX)   Written in C++

8. GNORASI technological Framework   QT Framework (cross platform application and UI framework)   Voreen open source VOlume REndering ENgine used in medical applications   Orfeo Toolbox (OTB). Open source library of image processing algorithms   ITK open source cross platform system for image analysis   GDAL translation library for raster geospatial data formats   PROJ4 cartographic projections library   OSSIM suite of geospatial libraries

9. Achievements   Object-based image analysis   Development of processing flows through an intuitive GUI   User friendly workspace, suitable for rapid prototyping   True modular architecture   Easy integration of new algorithms and functionalities, as modules   Module integration either locally or as services (e.g. web services)

10. Achievements   Semantic representation of geospatial and visual feature data   Classification based on semantic object representation and fuzzy rules   Integration of more than 150 OTB processors   Platform Independent

11. The Users Researchers Remote sensing developers GIS consultants / companies End Users and clients from the private and public sector

12. The Users Ministry of Rural Development and Food Ministry of Environment, Energy & Climatic Change Ministry of Public Order & Citizen Protection Ministry of Marine Organization of Agricultural Insurances National Level (Ministries) Regions / Prefectures Municipalities Regional Level (Local Authorities)

13. Fields of Application   Fire areas management   Natural disasters mapping and evaluation   Identification of land uses   Urban planning   Pollution accidents   Coastal zones monitoring   Environmental management   Monitoring of illegal constructions

14. Future development To integrate GNORASI with an existing open source GIS software To extent the algorithms To include more use cases To offer some functionalities through a web based interface To further develop GNORASI platform To reach our market To offer services related to GNORASI To work with real clients

15. Conclusions  GNORASI is an innovative tool for handling remote sensing data  Real life use cases illustrate the reliability and the applicability of the platform  GNORASI could be easily applied in various sectors

16. http://www.gnorasi.gr