This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Search for Publication

Year(s) from:  to 
Keywords (separated by spaces):

Image Information Mining and Remote Sensing Data Interpretation

M. Datcu, K. Seidel, A. Pelizarri, M. Schröder, H. Rehrauer, G. Palubinskas and M. Walessa
IEEE Intern. Geoscience and Remote Sensing Symposium IGARSS
July 2000


The new generation of high resolution imaging satellites acquires huge amounts of data which are stored in large archives. The state-of-the-art systems for data access allow only queries by geographical location, time of acquisition or type of sensor. This information is often less important than the content of the scene, i.e. structures, objects or scattering properties. Meanwhile, many new applications of remote sensing data are closer to computer vision and require the knowledge of complicated spatial and structural relationships among image objects. We are creating an intelligent satellite information mining system, a next generation architecture to help users to gather rapidly information during courses of actions, a tool to add value and to manage the huge amount of historical and newly acquired satellite data-sets by giving to experts access to rele- vant information in an understandable and directly usable form and to provide friendly interfaces for information query and browsing.

Download in pdf format
  author = {M. Datcu and K. Seidel and A. Pelizarri and M. Schr\"oder and H. Rehrauer and G. Palubinskas and M. Walessa},
  title = {Image Information Mining and Remote Sensing Data Interpretation},
  booktitle = {IEEE Intern. Geoscience and Remote Sensing Symposium IGARSS},
  year = {2000},
  month = {July},
  keywords = {Information Mining, Remote Sensing}