In the paper a methodology of RS-based thematic mapping is introduced which uses an original RS imagery interpretation approach. The implementation of the methodology is based on application of GIS MapInfo Professional and original imagery processing and interpretation system "LandMapper" developed in Tomsk Polytechnic University (TPU). The paper considers the basic principles of imagery interpretation approach adopted in the "LandMapper" system as well as gives the results of its application for Tomsk region oil-fields pollution mapping with use of high resolution images acquired by QuickBird satellite.
The paper proposes an idea of the adaptive classification procedure (ACP) making the process of remotely sensed (RS) data classification more flexible and efficient in comparison with existing recognition methods. The ACP employs an improved scheme of forming feature space and adaptive decision rule allowing an optimal imagery classification method to be chosen during thematic processing. In the paper the basic principles of the ACP design and the results of its classification methods efficiency research are considered. Also the results of the ACP application for solving problems of landscape-ecological mapping of Lake Chani area (Omsk region, Russia) and Pervomayskoe oil field (Tomsk region, Russia) using multispectral images from Russian satellite RESURS-O1 are shown.