DECAIR Development of an Earth Observation Data Converter with Application to Air Quality Forecast
by Jean-Paul Berroir and Francois Llirbat
The objectives of the DECAIR project are to provide air pollution models with good quality input data derived from earth observation (EO) satellites data, and to design a system prototype able to provide models with their required data, under specific quality and freshness constraints.
One of the major objective of the DECAIR project is to investigate the use of remote sensing data to estimate input data for air quality models. According to the nature and usage of the data, different kind of input data are under investigation: data required for documenting the studied area (elevation, land use); meteorological, initialisation and emission data, required on a daily basis; finally parameters required by the models for their internal modules, such as surface uptake, energy balance, turbulence, etc. In our investigation we first conduct an analysis of users requirements (authorities, companies in charge of delivering pollution measures, modelers), in order to specify the needs for high quality input data. Then, an analysis of data requirements will be conducted in order to select the appropriate satellite sensors and processing methods to estimate these input data. Finally, a prototype will be built that delivers up-to-date land use data and daily radiation data to models. A sensitivity analysis will be carried out to select critical model parameters, and to investigate remote sensing data analysis methods able to estimate these parameters.
The second major objective is the design of a Data Management System. This system has to be able to access, process and integrate data from various remote data sources like satellites, ground stations, etc., in order to maintain high quality input data for various final users like models users (the scientists designing and running models), companies and authorities at different sites, public). The system architecture is designed to fulfill objectives which are specific to the DECAIR project, i.e. to give the different air pollution models high quality EO-processed input data, and to automatically enforce accuracy and freshness of these data. It is also designed for long term objectives, such as easy adaptation of air quality models to a new application sites.
The architecture is based on modern concepts and techniques already addressed in other projects, for instance in the telematics domain: the Mediator technology will be used to process queries over an integrated logical view of all the data sources. A Monitor is responsible for governing the execution of queries, the call of data processing modules, the loading of the processed data to the DECAIR database and the access to this database by the final users. The design of the DECAIR database will handle the technical constraints related to the large number of image data to be stored and their relation to Graphical Information Systems. Communications between these components as well as dissemination of results to end users and public authorities will base on WWW technologies.
The DECAIR project is carried out with a strong concern of compatibility with concepts and standards developed by other projects in environmental information systems and telematics technologies. DECAIR involves research teams specialized in air quality modelling: GMD Institute for Computer Architecture and Software Technology and UPM, Spain, environmental information systems: INRIA, CLRC-RAL, FORTH-ICS, satellite image analysis: INRIA and industrial partners BULL and SICE. The applicative objectives of the project are to demonstrate the ability of satellite data to enhance the quality of air quality simulation, and to facilitate the implementation of an air quality model to new sites. The project will be demonstrated in the cities of Berlin and Madrid. It started June 1st, 1999, and its duration is 36 months. The project is administered by ERCIM.
Decair home page: http://www-air.inria.fr/decair
Isabelle Herlin - INRIA
Tel: +33 1 39 63 54 17