Remote sensing PD-OTKA
Earth observation is a growing field of interest in various application areas, such as monitoring agricultural activity, detection of pollution and environmental crimes, management of urban area expansion, crisis management, including civil protection, or homeland security. However, the evaluation of the collected remotely needs exhausting human intervention up to now due to the rich and continuously augmenting content and various aspects of assessment. For this reason, necessity of automated recognition problems in remote sensing is raised by both national and international demands.
The work will focus on the research towards a generalized framework and procedure library for representing different targets, hierarchic structures and various levels of changes using remotely sensed 2-D images and 3-D (LIDAR, ISAR or DEM) data. The developed methods attempt to collect similar tasks appearing in different application areas, and handle them in a joint methodological approach. An important feature of the proposed models will be the separation of the data and application dependent elements from the abstract hierarchical structure which has various levels, such as pixel, region, object, object group and land cover class. Task definitions will origin from specific applications, followed by problem grouping, abstraction and generalization.