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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.