There are basically two levels of calibrations and validation of digitally acquired spectral and other information via sensors carried on space-borne or airborne platforms.The basic level is carried out by the data producers executed by comparison made of results taken over test fields for example.The second level, more a part of a supervised classification effort are carried by the data users and value added spatial information users or providers Figure Skating - Skates - Girls to edge users.The latter is quite typical for supervised classification protocols.This is either for establishing libraries of spectral signatures for each relevant class-type or for ad-hoc classification where no previous information or specific knowledge wee kept.
Such methods indicate and support even strongly the need of the basic Cal/Val step of the sensors made by the original data providers.The paper is reviewing the method of database-driven concept that allows for automatic recognition of detected features within the digital spatial 2-D (yet) realm to its identification within the digital 2.5D spatial vector information within Votive existing large Big-data national core spatial data bases to be updated.These Large data bases are Big enough to operate the resourceful Munchhausen method of self-pulling information out of the huge abandon of data resources.