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This study compiles primarily the word structure of Modern Mongolian language and further more focused on the possibilities of description of Mongolian language in PC KIMMO, a two level processing method of morphological parsing. The rules file and lexicon presented in the paper describe the morphology of Mongolian words. A lexicon containing the root words of contemporary Mongolian is used in the testing. As a result the two-level morphology is determined as completely possible to be used for Mongolian linguistics. In addition PC-KIMMO description of traditional Mongolian script is considered as being possible.

We present in this paper some results obtained in the field of space geodesy based on continuous GPS observations at the Astronomical Observatory of Mongolia. Starting with a brief historical overview of the main space geodetic activities carried out by the Astronomical Observatory in the past, we outline here current achievements in the application of GPS techniques in the geosciences research in Mongolia. We setup a local GNSS Data Center of the Mongolian Academy of Sciences to receive, quality control and process into derivative products the observation data coming from its continuously recording stations. The quality check performed on three non-real-time permanent stations reveals that all three stations show smooth trends of each parameter indicating good quality in data record and operation without any anomalous behavior.

The aim of this study is to explore the performances of different data fusion techniques for the enhancement of urban features and evaluate the features obtained by the fusion techniques in terms of separation of urban land cover classes when multisource images are under consideration. For the data fusion, multiplicative method, Brovey transform, principal component analysis (PCA), Gram–Schmidt fusion, wavelet-based fusion and Elhers fusion are used and the results are compared. Of these methods, the best result is obtained by the use of the optical/synthetic aperture radar (SAR) wavelet-based fusion. The classification methods of multisource images, statistical maximum likelihood classification (MLC) and the knowledge-based method are used and the results are compared. The knowledge-based method is based on a hierarchical rule-based approach and it uses a hierarchy of rules describing different conditions under which the actual classification has to be performed. Overall, the research indicates that multisource information can significantly improve the interpretation and classification of land-cover types and the knowledge-based method is a powerful tool in the production of a reliable land-cover map. [ABSTRACT FROM PUBLISHER]