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

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

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

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

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

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

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

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

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)

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

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

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)

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

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

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