Application of Data Mining Techniques for Remote Sensing Image Analysis
نویسندگان
چکیده
The paper studies the applicability of various data mining techniques on aerial remote sensing imagery for automatic land-cover classification. Four techniques are applied, namely the Adaptive Dynamic K-means (ADK), Self Organizing Feature Map (SOFM), Machine Learning Induction Algorithm (C4.5) and Support Vector Machines (SVM). Special attention is drawn to the usefulness of these data mining classification techniques for automatic land-cover recognition, that is, for physical interpretation of the classes. A novel, hybrid ADK-SOFM-SVM data mining procedure suitable for automated land-cover cluster analysis is presented.
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