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The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to
support regional and global scientific research widely. Remote sensing product with different sensors and different
algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote
sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method
of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface
types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty
information of the remote sensing products based on a amount of in situ data and the validation techniques.
The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem,
Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read
service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules,
Scale-Change service modules and so on. To run the validation system platform, users could order these service modules
and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as
LAI ,ALBEDO ,VI etc.) .
Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service
modules which could be independent of any development environment by standards such as the Web-Service
Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to
create service modules.
One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that
the LAPVAS has a good performance to implement the land surface remote sensing product validation.
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